Most recent papers:

• Pricing Parisian and ParAsian Options by a Vectorized Binomial or Trinomial Tree.
  James X. Wu, Tao Wu.
  Journal of Futures Markets. 6 days ago
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nWe extend binomial and trinomial trees to price European and American style Parisian and ParAsian options by keeping track of a vector of option prices under different scenarios at each tree node. We also incorporate the method for choosing the number of time‐steps that will yield more precise price estimates. The vectorized tree models can easily price exotic path‐dependent options such as American double barrier Parisian options and look‐back options, which present challenges to other existing methods.\n"]

  April 25, 2026   doi: 10.1002/fut.70110   open full text
• Facts and Fantasies About DeFi: Lending, DEX, and Derivatives.
  Grigoriy Korolev.
  Journal of Futures Markets. 7 days ago
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nWe explore the risk‐return tradeoff of Decentralized Finance (DeFi). We construct three novel indices for different asset classes: Lending, Decentralized Exchanges, and Derivatives. Motivated by the cryptocurrency pricing framework of Liu and Tsyvinski, we investigate how DeFi assets comove with financial primitives. We document limited correlation with traditional equities, currencies, interest rates, and commodities. We further examine several DeFi‐specific factors. Bitcoin and Ethereum returns show no significant association with subsequent DeFi returns, highlighting a decoupling between base‐layer assets and application‐layer protocols. Meanwhile, we find some in‐sample associations with DeFi‐specific factors such as momentum, investor attention, and performance of centralized platforms. A novel book‐to‐market ratio constructed using Total Value Locked and market capitalization does not display a systematic relationship with returns. Finally, we find only limited and sector‐specific associations with traditional equity industries.\n"]

  April 24, 2026   doi: 10.1002/fut.70111   open full text
• How Does Economic Policy Uncertainty Reshape Option Pricing?
  Wenting Chen, Rixiang Fei, Nana Xu, Xin‐Jiang He.
  Journal of Futures Markets. 7 days ago
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nEconomic policy uncertainty (EPU) is a critical yet often neglected factor in derivatives pricing, leading to systematic biases in existing valuation frameworks. This study proposes an advanced pricing model that explicitly incorporates a stochastic EPU factor with a regime‐switching long‐term mean into the stochastic volatility framework. The principal theoretical contribution of this research is a closed‐form analytical pricing formula for European options, which successfully overcomes the challenges of multiple stochastic factors and achieves substantial computational advantages over traditional numerical methods such as the Monte‐Carlo simulation. A preliminary empirical study using SSE 50 ETF option data demonstrates the model's superior pricing performance compared to other benchmarks.\n"]

  April 24, 2026   doi: 10.1002/fut.70102   open full text
• Forecasting Natural Gas Futures Price Volatility of the United States: National Versus State‐Level Climate Concern Indexes.
  Afees A. Salisu, Ahamuefula E. Ogbonna, Rangan Gupta, Onur Polat.
  Journal of Futures Markets. 10 days ago
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nThis paper uses GARCH‐MIDAS to predict US natural gas futures volatility using national and state‐level Climate Concern Indexes (CCIs). We find that both national and state‐level CCIs positively affect price volatility. Notably, models using state‐level data—specifically those utilizing least‐squares (LS) weighting combinations—surpass the GARCH‐MIDAS‐GECON benchmark and models relying solely on national CCI. These findings deliver substantial statistical and economic utility gains. Our results underscore the importance of incorporating heterogeneous climate concerns across US states to capture varied demand‐supply conditions when forecasting energy market volatility.\n"]

  April 21, 2026   doi: 10.1002/fut.70108   open full text
• Fund Extreme Performance and Heterogeneous Investor Choice: Evidence From Smart Beta ETFs.
  Xiaoqun Liu, Youcong Chao, Yihao Huang, Hangjian Yu.
  Journal of Futures Markets. April 14, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nThis study investigates how extreme return components (MAXs) of smart beta exchange‐traded funds (ETFs) influence heterogeneous investor choice. We find that extreme overnight returns (overnight MAXs) have substantial ETFs' flow predictability above and beyond that provided by standard risk, performance, and market‐timing measures. This suggests that individual investors tend to choose funds based on historical overnight MAXs. The persistence of overnight MAXs supports the lottery preference theory, which posits that retail investors disproportionately focus on the likelihood of high payoff states in a fund's past return distribution. Furthermore, we demonstrate that overnight and intraday MAXs negatively and positively predict future smart beta ETFs' performance, respectively. This divergence indicates that heterogeneous investors hold varying beliefs and employ distinct trading activities with respect to those lottery‐like fund return distributions. Finally, we show that investor attention is beneficial to explain our findings.\n"]

  April 14, 2026   doi: 10.1002/fut.70105   open full text
• Intraday Liquidity in International Crude Oil Futures Markets: News Impacts, Commonality, and Spillovers.
  Hong Miao, Jian Yang.
  Journal of Futures Markets. April 14, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nUsing tick‐by‐tick data, this study examines intraday liquidity of WTI, Brent, and INE crude oil futures. US EIA inventory announcements significantly affect intraday returns and, to a lesser extent, liquidity across all three markets. We document strong commonality in intraday liquidity, largely driven by supply‐side factors, and find that WTI is the dominant source of liquidity spillovers, a pattern not mirrored in return spillovers. These findings highlight different mechanisms behind liquidity commonality and return comovements. The results are robust to additional control variables and alternative liquidity measures.\n"]

  April 14, 2026   doi: 10.1002/fut.70106   open full text
• Time Integrals Under the Black–Scholes–Merton and Margrabe Economies.
  José Carlos Dias, Mark B. Shackleton, Fernando Correia da Silva, Rafał M. Wojakowski.
  Journal of Futures Markets. April 14, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nThe problem of integrating the Black, Scholes, and Merton (BSM) formula with respect to the time variable is paramount for an economist. Inspired by the real options literature, Shackleton and Wojakowski offer analytic formulae for valuing finite maturity (profit) caps and floors that are contingent on continuous flows following a lognormal distribution. Alternative, but equivalent, closed‐form solutions have been recently proposed in Dias et al. by solving the time integral of options using a direct approach that does not rely on the real options intuition. This paper further extends and simplifies the computation of time integrals under the BSM world, considering not only plain‐vanilla but also several exotic, including path‐dependent options. We also provide a new closed‐form solution of the time integral under the Margrabe economy. The method proposed in this paper makes the evaluation easier, cements the “non‐real options” route and opens the way for more analytical work in BSM, Margrabe, and other areas.\n"]

  April 14, 2026   doi: 10.1002/fut.70107   open full text
• The Role of Price‐Volatility Cojumps in Volatility Forecasting.
  Kefu Liao.
  Journal of Futures Markets. April 08, 2026
  ["Journal of Futures Markets, Volume 46, Issue 5, Page 931-951, May 2026. ", "\nABSTRACT\nThis paper investigates whether simultaneous jumps in prices and volatility improve volatility forecasting. Using up‐to‐date high‐frequency S&P 500 and VIX data, we identify price‐volatility cojumps at the intraday granularity and construct upside, downside, and asymmetric measures. Embedding these into the Heterogeneous Autoregressive (HAR) model, we provide new empirical evidence that downside cojumps increase future volatility, upside cojumps reduce volatility. Out‐of‐sample analysis further shows that incorporating these impacts of cojumps significantly enhances HAR model forecasting performance. Moreover, our results reveal that recent price jumps become important predictors of volatility when accompanied by simultaneous volatility jumps, an effect not previously documented in the literature. Finally, we also document the economic interpretation, policy implications, and economic value of price‐volatility cojumps.\n"]

  April 08, 2026   doi: 10.1002/fut.70091   open full text
• Connectedness Across Healthcare Cryptocurrencies, DeFi, and NFTs Tokens: Which Global Risk Factors Should Be Given More Attention?
  Nasir Khan, Khaled Guesmi, Tong Su, Brian Lucey.
  Journal of Futures Markets. April 08, 2026
  ["Journal of Futures Markets, Volume 46, Issue 5, Page 878-903, May 2026. ", "\nABSTRACT\nThe study examines interconnectedness among categories of cryptocurrencies, healthcare cryptocurrencies, decentralized finance indices (DeFi), and non‐fungible tokens using TVP‐VAR extended joint connectedness, based on daily data from September 4, 2019, to July 31, 2024. The outcomes indicate that DeFi is the return shock and leading net transmitter, while healthcare cryptocurrencies are the net receivers. Secondly, we also analyze the effect of four news‐based global uncertainties on total returns using the BVAR model. The outcomes reveal that geopolitical risk (GPR) does not significantly influence global connectedness; however, some individual DeFi protocols, such as Chain Link, Tezos, and Maker, respond positively to GPR. Conversely, economic policy uncertainty reduces the total connectedness index, while infectious disease equity market volatility increases it. Using weekly data covering cryptocurrency uncertainty indices, exerts a positive effect on total return connectedness. The findings underline the influential crypto assets and should be monitored by investors and policymakers.\n"]

  April 08, 2026   doi: 10.1002/fut.70085   open full text
• Trading Periodicity and Algorithmic Divide in Cryptocurrency Markets.
  Andrei Shynkevich.
  Journal of Futures Markets. April 08, 2026
  ["Journal of Futures Markets, Volume 46, Issue 5, Page 904-930, May 2026. ", "\nABSTRACT\nDistinctive periodic patterns in trading activity at subsecond frequencies are present in the spot market and perpetual futures for Bitcoin and Ethereum at the major cryptocurrency exchange. Trading periodicity in the spot market is indicative of agency algorithms taking liquidity. The periodic pattern of trading activity in perpetual futures is symbolic of proprietary algorithms taking liquidity. Periodic surges in trading activity recurring at regular time intervals increase volatility and raise transaction costs, but they do not cause a significant adverse price impact. The largest share of price discovery occurs during the periods of trading activity associated with proprietary algorithms taking liquidity.\n"]

  April 08, 2026   doi: 10.1002/fut.70089   open full text
• Downside Risk and Agriculture Commodity Futures Returns: A Study Using Self‐Organizing Maps.
  Santanu Das.
  Journal of Futures Markets. April 08, 2026
  ["Journal of Futures Markets, Volume 46, Issue 5, Page 863-877, May 2026. ", "\nABSTRACT\nThis study analyzes downside risk and nonlinear dependence in agricultural commodity futures using a hybrid framework that integrates Self‐Organizing Maps (SOMs) with Copula‐based dependence modeling. Agricultural returns exhibit asymmetric behavior, making linear correlation inadequate for risk assessment. The SOM identifies distinct market regimes based on return dynamics and volatility structure, while Student‐\nt and Clayton copulas quantify symmetric and lower‐tail dependence within each regime. Results show a clear escalation of dependence from tranquil to crisis states, with tail‐dependence coefficients rising monotonically across SOM clusters. The Student‐\nt copula captures symmetric co‐movements in extreme returns, whereas the Clayton copula highlights strong joint downside risk during high‐volatility phases. These patterns confirm that diversification benefits across agricultural commodities weaken substantially under stress. The proposed SOM–Copula hybrid framework provides a regime‐sensitive approach to modeling tail interdependence in commodity markets.\n"]

  April 08, 2026   doi: 10.1002/fut.70088   open full text
• Forecasting Crude Oil Volatility With Geopolitical Risk: The RSV–MIDAS–GPR Model and Its Economic Value.
  Ke Yang, Xuebao Yin, Fengping Tian.
  Journal of Futures Markets. April 08, 2026
  ["Journal of Futures Markets, Volume 46, Issue 5, Page 824-842, May 2026. ", "\nABSTRACT\nThe paper proposes a new integrated realized stochastic volatility–mixed data sampling–geopolitical risk (RSV–MIDAS–GPR) model to model and forecast crude oil futures volatility. The model jointly models returns and the realized measure of volatility, leverages contemporaneous volatility information, and captures the effects of GPR on crude oil futures volatility. The empirical results demonstrate a significant positive correlation between GPR and crude oil futures volatility. Meanwhile, the RSV–MIDAS–GPR model, which incorporates both GPR and realized volatility, exhibits a synergistic effect, leading to a substantial improvement in out‐of‐sample forecasting performance. Furthermore, the model demonstrates notable capability in identifying high‐volatility states and achieves higher forecasting accuracy than competing models during market turmoil. Finally, economic value tests confirm that the inclusion of GPR provides valuable guidance for investor decision‐making. These findings offer both methodological and empirical contributions to the related research field.\n"]

  April 08, 2026   doi: 10.1002/fut.70084   open full text
• Oil Futures Prices, Inflation Expectations, and Bond Risk Premiums.
  Haibo Jiang.
  Journal of Futures Markets. April 08, 2026
  ["Journal of Futures Markets, Volume 46, Issue 5, Page 779-798, May 2026. ", "\nABSTRACT\nBy decomposing West Texas Intermediate futures price changes into structural supply and demand shocks, this paper shows that dissecting the oil price significantly improves inflation forecasts. Empirically, demand‐driven shocks predict a negative real bond risk premium but a positive inflation risk premium; these opposing effects result in an insignificant net effect on the nominal bond risk premium. A two‐sector New Keynesian model formalizes the dynamics among oil shocks, inflation, and bond yields, reconciling two distinct historical episodes: anchored inflation during the 2000s oil crisis and the surge in tandem with oil prices following the 2022 Russian invasion of Ukraine.\n"]

  April 08, 2026   doi: 10.1002/fut.70083   open full text
• VIX Term Structure in the Rough Heston Model via Markovian Approximation.
  Yifan Ye, Zheqi Fan, Yue Kuen Kwok.
  Journal of Futures Markets. April 08, 2026
  ["Journal of Futures Markets, Volume 46, Issue 5, Page 799-823, May 2026. ", "\nABSTRACT\nWe model the VIX term structure using the rough Heston model. Since the direct numerical modeling of the rough Heston model is computationally inefficient, we adopt a Markovian approximation approach. Building on the Markovian framework, we eliminate the need for simulation by exploiting an analytical expression for VIX. The resulting formula for squared VIX under the Markovian approximation provides an analytical approximation to its counterpart under the rough Heston model. Another efficiency in the calibration procedure is achieved by exploiting the analytical gradient formulas of squared VIX. Empirically, using an extensive dataset of daily VIX term structures, we show that the rough Heston model outperforms various competing Heston‐type models with jumps in both in‐sample and out‐of‐sample fit and yields more reliable estimates of spot volatility, validating that rough volatility is preferred to jumps in modeling VIX term structure.\n"]

  April 08, 2026   doi: 10.1002/fut.70082   open full text
• Harnessing Sunshine: A Dynamic Spillover Analysis of the Diversification Effects of China's Photovoltaic Weather Index.
  Yu Wei, Yue Shang, Qian Wang, Xiaodan Chen.
  Journal of Futures Markets. April 08, 2026
  ["Journal of Futures Markets, Volume 46, Issue 5, Page 843-862, May 2026. ", "\nABSTRACT\nThis paper investigates the diversification effects of China's new photovoltaic weather index (PVWI) on commodity portfolios. Using a TVP‐VAR spillover analysis, we find the PVWI is highly insulated from the commodity system, acting as a net shock receiver and confirming its diversification potential. We then construct novel “minimum‐connectedness portfolios” (MCoP). Results show that portfolios incorporating the PVWI, particularly the MCoP, significantly enhance risk‐adjusted returns and demonstrably outperform traditional minimum‐variance benchmarks. This study validates the practical benefits of well‐designed weather derivatives and the superiority of spillover‐aware asset allocation frameworks.\n"]

  April 08, 2026   doi: 10.1002/fut.70087   open full text
• Commodity Futures Report Text Sentiment and Returns.
  Qian Han, Pei‐lin Hsieh, Lu Zhang.
  Journal of Futures Markets. April 06, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nThis paper investigates how textual sentiment in analyst research reports influences commodity futures returns in China. Using the Natural Language Processing and Information Retrieval platform to analyze a comprehensive sample of reports from 2016 to 2021, we construct sentiment indices for 37 commodity futures across agriculture, metals, chemicals, and energy sectors. Our results show that text sentiment significantly explains both contemporaneous and future returns, with negative sentiment having a stronger impact. Increased optimism is associated with higher contemporaneous returns through investor sentiment and attention channels, especially for future contracts with low open interest growth, low volatility, a contango market (futures premium), and high basis‐momentum. We document heterogeneous results for subsequent returns and the three main risk premium factors. The findings remain robust after controlling for established pricing factors and macroeconomic variables. This study highlights the informational value of analyst sentiment, filling a gap in text sentiment research within the commodity futures market and offering insights for investors and policymakers.\n"]

  April 06, 2026   doi: 10.1002/fut.70090   open full text
• Trader Attention and Market Reaction to Fundamental News: Evidence From Natural Gas Futures.
  Chen Gu, Alexander Kurov, Raluca Stan.
  Journal of Futures Markets. April 02, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nThis paper examines the effect of trader attention on the response of the natural gas market to weekly US Energy Information Administration announcements regarding changes in natural gas inventories. We find that lower trader attention hinders price discovery in the natural gas futures market. Based on our daily regression estimates, the market responds 74% weaker to inventory announcements released on Fridays, compared to those released on Thursdays. We attribute the findings to lower trader attention in the natural gas market on Fridays compared to other weekdays. The results remain robust after controlling for the withdrawal and injection seasons in the natural gas market.\n"]

  April 02, 2026   doi: 10.1002/fut.70104   open full text
• Analytically Pricing Commodity Futures Options Under Financialization With Stochastic Liquidity Risks.
  Wenting Chen, Fangzhao Zhou, Xin‐Jiang He.
  Journal of Futures Markets. April 02, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nIn this paper, we propose a liquidity‐adjusted pricing model in the context of commodity financialization, aiming at improving the pricing efficiency of commodity futures options. This model captures key characteristics of the real commodity market by integrating a basic two‐factor model with a financialization index and a market liquidity risk factor. Under this complicated four‐factor model, a closed‐form analytical solution for the price of commodity futures options is derived, which is then validated numerically. Through a preliminary empirical study, it is demonstrated that the current model surpasses other benchmarks, indicating the necessity of integrating both financialization and liquidity risks into the pricing of commodity futures options.\n"]

  April 02, 2026   doi: 10.1002/fut.70103   open full text
• Improving Implied Volatility Forecasts for American Options Using Neural Networks.
  Haitong Jiang, Emese Lazar, Miriam Marra.
  Journal of Futures Markets. March 29, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nThis paper explores the application of neural networks to improve pricing of American options. Focusing on both American and European options on the S&P 100 index from January 2016 to August 2023, we integrate neural networks to model the difference between market‐implied and model‐implied volatilities derived from the Black‐Scholes and Heston models. We also employ a pure neural network which does not use pricing models. Our study compares two neural network training architectures: independent training, where the network is trained anew daily, and sequential training, which uses the previous day's network setup as starting point to retrain the network. The findings reveal that a pure neural network with sequential training significantly reduces the root mean square error (RMSE) of implied volatility predictions compared to traditional pricing models. The inclusion of European option data in the training can enhance the models' forecasting performance, though its effectiveness varies depending on market conditions.\n"]

  March 29, 2026   doi: 10.1002/fut.70101   open full text
• Enhancing Commodity Futures Price Prediction With Geopolitical Risk Embedding: A Comparative Study of Deep Learning Models.
  Yong Li, Lulu Qin, Chenying Yang.
  Journal of Futures Markets. March 15, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nThis study uses daily closing prices of nine Chinese commodity futures from 2015 to 2023 to analyze price fluctuations and improve prediction reliability. It compares traditional time series model (ARIMAX), benchmark deep learning models (LSTM, GRU), and generative adversarial networks (GAN, WGAN), while also exploring the impact of geopolitical risk (GPR). The results show that deep learning models outperform traditional methods. LSTM and GRU excel at capturing temporal features, while WGAN offers superior versatility and stability, addressing GAN prediction flaws. Including GPR enhances forecasting accuracy for most commodities, revealing a dynamic correlation between GPR and commodity prices, with significant variation across different commodities. This study provides empirical evidence for the use of deep learning in financial time series forecasting and highlights the role of geopolitical risks in futures markets.\n"]

  March 15, 2026   doi: 10.1002/fut.70096   open full text
• Why Do Hedgers Hedge? The Role of Ambiguity.
  Fiona Höllmann.
  Journal of Futures Markets. March 12, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nThis paper investigates whether ambiguity influences hedging behavior in commodity futures markets. Using high‐frequency crude oil futures data, distinct measures of risk and ambiguity are linked to weekly hedging positions from the Commodity Futures Trading Commission (CFTC). The results show that ambiguity significantly affects hedging behavior beyond traditional risk measures. Importantly, different types of hedgers respond to ambiguity in opposing ways: Operational hedgers, who hedge direct exposure to physical prices, reduce their hedging pressure when facing ambiguity, while financial intermediaries, who hedge exposures from client contracts, increasing their hedging pressure. The findings are robust to alternative ambiguity measures, additional controls, and causal identification strategies. Instrument variable evidence supports the intermediary effects; for operational hedgers, results are directionally similar but not longer significant.\n"]

  March 12, 2026   doi: 10.1002/fut.70098   open full text
• Quadratic Hedging of American Options Under GARCH Models.
  Junmei Ma, Chen Wang, Wei Xu.
  Journal of Futures Markets. March 12, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nAmerican options are widely traded in financial markets, yet there is a scarcity of literature on hedging in incomplete markets. In this paper, we derive optimal hedging ratios and option values using Local Risk Minimization (LRM) and Global Risk Minimization (GRM) hedging strategies through dynamic programming. Then, by utilizing the willow tree structure, the ratios and values can be computed efficiently and accurately. Moreover, this method provides a comprehensive table of hedging strategies across possible asset prices and discrete times, rather than a single initial ratio. Finally, we examine the effectiveness of LRM, GRM, and Delta hedging, assuming the underlying asset follows two different GARCH models under both the physical (\n\n\nP\n\n\n ${\\mathbb{P}}$\n\n\n) and risk‐neutral (\n\n\nQ\n\n\n ${\\mathbb{Q}}$\n\n\n) measures. Our objective is to assess the added value of GRM over LRM and Delta hedging, the impact of using the \n\n\nP\n\n\n ${\\mathbb{P}}$\n\n\n versus \n\n\nQ\n\n\n ${\\mathbb{Q}}$\n\n\n measure for hedging, and the influence of hedging frequency on hedging errors.\n"]

  March 12, 2026   doi: 10.1002/fut.70099   open full text
• The Impact of Biodiversity Risk on US Agricultural Futures Markets.
  Hongjun Zeng, Mohammad Zoynul Abedin.
  Journal of Futures Markets. March 09, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nThis paper examines biodiversity risk (BOR) transmission to US agricultural futures markets. We find (1) all futures exhibit moderate‐to‐high biodiversity sensitivity, with coffee showing highest response through transparent price transmission mechanisms; (2) wavelet analysis reveals time‐frequency heterogeneity, where tropical crops maintain strong long‐term synchronization with BOR, intensified during COVID‐19; (3) frequency‐dependent asymmetric correlations emerge, with grains shifting from positive long‐cycle to negative short‐cycle correlations; (4) systemic spillover analysis indicates moderate interdependence, with soybeans as primary risk receiver and sugar as dominant transmitter, revealing differentiated transmission roles.\n"]

  March 09, 2026   doi: 10.1002/fut.70097   open full text
• Curve Momentum in China.
  Zhenlong Zheng, Yiye Liu, You Wu, Rong Chen.
  Journal of Futures Markets. March 09, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nIncorporating the distinct characteristics of the Chinese futures market, we implement a momentum strategy within the commodity futures curves. Our diversified curve momentum strategy yields significantly positive average excess returns, achieving a Sharpe ratio comparable to or exceeding those of traditional futures factors. These excess returns are difficult to reconcile with risk‐based explanations. We show that a behavioral mechanism based on investor herding plays a central role in generating the strategy's excess returns. A cross‐market comparison between China and the United States further shows that differences in maturity‐level liquidity structure condition whether herding‐driven trading pressure can propagate into persistent relative return continuation along the futures curve. The profitability of the strategy remains robust when subjected to tests of alternative formation and holding periods, weighting schemes, decision delays, transaction costs and definitions of the commodity cross section, and is not driven by narrow subsets of commodities.\n"]

  March 09, 2026   doi: 10.1002/fut.70093   open full text
• Asymmetric Option Returns in China.
  Xianzhen Wang.
  Journal of Futures Markets. March 09, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nThis paper documents two return asymmetries in China's options market: call (put) returns are positive (negative) overnight but negative (positive) intraday. We provide a demand‐pressure‐based explanation for this phenomenon, identifying retail investors' gambling motives as the primary catalyst, which are particularly salient following negative realizations of underlying returns. Additionally, insurance‐driven demand accounts for the negative overnight put returns, while attention‐driven demand contributes to the night‐day asymmetry in call returns. Despite institutional investors exploiting these mispricings, the asymmetries persist over time, leaving retail investors to bear losses as counterparties.\n"]

  March 09, 2026   doi: 10.1002/fut.70095   open full text
• On the Comovement of Contango and Backwardation Across Futures Commodity Markets.
  Angelo Luisi, Francesco Roccazzella, Athanasios Triantafyllou.
  Journal of Futures Markets. March 09, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nWe examine the time‐varying nature of the comovement of the slope of the futures curve in major agricultural, metals and energy commodity futures markets in a Global Vector Autoregressive model. We find significant comovement between the slopes, indicating the co‐existence of backwardation and contango in many seemingly unrelated commodity futures markets. The degree of comovement in commodity futures curves intensifies during periods of financial and macroeconomic turmoil and increased geopolitical risk. In contrast, our analysis shows that the gold futures market becomes more backwardated (contangoed) when the rest of the commodity futures markets become more contangoed (backwardated).\n"]

  March 09, 2026   doi: 10.1002/fut.70092   open full text
• Option Market Value‐Based Reaction and Anticipation of Corporate‐Related Decisions by the United States Supreme Court.
  Yehuda Davis, Suresh Govindaraj, Yi Liu, Kate Suslava.
  Journal of Futures Markets. March 09, 2026
  ["Journal of Futures Markets, EarlyView. ", "\nABSTRACT\nOur paper studies the option market reactions to judicial decisions in the United States Supreme Court (SCOTUS) relating to cases where at least one party involved is a public firm. Prior research finds the stock market is unable to anticipate SCOTUS's actions and registers a significant negative stock market reaction to the grant of certiorari (acceptance of a petition to review a lower court's decision) for respondents and, surprisingly, for petitioners as well. We show the negative price reaction for both petitioner and respondent firms is a consequence of increased uncertainty. We also provide evidence that on the day certiorari is granted, the option market anticipates the final decision by SCOTUS. We believe we are the first to study the ability of futures markets to predict SCOTUS decisions.\n"]

  March 09, 2026   doi: 10.1002/fut.70094   open full text
• Catastrophe Futures and Reinsurance Contracts: An Incomplete Markets Approach.
  Stylianos Perrakis, Ali Boloorforoosh.
  Journal of Futures Markets. October 20, 2017
  We present a theoretical methodology for the pricing of catastrophe (CAT) derivatives with event‐dependent and non‐convex payoffs given the price of a CAT indexed futures contract. We do not assume a fully diversifiable CAT event risk, nor do we assume knowledge of the martingale probability measure beyond the futures price. We derive tight bounds on the contract value and present trading strategies exploiting the mispricing whenever the bounds are violated. We estimate the bounds of the reinsurance contract with data from hurricane landings in Florida. Our method is also applicable when there is no futures market but the price of a CAT‐indexed bond is available.

  October 20, 2017   doi: 10.1002/fut.21880   open full text
• The weather premium in the U.S. corn market.
  Ziran Li, Dermot J. Hayes, Keri L. Jacobs.
  Journal of Futures Markets. October 06, 2017
  We show that the weather premium, an anecdotal phenomenon in the U.S. corn futures market, can arise from a convex demand function. We further show that the magnitude of the weather premium depends on the carryout and expected yield at harvest. We use data from 1968 to 2015 to evaluate the accuracy of the December futures price as a forecast of the harvest price. A predictable component in the forecast error is consistent with the existence of a time‐varying weather premium. We demonstrate that a passive strategy of routinely shorting the corn December futures does not provide an attractive risk‐adjusted return.

  October 06, 2017   doi: 10.1002/fut.21884   open full text
• A comprehensive look at the return predictability of variance risk premia.
  Suk Joon Byun, Bart Frijns, Tai‐Yong Roh.
  Journal of Futures Markets. October 05, 2017
  The discrepancy between in‐sample and out‐of‐sample predictability of common predictors for asset returns has been widely discussed in the literature. We examine the out‐of‐sample predictability and its economic significance of Variance risk premium (VRP), which recently has shown empirical success in predicting asset returns in‐sample. Extensive analysis indicates strong out‐of‐sample predictability of the VRP for U.S. stock index, currencies, credit index, and equity portfolios. However, we do not find any evidence for predictability of bond and commodity markets. We demonstrate economic significance by providing profitable market timing strategies exploiting the out‐of‐sample forecasting power of the VRP in a real time setting.

  October 05, 2017   doi: 10.1002/fut.21882   open full text
• Forecasting using alternative measures of model‐free option‐implied volatility.
  Xingzhi Yao, Marwan Izzeldin.
  Journal of Futures Markets. October 02, 2017
  This paper evaluates the performance of various measures of model‐free implied volatility in predicting returns and realized volatility. The critical role of the out‐of‐the money call options is highlighted through an investigation of the relevance of different components of the model‐free implied volatility. The Monte Carlo simulations show that: first, volatility forecasting performance of various measures can be enhanced by employing an interpolation‐extrapolation technique; second, for most measures considered, gains in their predictive power for future returns can be obtained by implementing an interpolation procedure. An empirical application using SPX options recorded from 2003 to 2013 further illustrates these claims.

  October 02, 2017   doi: 10.1002/fut.21881   open full text
• Structural breaks and volatility forecasting in the copper futures market.
  Xu Gong, Boqiang Lin.
  Journal of Futures Markets. October 02, 2017
  This paper examines whether structural breaks contain incremental information for forecasting the volatility of copper futures. Considering structural breaks in volatility, we develop four heterogeneous autoregressive (HAR) models based on classical or latest HAR‐type models. Subsequently, we apply these models to forecast volatility in the copper futures market. The empirical results reveal that our models exhibit better in‐sample and out‐of‐sample performances than classical or latest HAR‐type models. This suggests that structural breaks contain incremental prediction information for the volatility of copper futures. More importantly, we argue that considering structural breaks can improve the performances of most of existing HAR‐type models. Highlights There are many structural break points in return volatility of the copper futures. We propose 12 new heterogeneous autoregressive models. Our models outperform the existing heterogeneous autoregressive models. Structural breaks contain additional ex ante information for volatility forecasting. The ex ante information is obvious in forecasting mid‐ and long‐term volatilities.

  October 02, 2017   doi: 10.1002/fut.21867   open full text
• Economic significance of commodity return forecasts from the fractionally cointegrated VAR model.
  Sepideh Dolatabadi, Paresh Kumar Narayan, Morten Ørregaard Nielsen, Ke Xu.
  Journal of Futures Markets. September 18, 2017
  We model and forecast commodity spot and futures prices using fractionally cointegrated vector autoregressive (FCVAR) models generalizing the well‐known (non‐fractional) CVAR model to accommodate fractional integration. In our empirical analysis to daily data on 17 commodity markets, the fractional model is statistically superior in terms of in‐sample fit and out‐of‐sample forecasting. We analyze economic significance of the forecasts through dynamic (mean‐variance) trading strategies, leading to statistically significant and economically meaningful profits in most markets. We generally find that the fractional model generates higher profits on average, especially in the futures markets.

  September 18, 2017   doi: 10.1002/fut.21866   open full text
• Options‐based benchmark indices—A review of performance and (in)appropriate measures.
  Markus Natter.
  Journal of Futures Markets. August 18, 2017
  This paper reviews the performance and profitability of different option strategy benchmark indices provided by the CBOE. Using different performance approaches, I show that performance measurement of these indices is highly complex and sensitive to the model choice. Moreover, this study controls for time‐varying delta exposure via linear timing approaches and uses a linear option‐factor model that is independent from the portfolio composition. Splitting the sample, I find that outperformance reported by previous studies is mostly driven by limited data. Moreover, the profitability of option strategies for private investors is evaluated based on easily investable investment products.

  August 18, 2017   doi: 10.1002/fut.21865   open full text
• Do investors use options and futures to trade on different types of information? Evidence from an aggregate stock index.
  Kyoung‐Hun Bae, Peter Dixon.
  Journal of Futures Markets. August 14, 2017
  Option prices are sensitive to changes in volatility whereas futures prices are not. We investigate this distinction empirically and test the hypothesis that investors with information about future returns (volatilities) will prefer to trade in futures (options) because futures (options) protect the investor from the risk that their bet will go against them due to unforeseen changes in volatility (returns). Consistent with this hypothesis we find that order imbalances between institutional and retail investors in Korean KOSPI 200 index futures (options) robustly predict short‐term returns (volatilities) on the KOSPI 200 index whereas options (futures) imbalances do not.

  August 14, 2017   doi: 10.1002/fut.21863   open full text
• Oil and stock markets before and after financial crises: A local Gaussian correlation approach.
  Georgios Bampinas, Theodore Panagiotidis.
  Journal of Futures Markets. July 14, 2017
  The effect of financial shocks on the cross‐market linkages between oil prices (spot and futures) and stock markets is examined for four major crises. We employ the local Gaussian correlation approach and find that the two markets were regionalized for most of the 1990s and the early 2000s. Flights from stocks to oil occur in all crisis episodes, except the recent global financial crisis. The view that stock and oil markets behave like “a market of one” after the financialization of commodities is further supported by the presence of contagion between US stock markets and all the benchmark oil markets.

  July 14, 2017   doi: 10.1002/fut.21860   open full text
• Time is money: An empirical investigation of delivery behavior in the U.S. T‐Bond futures market.
  Michèle Breton, Ramzi Ben‐Abdallah.
  Journal of Futures Markets. July 11, 2017
  This paper analyzes the delivery behavior observed in the CBOT T‐Bond futures market over the period spanning 1985–2016 in order to assess how timing decisions were made, and whether these decisions were optimal. During that period, delivery was generally deferred to the last possible moment, but early delivery episodes were also observed regularly. A regression model identifying the determinants of early exercise over the last three decades is proposed, along with a case‐by‐case analysis of specific delivery patterns. Finally, the optimality of the observed delivery strategies is assessed a posteriori.

  July 11, 2017   doi: 10.1002/fut.21862   open full text
• Do trend following strategies work in Chinese futures markets?
  Bin Li, Di Zhang, Yang Zhou.
  Journal of Futures Markets. June 30, 2017
  We examine the performance of trend following strategies in Chinese commodity futures markets. We provide evidence that trend following‐based technical trading rules yield better performance than the buy and hold strategy on both individual contracts and sorted portfolios. The outperformance is robust to transaction costs, data frequency, sub‐prime crisis, shorting constraint, delayed execution, liquidity and parameters. Finally, the profitability of the trend following strategy may be subject to data snooping bias.

  June 30, 2017   doi: 10.1002/fut.21856   open full text
• Need for speed: Hard information processing in a high‐frequency world.
  S. Sarah Zhang.
  Journal of Futures Markets. June 23, 2017
  I study the role of high‐frequency traders (HFTs) and non‐high‐frequency traders (nHFTs) in transmitting hard price information from the futures market to the stock market using an index arbitrage strategy. Using intraday transaction data with HFT identification, I find that HFTs process hard information faster and trade on it more aggressively than nHFTs. In terms of liquidity supply, HFTs are better at avoiding adverse selection than nHFTs. Consequently, HFTs enhance the linkage between the futures and stock markets, and significantly contribute to information efficiency in the stock market by reducing the delay between the stock and the futures markets.

  June 23, 2017   doi: 10.1002/fut.21861   open full text
• The joint credit risk of UK global‐systemically important banks.
  Mario Cerrato, John Crosby, Minjoo Kim, Yang Zhao.
  Journal of Futures Markets. June 14, 2017
  We study the joint credit risk in the UK banking sector using the weekly CDS spreads of global systemically important banks over 2007–2015. We show that the time‐varying and asymmetric dependence structure of the CDS spread changes is closely related to the joint default probability that two or more banks simultaneously default. We are able to flexibly measure the joint credit risk at the high‐frequency level by applying the combination of the reduced‐form model and the GAS‐based dynamic asymmetric copula model to the CDS spreads. We also verify that much of the dependence structure of the CDS spread changes are driven by the market factors. Overall, our study demonstrates that the market factors are key inputs for the effective management of the systemic credit risk in the banking sector.

  June 14, 2017   doi: 10.1002/fut.21855   open full text
• Do futures prices help forecast the spot price?
  Xin Jin.
  Journal of Futures Markets. June 05, 2017
  This study proposes a futures‐based unobserved components model for commodity spot prices. Prices quoted at the same time incorporate the same information, but are affected differently, resulting in the different shapes of futures curves. This model utilizes information from part of the futures curve to improve forecasting accuracy of the spot price. Applying this model to oil market data, I find that the model forecasts outperform the literature benchmark (the no‐change forecast) and futures prices forecasts in multiple dimensions, with smaller average error variation over the sample period and higher chance of smaller absolute error in each period.

  June 05, 2017   doi: 10.1002/fut.21854   open full text
• Density forecast comparisons for stock prices, obtained from high‐frequency returns and daily option prices.
  Rui Fan, Stephen J. Taylor, Matteo Sandri.
  Journal of Futures Markets. June 05, 2017
  This paper presents the first comparison of the accuracy of density forecasts for stock prices. Six sets of forecasts are evaluated for DJIA stocks, across four forecast horizons. Two forecasts are risk‐neutral densities implied by the Black–Scholes and Heston models. The third set are historical lognormal densities with dispersion determined by forecasts of realized variances obtained from 5‐min returns. Three further sets are defined by transforming risk‐neutral and historical densities into real‐world densities. The most accurate method applies the risk transformation to the Black–Scholes densities. This method outperforms all others for 87% of the comparisons made using the likelihood criterion.

  June 05, 2017   doi: 10.1002/fut.21859   open full text
• Index futures trading and spot volatility in China: A semiparametric approach with range‐based proxies.
  Na Tan, Yulei Peng, Yanchu Liu, Zhewen Pan.
  Journal of Futures Markets. May 19, 2017
  We relax the linear conditional mean assumption in Hsiao et al. (2012). Journal of Applied Econometrics, 27(5), 705–740 and extend it to a single‐index semi‐parametric setting. The asymptotic distribution properties are derived and the semi‐parametric model is applied to study the treatment effect of introducing the stock index futures contracts in China. Our empirical results indicate that the introduction of stock index futures significantly reduced stock market volatility before October 2014, but the long‐run effect is not significant. This temporary stabilization effect is robust to different underlying spot indexes, to various proxies of volatility, and to placebo tests on the introduction date of stock index futures.

  May 19, 2017   doi: 10.1002/fut.21858   open full text
• An analysis on the intraday trading activity of VIX derivatives.
  Dian‐Xuan Kao, Wei‐Che Tsai, Yaw‐Huei Wang, Kuang‐Chieh Yen.
  Journal of Futures Markets. May 19, 2017
  We investigate the relation between trading activity in the VIX derivative markets and changes in the VIX index under a high‐frequency framework. We find a significant relation between the signed trading variables of VIX futures and the contemporaneous changes in the VIX index. In addition, the net signed trading variables of VIX futures are significant predictors of future changes in the VIX index. Our results provide support for the informational role of VIX futures and evidence that trading activity in VIX options is likely caused by temporary liquidity shocks rather than the likelihood of informed trading.

  May 19, 2017   doi: 10.1002/fut.21857   open full text
• The effects of investor attention on commodity futures markets.
  Liyan Han, Ziying Li, Libo Yin.
  Journal of Futures Markets. May 05, 2017
  This study utilizes the search volume for key terms on Google as a direct and timely proxy for investor attention in order to examine how attention impacts commodity futures prices, We provide significant evidence for attention's influence on 13 commodity futures and the interaction between attention and returns, even after controlling for important macroeconomic variables. We also examine the impact of investor attention on market efficiency. Results show that rising attention, on one hand, increases information efficiency and attenuates arbitrage opportunities, whereas, on the other hand, decreases market efficiency by facilitating herd behavior.

  May 05, 2017   doi: 10.1002/fut.21853   open full text
• Are single stock futures used as an alternative during a short‐selling ban?
  Bouchra Benzennou, Owain ap Gwilym, Gwion Williams.
  Journal of Futures Markets. April 28, 2017
  The response of the single stock futures (SSF) market to a short‐selling ban is investigated. The hypothesis is that traders use SSF as a substitute instrument for short‐selling. A significant increase in SSF trading activity is documented, accompanied by narrower spreads. SSF market volatility did not react during the ban, which suggests that the increased trading activity did not weaken SSF market quality. The quality of the underlying market during the ban period is also assessed, with the results suggesting that changes in SSF market activity had neither positive nor negative effects on the stocks’ liquidity, volatility, and volume.

  April 28, 2017   doi: 10.1002/fut.21849   open full text
• Forecasting the volatility of Nikkei 225 futures.
  Manabu Asai, Michael McAleer.
  Journal of Futures Markets. April 28, 2017
  This article proposes an indirect method for forecasting the volatility of futures returns, based on the relationship between futures and the underlying asset for the returns and time‐varying volatility. The paper considers the stochastic volatility model with asymmetry and long memory, using high frequency data of the underlying asset, for forecasting its volatility. The empirical results for Nikkei 225 futures indicate that the adjusted R2 supports the appropriateness of the indirect method, and that the new method based on stochastic volatility models with asymmetry and long memory outperforms the forecasting model based on the direct method using the pseudo long time series.

  April 28, 2017   doi: 10.1002/fut.21847   open full text
• The impact of crude oil inventory announcements on prices: Evidence from derivatives markets.
  Hong Miao, Sanjay Ramchander, Tianyang Wang, Jian Yang.
  Journal of Futures Markets. April 28, 2017
  This study examines the impact of weekly crude oil storage announcements on oil futures and options prices. We document evidence of a strong announcement day effect on both markets, and find prices to move in anticipation of the inventory surprise. Futures returns significantly decrease with positive surprises and increase with negative surprises. There is no evidence of an asymmetric impact on futures prices. Near‐the‐money options exhibit the greatest price sensitivity, and the magnitude of the price response of both futures and options declines with maturity. The results remain robust even after controlling for various macroeconomic and other storage‐related news variables.

  April 28, 2017   doi: 10.1002/fut.21850   open full text
• The dynamic correlations between the G7 economies and China: Evidence from both realized and implied volatilities.
  Xingguo Luo, Xuyuanda Qi.
  Journal of Futures Markets. April 28, 2017
  This paper investigates the dynamic correlations between the G7 economies and China by using the EGARCH/DCC models proposed by Engle and Figlewski (). We find that the correlations between the G7 economies can be captured by a one‐factor model when either the realized or implied volatilities are used. Although no significant correlations between China and the G7 countries are captured using realized volatilities, we find that the correlations increased during the 2008 financial crisis. Furthermore, we show that the one‐factor model is useful for hedging the volatility risks of individual countries.

  April 28, 2017   doi: 10.1002/fut.21851   open full text
• Informed Trading in the Options Market and Stock Return Predictability.
  JoongHo Han, Da‐Hea Kim, Suk‐Joon Byun.
  Journal of Futures Markets. March 06, 2017
  Previous research highlights the importance of two distinct types of informed trading in the options market: trading on the price direction of underlying stocks, and trading on their uncertainty. Surprisingly, however, the studies considering these in a unified framework are scant.This study attempts to fill the gap. We predict that when both directional andvolatility information could motivateoptions trading, the return predictability of options volume hinges onthe shape of the volatility smirk.Consistent with this prediction, we find thatthe negative relationship between options volume and future stock returns is concentrated in stocks exhibiting steep volatility smirks. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark 37:1053–1093, 2017

  March 06, 2017   doi: 10.1002/fut.21837   open full text
• VPIN, Jump Dynamics and Inventory Announcements in Energy Futures Markets.
  Johan Bjursell, George H. K. Wang, Hui Zheng.
  Journal of Futures Markets. March 02, 2017
  The Volume‐Synchronized Probability of Informed Trading (VPIN) metric is proposed by Easley et al. (2011, 2012) (Journal of Portfolio Management, 37:118–128; Review of Financial Studies, 25:1457–1493) as a real‐time measure of order flow toxicity in an electronic trading market. This study examines the performance of VPIN around inventory announcements and price jumps in crude oil and natural gas futures markets with a sample period from January 2009 to May 2015. We obtain several interesting results: (i) VPIN increases significantly around inventory announcements with price jumps as well as at jumps not associated with any scheduled announcements. (ii) VPIN does not peak prior to the events but shortly after. (iii) A minor variation of VPIN based on exponential smoothing significantly improves the early warning signal property of VPIN, and this estimate of toxicity returns faster to the pre‐event level. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark 37:542–577, 2017

  March 02, 2017   doi: 10.1002/fut.21839   open full text
• Macroeconomic Conditions and Credit Default Swap Spread Changes.
  Tong Suk Kim, Jae Won Park, Yuen Jung Park.
  Journal of Futures Markets. March 02, 2017
  This study investigates the importance of the business cycle in explaining credit default swap spread changes by utilizing ex ante proxies. It uses portfolio regression and finds the structural variables, including the business cycle, explain approximately 65% of the spread differences. Furthermore, the business cycle variable enhances explanatory power more during the pre‐ and post‐crisis periods than during the crisis period and shows greater improvement for investment‐grade than for non‐investment‐grade firms. These results suggest that macroeconomic conditions play a critical role when the underlying asset value is likely to have greater distance from the default barrier. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark 37:766–802, 2017

  March 02, 2017   doi: 10.1002/fut.21836   open full text
• A Multivariate Markov Regime‐Switching High‐Frequency‐Based Volatility Model for Optimal Futures Hedging.
  Yu‐Sheng Lai, Her‐Jiun Sheu, Hsiang‐Tai Lee.
  Journal of Futures Markets. March 02, 2017
  This study proposes a multivariate Markov regime‐switching high‐frequency‐based volatility (MRS‐HEAVY) model for modeling the covariance structure of spot and futures returns, and estimating the associated hedge ratios. S&P 500 equity index data are used in estimations, and the results reveal that the MRS‐HEAVY model has a shorter response time than that of the Markov regime‐switching GARCH model; this difference is more pronounced in the high‐volatility regime than in the low‐volatility regime. Out‐of‐sample hedging exercises illustrate that the MRS‐HEAVY exhibits superior hedging performance in terms of both variance reductions and utility gains; it is robust even when transaction costs are considered. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark 37:1124–1140, 2017

  March 02, 2017   doi: 10.1002/fut.21842   open full text
• Sugar with your Coffee? Fundamentals, Financials, and Softs Price Uncertainty.
  Genèvre Covindassamy, Michel A. Robe, Jonathan Wallen.
  Journal of Futures Markets. February 23, 2017
  We investigate empirically the main factors related to coffee and sugar (“softs”) price uncertainty. We link physical market fundamentals as well as financial variables to (i) market expectations of future price volatility and (ii) the extent to which these two commodities both co‐move with equities. The physical market fundamentals that matter include the state of inventories, weather, and disease outbreaks. Beyond these fundamental factors, our results highlight the crucial role of financial market sentiment in understanding cross market linkages and the magnitude of softs market uncertainty. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark 37:744–765, 2017

  February 23, 2017   doi: 10.1002/fut.21846   open full text
• Pricing Vulnerable Options with Jump Clustering.
  Yong Ma, Keshab Shrestha, Weidong Xu.
  Journal of Futures Markets. February 23, 2017
  This paper presents a valuation of vulnerable European options using a model with self‐exciting Hawkes processes that allow for clustered jumps rather than independent jumps. Many existing valuation models can be regarded as special cases of the model proposed here. Using numerical analyses, this study also performs sensitivity analyses and compares the results to those of existing models for European call options. The results show that jump clustering has a significant impact on the option value. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark

  February 23, 2017   doi: 10.1002/fut.21843   open full text
• The CDS‐Bond Basis Arbitrage and the Cross Section of Corporate Bond Returns.
  Gi H. Kim, Haitao Li, Weina Zhang.
  Journal of Futures Markets. February 23, 2017
  We provide a comprehensive empirical analysis on the implication of CDS‐Bond basis arbitrage for the pricing of corporate bonds. Basis arbitrageurs introduce new risks such as funding liquidity and counterparty risk into the corporate bond market, which was dominated by passive investors before the existence of credit default swap (CDS). We show that a basis factor, constructed as the return differential between LOW and HIGH quintile basis portfolios, is a superior empirical proxy that captures the new risks. In the cross section of investment grade bond returns, the basis factor carries an annual risk premium of about 3% in normal periods. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark 37:836–861, 2017

  February 23, 2017   doi: 10.1002/fut.21845   open full text
• Optionable Stocks and Mutual Fund Performance.
  Chune Young Chung, Doojin Ryu, Kainan Wang, Blerina Bela Zykaj.
  Journal of Futures Markets. February 23, 2017
  We examine whether stock‐level options information drives mutual fund performance. Our paper is motivated by existing studies indicating that options prices or implied volatilities predict stock returns. We find that stock‐implied volatility innovations forecast mutual fund performance. Specifically, mutual funds investing in fewer optionable stocks or optionable stocks with favorable information outperform other funds. In addition, mutual fund managers overall do not trade on past options information. However, well‐performing fund managers use that information to decrease their holdings in poorly performing stocks. Moreover, well‐performing mutual funds containing strong options information tend to increase their holdings in optionable stocks in subsequent periods. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark

  February 23, 2017   doi: 10.1002/fut.21844   open full text
• Option Introductions and the Skewness of Stock Returns.
  Benjamin M. Blau, Ryan J. Whitby.
  Journal of Futures Markets. February 15, 2017
  The decision to introduce options for stocks is made by exchanges with the intention of selecting stocks that will generate the most option trading activity. This study hypothesizes that exchanges will introduce options for stocks with positive skewness. The motivation for our tests is based on the idea that some investors have preferences for skewness and the payoff structure of options is conducive to these types of preferences. Results show that the likelihood of introducing options is increasing in the level of return skewness. We also find that stocks with the most pre‐introduction skewness generate the most post‐listing option volume. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark

  February 15, 2017   doi: 10.1002/fut.21840   open full text
• A Bivariate High‐Frequency‐Based Volatility Model for Optimal Futures Hedging.
  Yu‐Sheng Lai, Donald Lien.
  Journal of Futures Markets. February 15, 2017
  This study examines the usefulness of high‐frequency data for estimating hedge ratios for different hedging horizons. By jointly modeling the returns and conditional expectation of the covariation, the multivariate high‐frequency‐based volatility (HEAVY) model generates spot‐futures distributions over longer horizons. Using the data on international equity index futures, performance comparisons between HEAVY and generalized autoregressive conditional heteroskedasticity (GARCH) hedge ratios indicate that HEAVY hedge ratios perform more effectively than GARCH hedge ratios at shorter hedging horizons. This implies that the distinct properties of short‐time response and short‐run momentum effects revealed in the HEAVY model are vital for hedge ratio estimation. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark

  February 15, 2017   doi: 10.1002/fut.21841   open full text
• Anchoring and Probability Weighting in Option Prices.
  R. Jared DeLisle, Dean Diavatopoulos, Andy Fodor, Kevin Krieger.
  Journal of Futures Markets. February 02, 2017
  Cumulative prospect theory argues that the human decision‐making process tends to improperly weight unlikely events. Another behavioral phenomenon, anchoring bias, is the failure to update beliefs away from established anchor points. In this study, we find evidence that equity option market investors both anchor to prices and incorporate a probability weighting function similar to that proposed by cumulative prospect theory. The biases result in inefficient prices for put options when firms have relatively high or relatively low implied volatilities. This has implications for the cost of hedging long portfolios and long individual equity positions. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark 37:614–638, 2017

  February 02, 2017   doi: 10.1002/fut.21833   open full text
• Momentum in International Commodity Futures Markets.
  Jangkoo Kang, Kyung Yoon Kwon.
  Journal of Futures Markets. February 01, 2017
  This paper examines whether commodity futures momentum can predict business cycles in the US, China, UK, Japan, and India. Momentum as a risk factor may play a role as a state variable in the spirit of Liew and Vassalou (). We find significant and negative predictability of commodity futures momentum, although the basis factor of the commodity futures markets shows insignificant results. Moreover, we find that commodity futures momentum is an independent factor that cannot be fully explained by traditional risk factors, macroeconomic variables, or commodity sector momentum. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark 37:803–835, 2017

  February 01, 2017   doi: 10.1002/fut.21834   open full text
• Investors’ Heterogeneity in Beliefs, the VIX Futures Basis, and S&P 500 Index Futures Returns.
  Hsiu‐Chuan Lee, Tzu‐Hsiang Liao, Pao‐Ying Tung.
  Journal of Futures Markets. January 23, 2017
  This study analyzes the impact of the VIX futures basis on subsequent S&P 500 index futures returns using quantile regression. The results show that the impact varies with return distributions and that the effect is stronger under bad market conditions than under good market conditions. The evidence also shows that the VIX futures basis provides incremental information for the purpose of risk management. Overall, our evidence supports the conclusion that the VIX futures basis and investors’ heterogeneity in beliefs are important factors that affect S&P 500 index futures returns. © 2017 Wiley Periodicals, Inc. Jrl Fut Mark

  January 23, 2017   doi: 10.1002/fut.21838   open full text
• Investor Sentiment and Credit Default Swap Spreads During the Global Financial Crisis.
  Jeehye Lee, Sol Kim, Yuen Jung Park.
  Journal of Futures Markets. December 28, 2016
  This paper examines whether investor sentiment can predict credit default swap (CDS) spread changes. Among several proxies for investor sentiment, change in equity put–call ratio performs best in predicting variation in CDS spread changes in both firm‐ and portfolio‐level regressions; in particular, the explanatory power of this proxy is greater for non‐investment‐grade firms than for investment‐grade firms. More importantly, sentiment may be a critical factor in determining CDS spread changes during the global financial crisis and may best explain the differences in CDS spread in the group of firms whose leverage ratio and stock volatility are highest. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark

  December 28, 2016   doi: 10.1002/fut.21828   open full text
• An Empirical Analysis of the Dynamic Probability of Informed Institutional Trading: Evidence from the Taiwan Futures Exchange.
  Pei‐Shih Weng, Ming‐Hung Wu, Miao‐Ling Chen, Wei‐Che Tsai.
  Journal of Futures Markets. December 22, 2016
  Based upon a unique dataset of institutional transactions in the Taiwan index futures market, we analyze the informational role of institutional investors using the “dynamic probability of informed trading” (DPIN). Compared to “trading imbalances” (TIB) and the “volume‐synchronized probability of informed trading” (VPIN), we show that the DPIN of foreign institutional investors outperforms the alternative measures and provides more stable effects in measuring informed trading. Following the strategies highlighted by DPIN, foreign institutional investors also perform better than domestic institutional investors. Our results support the validity of DPIN and present that foreign institutional investors are more informed. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark

  December 22, 2016   doi: 10.1002/fut.21830   open full text
• Order Aggressiveness, Trading Patience, and Trader Types in a Limit Order Market.
  Junmao Chiu, Huimin Chung, George H. K. Wang.
  Journal of Futures Markets. December 21, 2016
  This study examines the order aggressiveness and trading patience of foreign institutional traders, futures proprietary firm traders, individual day and non‐day traders in the Taiwan index futures market. We consider order choice given a completely transparent limit order book. Our empirical results show that individual (foreign institutional) traders use a more aggressive (patient) order submission strategy than the other trader types. We find significant differences among trader types in the timing of order aggressiveness and trading patience over the intraday time period. Both top and rest‐of‐the‐order‐book activities affect traders’ order submission decisions. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:1094–1123, 2017

  December 21, 2016   doi: 10.1002/fut.21832   open full text
• The Zero Lower Bound and Economic Determinants of the Volatility Surface in the Interest Cap Markets.
  Myeong‐Hyeon Kim, Changki Kim, Injun Hwang.
  Journal of Futures Markets. December 19, 2016
  We address an important yet unanswered question: what would be the economic determinants of the implied volatility during the zero lower bound periods? To answer this question, we examine time variations of the cap market implied volatility and investigate economic determinants on slopes and curvatures of the implied volatility curves. We find that unexpected unemployment and inflation shocks play an important role in explaining implied volatility curves for different maturities. We associate negative jumps in the volatility dynamics (Jarrow, Li, & Zhao, 2007) with two unexpected macroeconomic shocks. Our results provide an important implication for practitioners who prepare future exit strategies. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:578–598, 2017

  December 19, 2016   doi: 10.1002/fut.21829   open full text
• Trading Activity and Rate of Convergence in Commodity Futures Markets.
  David Bosch, Elina Pradkhan.
  Journal of Futures Markets. December 14, 2016
  We analyze whether and how the trading activity of different trader types impacts the rate of convergence between spot and futures markets for a broad range of commodity futures markets over the 1999–2014 period. There is strong evidence that speculators (commodity index traders) increase (reduce) the rate of convergence between spot and futures markets. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark

  December 14, 2016   doi: 10.1002/fut.21831   open full text
• AVIX: An Improved VIX Based on Stochastic Interest Rates and an Adaptive Screening Mechanism.
  Zhenlong Zheng, Zhengyun Jiang, Rong Chen.
  Journal of Futures Markets. December 09, 2016
  An improved model‐free implied variation index (AVIX) is proposed in this article. The AVIX is developed under a generalized semi‐martingale process with stochastic interest rates. An adaptive option screening mechanism is proposed to accommodate different market conditions. The effect of dividend protection is also considered. An empirical study of the China 50 ETF option market suggests that the AVIX is a better barometer of aggregate implied variation and investor sentiment than the traditional VIX. It reacts to market changes more rapidly and more sensitively. The AVIX also contains more information about future volatility and provides a more efficient forecast of future realized volatility. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:374–410, 2017

  December 09, 2016   doi: 10.1002/fut.21824   open full text
• Expanding the Explanations for the Return–Volatility Relation.
  Bakhtear Talukdar, Robert T. Daigler, A. M. Parhizgari.
  Journal of Futures Markets. December 06, 2016
  We examine the return–volatility relation using three of the CBOE's recent indices. We employ more robust estimation techniques that account for the asymmetric relation between return and volatility. Our findings indicate that contributions of these indices to R2 are surprisingly large (7.45–35.54%) when the observations are divided into deciles groups. The results further indicate that behavioral theories explain the return–volatility relation better than the fundamental theories. We use daily and high frequency data. The results are consistent across all data, though the high frequency data seem to provide more support for the behavioral theories. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark

  December 06, 2016   doi: 10.1002/fut.21827   open full text
• Option Market Characteristics and Price Monotonicity Violations.
  Heejin Yang, Hyung‐Suk Choi, Doojin Ryu.
  Journal of Futures Markets. November 22, 2016
  This study reexamines whether option price monotonicity properties hold in a liquid market with little market friction and considers the validity of the monotonicity properties in light of option market characteristics. We confirm that option prices do not monotonically correlate with underlying spot prices and that call and put prices often increase or decrease together, indicating that the monotonicity properties are not consistent with the observed option price dynamics. The violations of monotonicity properties are associated with not only market microstructure effects, trade sizes, and option leverage but also other market characteristics such as trade direction, individual investor demand, foreign investor trading, and market volatility. Violation occurrences tend to be clustered, and their relationship with option market characteristics has not been affected by the recent market reform. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:473–498, 2017

  November 22, 2016   doi: 10.1002/fut.21826   open full text
• Option Pricing with the Realized GARCH Model: An Analytical Approximation Approach.
  Zhuo Huang, Tianyi Wang, Peter Reinhard Hansen.
  Journal of Futures Markets. November 18, 2016
  We derive a pricing formula for European options for the Realized GARCH framework based on an analytical approximation using an Edgeworth expansion for the density of cumulative return. Existing approximations in this context are based on a Gram–Charlier expansion while the proper Edgeworth expansion is more accurate. In relation to existing discrete‐time option pricing models with realized volatility, our model is log‐linear, non‐affine, with a flexible leverage effect. We conduct an extensive empirical analysis on S&P500 index options and the results show that our computationally fast formula outperforms competing methods in terms of pricing errors, both in‐sample and out‐of‐sample. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:328–358, 2017

  November 18, 2016   doi: 10.1002/fut.21821   open full text
• Index Futures Trading Restrictions and Spot Market Quality: Evidence from the Recent Chinese Stock Market Crash.
  Qian Han, Jufang Liang.
  Journal of Futures Markets. November 09, 2016
  Using a difference‐in‐difference approach, we find that restrictions placed on the CSI 300 and CSI 500 index futures trading during the recent Chinese stock market crisis deteriorated spot market quality, particularly the September trade restrictions. Our results can be explained by the sudden risk exposure faced by alpha‐strategy traders who stop trading spots after the index futures trading restrictions are introduced, thus worsening the spot market quality. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:411–428, 2017

  November 09, 2016   doi: 10.1002/fut.21825   open full text
• Pricing the CBOE VIX Futures with the Heston–Nandi GARCH Model.
  Tianyi Wang, Yiwen Shen, Yueting Jiang, Zhuo Huang.
  Journal of Futures Markets. November 09, 2016
  We propose a closed‐form pricing formula for the Chicago Board Options Exchange Volatility Index (CBOE VIX) futures based on the classic discrete‐time Heston–Nandi GARCH model. The parameters are estimated using several sets of data, including the S&P 500 returns, the CBOE VIX, VIX futures prices and combinations of these data sources. Based on the resulting empirical pricing performances, we recommend the use of both VIX and VIX futures prices for a joint estimation of model parameters. Such estimation method can effectively capture the variations of the market VIX and the VIX futures prices simultaneously for both in‐sample and out‐of‐sample analysis. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark

  November 09, 2016   doi: 10.1002/fut.21820   open full text
• Equity Option Implied Probability of Default and Equity Recovery Rate.
  Bo Young Chang, Greg Orosi.
  Journal of Futures Markets. November 09, 2016
  There is a close link between prices of equity options and the default probability of a firm. We show that in the presence of positive expected equity recovery, standard methods that assume zero equity recovery at default misestimate the option‐implied default probability. We introduce a simple method to detect stocks with positive expected equity recovery by examining option prices and propose a method to extract the default probability from option prices that allows for positive equity recovery. We demonstrate possible applications of our methodology with examples that include financial institutions in the United States during the 2007–09 subprime crisis. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:599–613, 2017

  November 09, 2016   doi: 10.1002/fut.21823   open full text
• Asymmetry in the Permanent Price Impact of Block Purchases and Sales: Theory and Empirical Evidence.
  Alex Frino, Vito Mollica, Maria Grazia Romano, Zeyang Zhou.
  Journal of Futures Markets. November 09, 2016
  Previous research has identified that the information effects of buyer‐initiated trades are greater than seller‐initiated trades. We develop a theoretical model that predicts block purchases are relatively more informed in bear markets and block sales are relatively more informed in bull markets. Using a sample of large trades executed in the E‐mini S&P 500 index futures and SPDR S&P 500 exchange traded fund, we find evidence consistent with our theoretical model. Our results are robust to volatility and macro‐economic news announcements categorized as bullish or bearish. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:359–373, 2017

  November 09, 2016   doi: 10.1002/fut.21822   open full text
• Derivatives Valuation Based on Arbitrage: The Trade is Crucial.
  Stephen Figlewski.
  Journal of Futures Markets. September 07, 2016
  Derivatives valuation has strong theoretical support because models are derived from the principle that arbitrage between the derivative and its underlying will eliminate riskless profits and drive the market price to the model value. “No‐arbitrage” is invoked routinely whenever a new pricing model is developed. But real world market prices are determined by trades, not by theories. In this talk, I discuss how different the arbitrage trade is for different markets and different models and I review articles from the literature that illustrate how limits to the arbitrage trade have affected the way derivatives theory gets into prices in practice. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:316–327, 2017

  September 07, 2016   doi: 10.1002/fut.21806   open full text
• Convenience Yields in Electricity Prices: Evidence from the Natural Gas Market.
  Nikolaos Milonas, Nikolaos Paratsiokas.
  Journal of Futures Markets. August 25, 2016
  This study develops a model in which changes in the electricity basis are directly related to changes in the fuel's storage level and the fuel's convenience yield. The model is tested with data from the US electricity and natural gas markets during the period 2004–2014. Empirical results show a negative relationship between the electricity basis and the fuel's convenience yield giving support to the argument that non‐storable commodities embody convenience yields. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:522–538, 2017

  August 25, 2016   doi: 10.1002/fut.21807   open full text
• The Valuation of Power Exchange Options with Counterparty Risk and Jump Risk.
  Xingchun Wang, Shiyu Song, Yongjin Wang.
  Journal of Futures Markets. August 21, 2016
  This study presents a pricing model for power exchange options, in which the possibility of default by the risky counterparty as well as the arrival of important business information are taken into consideration. The idiosyncratic and common jump components induced by the arrival of business information are subsumed into all asset price processes whose dynamics are correlated with each other. Employing the measure‐change technique, we obtain a pricing formula for the values of power exchange options with counterparty risk. At last, based on the derived formula, we numerically analyze the impacts of counterparty risk and jump risk on option prices. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:499–521, 2017

  August 21, 2016   doi: 10.1002/fut.21803   open full text
• Tail Wags Dog: Intraday Price Discovery in VIX Markets.
  Nicolas P.B. Bollen, Michael J. O'Neill, Robert E. Whaley.
  Journal of Futures Markets. August 19, 2016
  Beginning with VIX futures in 2004, followed by VIX options in 2006 and VIX ETPs in 2009, the daily open interest in volatility contracts is now in the tens of billions of dollars. Given this growth, it is important to develop a better understanding of price discovery and the supply/demand dynamics in each market. Some of the price relations are linked by arbitrage. Others are not. In particular, the relation between the VIX cash index and the VIX futures is not arbitraged, and we show that, where once VIX changes led VIX futures price changes, the VIX futures now leads. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:431–451, 2017

  August 19, 2016   doi: 10.1002/fut.21805   open full text
• Could the Extended Trading of CSI 300 Index Futures Facilitate Its Role of Price Discovery?
  Sungbin Sohn, Xiaofeng Zhang.
  Journal of Futures Markets. August 19, 2016
  This study examines the role of extended CSI 300 Index futures trading in price discovery. As a prerequisite for the facilitation of price discovery, we first confirm that extended trading is weak‐form efficient and driven by information. We find that the predictability of futures returns during extended trading on the index's overnight returns is strong and improving. More importantly, compared to the index, its futures price exhibits stronger price leadership, particularly in the early synchronous trading hours. Evidence suggests that extended trading facilitates price discovery at the opening and in the early trading hours of the stock market. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark

  August 19, 2016   doi: 10.1002/fut.21804   open full text
• Variance Risk Premiums of Commodity ETFs.
  Chyng Wen Tee, Christopher Ting.
  Journal of Futures Markets. August 08, 2016
  We propose a model‐independent method to account for the early exercise premiums in American options on non‐dividend paying stocks. We find that our estimates of early exercise premium are generally larger than the estimates by existing methods. Given the American options on the Exchange‐Traded Funds (ETFs) of gold, silver, natural gas, and crude oil, we find strong empirical evidence of variance risk premiums for these commodities, over a volatility term structure up to 18 months. Furthermore, we show that volatility indexes constructed by using existing methods tend to overestimate the risk‐neutral variance, and consequently the magnitude of variance risk premium. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:452–472, 2017

  August 08, 2016   doi: 10.1002/fut.21802   open full text
• The Skewness Implied in the Heston Model and Its Application.
  Jin E. Zhang, Fang Zhen, Xiaoxia Sun, Huimin Zhao.
  Journal of Futures Markets. August 06, 2016
  In this paper, we provide an exact formula for the skewness of stock returns implied in the Heston (1993) model by using a moment‐computing approach. We compute the moments of Itoˆ integrals by using Itoˆ's Lemma skillfully. The model's affine property allows us to obtain analytical formulas for cumulants. The formulas for the variance and the third cumulant are written as time‐weighted sums of expected instantaneous variance, which are neater and more intuitive than those obtained with the characteristic function approach. Our skewness formula is then applied in calibrating Heston's model by using the market data of the CBOE VIX and SKEW. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:211–237, 2017

  August 06, 2016   doi: 10.1002/fut.21801   open full text
• Volatility Smile and One‐Month Foreign Currency Volatility Forecasts.
  Alfred Huah‐Syn Wong, Richard A. Heaney.
  Journal of Futures Markets. August 06, 2016
  We find knowledge of the volatility smile implied from foreign exchange options improves foreign exchange volatility forecast accuracy. The literature shows curvature of the smile can be captured by risk‐neutral skewness and risk‐neutral kurtosis and we find inclusion of these variables in forecast models improves volatility forecast accuracy. Further, delta‐neutral hedged portfolio performance highlights the economic significance of incorporating knowledge of the smile in forecast models. Analysis is conducted using options with one month to maturity written on four exchange rate series, GBP/USD, EUR/USD, AUD/USD, and the USD/JPY from 2001 to 2006. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:286–312, 2017

  August 06, 2016   doi: 10.1002/fut.21799   open full text
• Correlation and Lead–Lag Relationships in a Hawkes Microstructure Model.
  José Da Fonseca, Riadh Zaatour.
  Journal of Futures Markets. July 26, 2016
  The aim of this paper is to develop a multi‐asset model based on the Hawkes process describing the evolution of assets at high frequency and to study the lead–lag relationship as well as the correlation between the assets within this framework. We compute several statistical quantities and the covariance matrix associated with the diffusive limit of the model so that the relation between the parameters driving the assets at high and low frequencies is explicit. We illustrate the results using several financial assets quoted in the Eurex market and show how the model captures the lead–lag relationship between them. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:260–285, 2017

  July 26, 2016   doi: 10.1002/fut.21800   open full text
• Does Option‐Implied Cross‐Sectional Return Dispersion Forecast Realized Cross‐Sectional Return Dispersion? Evidence From the G10 Currencies.
  Klaus Grobys, Jari‐Pekka Heinonen.
  Journal of Futures Markets. July 07, 2016
  This study employs option‐price data to back out the implied cross‐sectional return variance in the G10 currencies. It investigates the relation of implied cross‐sectional return dispersion in the currency market and subsequent realized cross‐sectional return dispersion. We find that implied cross‐sectional return variance, based on option‐price data with 1‐ and 3‐month maturity, outperforms past cross‐sectional return variance in forecasting future cross‐sectional return variance. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:3–22, 2017

  July 07, 2016   doi: 10.1002/fut.21798   open full text
• Net Buying Pressure and Option Informed Trading.
  Chao‐Chun Chen, Shih‐Hua Wang.
  Journal of Futures Markets. June 15, 2016
  To differentiate between the effects of volatility trading and direction trading on an option market, this study decomposes net buying pressure of options into volatility‐motivated demand and direction‐motivated demand and examines their information content accordingly. With the two proposed measures, we find that changes in implied volatility of TAIEX OTM put options are driven by both volatility trading and directional trading over the sample period before the onset of the 2011 U.S. debt‐ceiling crisis, though the volatility trading effect is less than the directional trading effect. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:238–259, 2017

  June 15, 2016   doi: 10.1002/fut.21797   open full text
• Do Scheduled Macroeconomic Announcements Influence Energy Price Jumps?
  Kam Fong Chan, Philip Gray.
  Journal of Futures Markets. June 03, 2016
  For six important energy futures markets, this study examines whether large price movements (i.e., jumps) are related to the arrival and information content of scheduled macroeconomic announcements. Since prior studies by Kilian and Vega [(2011) Review of Economics and Statistics, 93, 660–671] and Chatrath, Miao, and Ramchander [(2012) Journal of Futures Markets, 32, 536–559] find little evidence of an announcement‐price reaction in mean energy returns, we focus on jump dynamics as a possible conduit for macroeconomic announcements to influence the distribution of returns. We find little evidence of an increase in jump arrival rates coinciding with scheduled releases of economic data. Similarly, there is no compelling evidence that the magnitude and/or sign (“good” vs. “bad”) of the inherent announcement surprises influence the mean jump size. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:71–89, 2017

  June 03, 2016   doi: 10.1002/fut.21796   open full text
• Price Discovery on the International Soybean Futures Markets: A Threshold Co‐Integration Approach.
  Chao Li, Dermot J. Hayes.
  Journal of Futures Markets. June 03, 2016
  This paper investigates the lead‐lag relationships among soybean prices in United States, Brazilian, and Chinese futures markets. We focus on both long‐run price co‐movements and on short‐run price relationships. Various co‐integration methodologies and causality tests are applied to examine the changes in price relationships over time. The empirical results indicate the following: (a) the soybean futures market in the U.S. is still the most important and influential market, and the U.S. price, in the long‐term, leads price changes in Brazil and China; (b) in the short‐term, the overnight return of U.S. soybean futures and the daytime return of Chinese No. 1 soybean futures contemporaneously affect each other, but there is no significant causality between U.S. overnight return and the daytime return of Chinese No. 2 soybean futures; and, (c) a weak temporal seasonal causality between U.S. and Brazilian soybean futures price exists and more often than not Brazilian futures lead U.S. futures during the Brazilian growing season. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:52–70, 2017

  June 03, 2016   doi: 10.1002/fut.21794   open full text
• Cross‐Hedging Ambiguous Exchange Rate Risk.
  Kit Pong Wong.
  Journal of Futures Markets. June 02, 2016
  This paper examines the behavior of an exporting firm that sells its output to two foreign countries, only one of which has futures and options available for its currency. The firm possesses smooth ambiguity preferences and faces multiple sources of ambiguous exchange rate risk. We show that the separation theorem fails to hold in that the firm's production and export decisions depend on the firm's attitude toward ambiguity and on the incident to the underlying ambiguity. Given that the random spot exchange rates are first‐order independent with respect to each plausible subjective distribution, we derive necessary and sufficient conditions under which the full‐hedging theorem applies to the firm's cross‐hedging decisions. When these conditions are violated, we show that the firm includes options in its optimal hedge position. This paper as such offers a rationale for the hedging role of options under smooth ambiguity preferences and cross‐hedging of ambiguous exchange rate risk. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:132–147, 2017

  June 02, 2016   doi: 10.1002/fut.21793   open full text
• Option Pricing with Threshold Mean Reversion.
  Zeyu Chi, Fangyuan Dong, Hoi Ying Wong.
  Journal of Futures Markets. May 30, 2016
  Mean reversion and regime switching are well‐known features of commodity prices. Recent empirical research additionally documents the time variation of the mean reversion rate and volatility. This paper considers the option pricing framework for an underlying commodity price with mean reversion rate and volatility change according to a self‐exciting regime switching model. We offer empirical evidence for the proposed model and derive analytic pricing formulas for the European and barrier options. Numerical examples demonstrate the application and the ability of the proposed model in capturing volatility smile and regime‐switching in the mean reversion rate, simultaneously. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:107–131, 2017

  May 30, 2016   doi: 10.1002/fut.21795   open full text
• Monetary Policy and Stock Prices: Does the “Fed Put” Work When It Is Most Needed?
  Alexander Kurov, Chen Gu.
  Journal of Futures Markets. May 20, 2016
  Most studies of the effect of monetary policy on asset prices use the event study methodology with daily data. The resulting estimates suffer from bias due to omitted variables and endogeneity of policy decisions. We provide evidence that this bias becomes so large during the 2007–2008 financial crisis that it reverses the sign of the estimated stock market response to monetary news, leading to an erroneous conclusion that interest rate cuts are bad news for stocks. We also examine the stock market reaction to monetary policy during the zero lower bound period. The results show a significant bias in daily event study estimates of the stock market response to news about the future path of monetary policy. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1210–1230, 2016

  May 20, 2016   doi: 10.1002/fut.21790   open full text
• An International Comparison of Implied, Realized, and GARCH Volatility Forecasts.
  Apostolos Kourtis, Raphael N. Markellos, Lazaros Symeonidis.
  Journal of Futures Markets. May 20, 2016
  We compare the predictive ability and economic value of implied, realized, and GARCH volatility models for 13 equity indices from 10 countries. Model ranking is similar across countries, but varies with the forecast horizon. At the daily horizon, the Heterogeneous Autoregressive model offers the most accurate predictions, whereas an implied volatility model that corrects for the volatility risk premium is superior at the monthly horizon. Widely used GARCH models have inferior performance in almost all cases considered. All methods perform significantly worse over the 2008–09 crisis period. Finally, implied volatility offers significant improvements against historical methods for international portfolio diversification. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1164–1193, 2016

  May 20, 2016   doi: 10.1002/fut.21792   open full text
• Option Pricing Under Skewness and Kurtosis Using a Cornish–Fisher Expansion.
  Sofiane Aboura, Didier Maillard.
  Journal of Futures Markets. May 19, 2016
  This paper revisits the pricing of options, in a context of financial stress, when the underlying asset's returns displays skewness and excess kurtosis. For that purpose, we use a Cornish–Fisher transformation for valuing option contracts with an exact formula allowing for heavy‐tails. An application to the S&P 500 stock index option contracts is carried out during both stress (October 2008) and calm (May 2015) periods. It provides evidence about the capability of the Cornish–Fisher model to fairly price options during a period of stress without violating the skewness–kurtosis boundaries given its large domain of validity. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1194–1209, 2016

  May 19, 2016   doi: 10.1002/fut.21787   open full text
• Differences in the Prices of Vulnerable Options with Different Counterparties.
  Xingchun Wang.
  Journal of Futures Markets. May 19, 2016
  In this paper, a new pricing model is proposed to investigate the differences in the prices of vulnerable options with different counterparties. I start by specifying the dynamics of the market portfolio, and then break down the risk of the underlying asset and the assets of the counterparties into systematic and idiosyncratic risk, which allows me to distinguish the counterparties from these two kinds of risk. Finally, the derived pricing formulae are used to illustrate the differences between vulnerable option prices. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:148–163, 2017

  May 19, 2016   doi: 10.1002/fut.21789   open full text
• The Binomial CEV Model and the Greeks.
  Aricson Cruz, José Carlos Dias.
  Journal of Futures Markets. May 06, 2016
  This article compares alternative binomial approximation schemes for computing the option hedge ratios studied by Chung and Shackleton (2002), Chung, Hung, Lee, and Shih (2011), and Pelsser and Vorst (1994) under the lognormal assumption, but now considering the constant elasticity of variance (CEV) process proposed by Cox (1975) and using the continuous‐time analytical Greeks recently offered by Larguinho, Dias, and Braumann (2013) as the benchmarks. Among all the binomial models considered in this study, we conclude that an extended tree binomial CEV model with the smooth and monotonic convergence property is the most efficient method for computing Greeks under the CEV diffusion process because one can apply the two‐point extrapolation formula suggested by Chung et al. (2011). © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:90–104, 2017

  May 06, 2016   doi: 10.1002/fut.21791   open full text
• Trading the VIX Futures Roll and Volatility Premiums with VIX Options.
  David P. Simon.
  Journal of Futures Markets. May 06, 2016
  This study examines VIX option trading strategies based on the systematic tendencies of VIX futures from January 2007 through March 2014. The strategies involve buying VIX options to exploit the tendency of VIX futures to rise and fall when the VIX futures curve is in backwardation and in contango, respectively, as well as the tendency of VIX futures ex ante volatility premiums to spike and then revert to more typical levels. Subject to caveats about the often wide VIX option bid–ask spread quotes in the first few years of trading, the results demonstrate that these limited risk strategies are highly profitable. An important factor driving the results is that long VIX option strategies greatly benefit from a tendency of VIX option implied volatilities to rise with increases in the volatilities of underlying VIX futures contracts, as the latter move toward settlement and their volatilities converge to the typically higher volatility of the VIX. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:184–208, 2017

  May 06, 2016   doi: 10.1002/fut.21788   open full text
• VIX Exchange Traded Products: Price Discovery, Hedging, and Trading Strategy.
  Christoffer Bordonado, Peter Molnár, Sven R. Samdal.
  Journal of Futures Markets. May 06, 2016
  This paper investigates the most traded VIX exchange traded products (ETPs) with focus on their performance, price discovery, hedging ability, and trading strategy. The VIX ETPs track their benchmark indices well. They are therefore exposed to the same time‐decay (high negative expected returns) as these indices. This makes them unsuitable for buy‐and‐hold investments, but it gives rise to a highly profitable trading strategy. Despite being negatively correlated with the S&P 500, the ETPs perform poorly as a hedging tool; their inclusion in a portfolio based on S&P 500 will decrease the risk‐adjusted performance of the portfolio. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:164–183, 2017

  May 06, 2016   doi: 10.1002/fut.21786   open full text
• Price Discovery and Foreign Participation in Korea's Government Bond Futures and Cash Markets.
  Cyn‐Young Park, Rogelio Mercado, Jaehun Choi, Hosung Lim.
  Journal of Futures Markets. May 02, 2016
  This paper examines the impact of foreign participation in Korean Treasury Bond (KTB) futures and its role in price discovery, using daily transactions data from the over‐the‐counter market and from the Korea Exchange for the futures. Our analysis suggests that foreign trading in the KTB futures market leads the price discovery process for the underlying bonds. Empirical results show that foreigners’ daily net long positions in the futures market exert significant influence in KTB and KTB futures prices. We also find that it is the unexpected component of foreign investors’ net long futures positions that explains a significant share of the pricing effects. Our empirical results also suggest that information transmission between cash and futures markets has improved significantly in the crisis and post‐crisis period while local market participants have become better in extracting information content from market transactions. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 37:23–51, 2017

  May 02, 2016   doi: 10.1002/fut.21785   open full text
• Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models.
  Dimos S. Kambouroudis, David G. McMillan, Katerina Tsakou.
  Journal of Futures Markets. April 29, 2016
  We investigate the information content of implied volatility forecasts for stock index return volatility. Using different autoregressive models, we examine whether implied volatility forecasts contain information for future volatility beyond that in GARCH and realized volatility models. Results show implied volatility follows a predictable pattern and confirm the existence of a contemporaneous relationship between implied volatility and index returns. Individually, implied volatility performs worse than alternate forecasts, however, a model that combines an asymmetric GARCH model with implied and realized volatility through (asymmetric) ARMA models is preferred model for forecasting volatility. This evidence is further supported by consideration of value‐at‐risk. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1127–1163, 2016

  April 29, 2016   doi: 10.1002/fut.21783   open full text
• Convenience Yields and Risk Premiums in the EU‐ETS—Evidence from the Kyoto Commitment Period.
  Stefan Trück, Rafał Weron.
  Journal of Futures Markets. April 15, 2016
  We examine convenience yields and risk premiums in the EU‐wide CO2 emissions trading scheme (EU‐ETS) during the first Kyoto commitment period (2008–2012). We find that the market has changed from initial backwardation to contango with significantly negative convenience yields in futures contracts. We further examine the impact of interest rate levels in the Eurozone, the increasing level of surplus allowances and banking, as well as returns, variance, or skewness in the EU‐ETS spot market. Our findings suggest that the drop in risk‐free rates during and after the financial crisis has impacted on the deviation from the cost‐of‐carry relationship for emission allowances (EUA) futures contracts. Our results also illustrate a negative relationship between convenience yields and the increasing level of inventory during the first Kyoto commitment period, providing an explanation for the high negative convenience yields. Finally, we find that market participants are willing to pay an additional risk premium in the futures market for a hedge against increased volatility in EUA prices. Overall, our results contribute to the literature on the determinants and empirical properties of convenience yields and risk premiums for this relatively new class of assets. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:587–611, 2016

  April 15, 2016   doi: 10.1002/fut.21780   open full text
• Spillovers and Directional Predictability with a Cross‐Quantilogram Analysis: The Case of U.S. and Chinese Agricultural Futures.
  Huayun Jiang, Jen‐Je Su, Neda Todorova, Eduardo Roca.
  Journal of Futures Markets. March 14, 2016
  This paper examines the daily, overnight, intraday, and rolling return spillovers of four key agricultural commodities—soybeans, wheat, corn, and sugar, between the U.S. and Chinese futures markets via a newly developed quantile dependence measure called quantilogram. The results reveal significant bi‐directional dependence between the two markets across commodities which is greater in extreme quantiles and moderately stronger from the United States to China. These findings offer valuable insights into investors’ behavior, market integration, dissimilarity, and market efficiency in both countries. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1231–1255, 2016

  March 14, 2016   doi: 10.1002/fut.21779   open full text
• Empirical Properties, Information Flow, and Trading Strategies of China's Soybean Crush Spread.
  Qingfeng Wilson Liu, Hui He Sono.
  Journal of Futures Markets. March 14, 2016
  This study examines the empirical properties of soybean, soymeal, and soyoil futures prices at China's Dalian Commodity Exchange. We find that the three series are cointegrated, and that the cointegration relationship is characterized by significant seasonality and consistent time trends. Further, employing a new trivariate VAR‐GARCH model, we find evidence of one‐way information flow from the soymeal and soyoil markets to the soybean market, but bidirectional information flow and volatility spillover between the soymeal and soyoil markets. Trading simulations based on the mean‐reverting tendencies of the cointegration relationship and 5‐day averages of the commonly‐used spread both generate positive returns. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1057–1075, 2016

  March 14, 2016   doi: 10.1002/fut.21777   open full text
• Estimation of Market Information Shares: A Comparison.
  Donald Lien, Zijun Wang.
  Journal of Futures Markets. March 02, 2016
  This note investigates via Monte Carlo simulation the finite‐sample performance of two identification schemes that provide unique measures of Hasbrouck‐type information share in price discovery. The Lien and Shrestha (2009) method is based on factorization of the full correlation matrix and the Grammig and Peter (2013) method is based on different correlations of price innovations in the tails and in the center of the distributions. We find that the GP method performs poorly under the chosen data generation processes. The LS method provides at most marginal improvement over the method based upon the upper/lower bound midpoint of the Hasbrouck measure. The results, therefore, support the common practice of the midpoint approach. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1108–1124, 2016

  March 02, 2016   doi: 10.1002/fut.21781   open full text
• Currency Carry Trades: The Role of Macroeconomic News and Futures Market Speculation.
  Suk‐Joong Kim.
  Journal of Futures Markets. February 22, 2016
  This paper investigates carry trade opportunities in major currencies against the US dollar over the period January 2, 1999 to December 31, 2012. There is evidence of significant Australian dollar (AUD), Euro, and Japanese yen (JPY) carry trades during noncrisis periods. The AUD (JPY) was an investment (a funding) currency, and the Euro was both. However, cross currency carry trades were not present. For the AUD and JPY, carry trades were more likely with low volatility and volume. Macroeconomic news that appreciate (depreciate) the AUD (the JPY) also stimulated the AUD (the JPY) carry trades. However, there is no evidence of meaningful and consistent impact of macroeconomic news on the EUR carry trades. For weekly horizon investigations, net long futures positions in the AUD promoted carry trades in the AUD and JPY. However, net long positions in the JPY only managed to reduce JPY carry trade probability. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1076–1107, 2016

  February 22, 2016   doi: 10.1002/fut.21778   open full text
• Who Sets the Price of Gold? London or New York.
  Martin Hauptfleisch, Tālis J. Putniņš, Brian Lucey.
  Journal of Futures Markets. February 22, 2016
  We investigate which of the two main centers of gold trading—the London spot market and the New York futures market—plays a more important role in setting the price of gold. Using intraday data during a 17‐year period, we find that although both markets contribute to price discovery, the New York futures play a larger role on average. This is striking given the volume of gold traded in New York is less than a tenth of the London spot volume, and illustrates the importance of market structure on the process of price discovery. We find considerable variation in price discovery shares both intraday and across years. The variation is related to the structure and liquidity of the markets, daylight hours, and macroeconomic announcements that affect the price of gold. We find that a major upgrade in the New York trading platform reduces the relative amount of noise in New York futures prices, reduces the impact of daylight hours on the location of price discovery, but does not greatly increase the speed with which information is reflected in prices. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:564–586, 2016

  February 22, 2016   doi: 10.1002/fut.21775   open full text
• Components of the Bid–Ask Spread and Variance: A Unified Approach.
  Björn Hagströmer, Richard Henricsson, Lars L. Nordén.
  Journal of Futures Markets. February 15, 2016
  We develop a structural model for the price formation and liquidity supply of an asset. Our model facilitates decompositions of both the bid–ask spread and the return variance into components related to adverse selection, inventory, and order processing costs. Furthermore, the model shows how the fragmentation of trading volume across trading venues influences inventory pressure and price discovery. We use the model to analyze intraday price formation for gold futures traded at the Shanghai Futures Exchange. We find that order processing costs explain about 50% of the futures bid–ask spread, whereas the remaining 50% is equally due to asymmetric information and to inventory costs. About a third of the variance in futures returns is attributable to microstructure noise. Trading at the spot market has a significant influence on futures price discovery, but only a limited impact on the futures bid–ask spread. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:545–563, 2016

  February 15, 2016   doi: 10.1002/fut.21776   open full text
• Are Hedgers Informed? An Examination of the Price Impact of Large Trades in Illiquid Agricultural Futures Markets.
  Alex Frino, Andrew Lepone, Vito Mollica, Shunquan Zhang.
  Journal of Futures Markets. February 15, 2016
  The “received” view in the finance literature is that hedgers are uninformed traders who use futures to fix future price movements and prevent losses from unexpected and unknown fluctuations in the purchase or sale price of a commodity. In this paper, we examine transactions executed by large traders in a relatively illiquid deliverable agricultural (grain) futures market where most transactions are executed by hedgers. We provide evidence that the price impact of large buyer‐initiated transactions is permanent, consistent with the proposition that they are executed by traders perceived to be informed. We also provide evidence that the price impact of large buyer‐initiated trades is greatest around announcements related to the underlying commodity—corroborating our conclusion that they are executed by traders perceived to be informed. This evidence is contrary to the “received” view in the literature that hedgers are uninformed, and implies that large long hedgers in agricultural futures markets are informed. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:612–622, 2016

  February 15, 2016   doi: 10.1002/fut.21774   open full text
• Is the Information on the Higher Moments of Underlying Returns Correctly Reflected in Option Prices?
  Jangkoo Kang, Soonhee Lee.
  Journal of Futures Markets. February 07, 2016
  This study examines the information implied in options with short and long maturities. In the analysis using the forward moments, we find that long‐term option investors, on average, seem to underestimate the third moment relative to short‐term option investors, and this becomes severe when the market variance is large. We find that the third moment underestimation of long‐term option investors is economically meaningful using Corrado and Su's model and a trading strategy exploiting the relative underestimated skewness in long‐term options. The abnormal return of the strategy is around 7% per year after controlling systematic risks. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:722–744, 2016

  February 07, 2016   doi: 10.1002/fut.21769   open full text
• Crude Oil and Agricultural Futures: An Analysis of Correlation Dynamics.
  Annastiina Silvennoinen, Susan Thorp.
  Journal of Futures Markets. February 04, 2016
  Correlations between oil and agricultural commodities have varied over previous decades, impacted by renewable fuels policy and turbulent economic conditions. We estimate smooth transition conditional correlation models for 12 agricultural commodities and WTI crude oil. While a structural change in correlations occurred concurrently with the introduction of biofuel policy, oil and food price levels are also key influences. High correlation between biofuel feedstocks and oil is more likely to occur when food and oil price levels are high. Correlation with oil returns is strong for biofuel feedstocks, unlike with other agricultural futures, suggesting limited contagion from energy to food markets. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:522–544, 2016

  February 04, 2016   doi: 10.1002/fut.21770   open full text
• Fat‐Finger Trade and Market Quality: The First Evidence From China.
  Ming Gao, Yu‐Jane Liu, Weili Wu.
  Journal of Futures Markets. February 04, 2016
  More trading is algorithmic or computer generated, and in markets where it is allowed, high frequency. However, what happens when there is an algorithmic trading error? This study attempts to answer that question by examining the August 16, 2013, fat‐finger trade in Chinese equity and equity futures markets. We find that both markets were excessively volatile, illiquid, and positively skewed. Moreover, we document that index returns are predictable for a short time, indicating that the fat‐finger event induced an inefficient market. Our results highlight the importance of market surveillance and regulation to lessen the damage of future fat‐finger events. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1014–1025, 2016

  February 04, 2016   doi: 10.1002/fut.21771   open full text
• An Analysis of the Risk‐Return Characteristics of Serially Correlated Managed Futures.
  Gert Elaut, Péter Erdős, John Sjödin.
  Journal of Futures Markets. February 04, 2016
  We investigate the implications of low but persistent serial correlation in Managed Futures' returns for portfolio management. Using a measure based on the unweighted sum of autocorrelations, we find that more positively autocorrelated Managed Futures exhibit distinctly different risk‐return profiles and outperform, on a risk‐adjusted basis, Managed Futures that exhibit lower degrees of serial correlation. The observed premium is unlikely to be explained by a concentration in certain strategies, fund size and age, attrition or delisting bias, and does not seem to hamper Managed Futures' portfolio benefits as a tail‐risk hedge. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:992–1013, 2016

  February 04, 2016   doi: 10.1002/fut.21773   open full text
• Asymmetric Effects of Volatility Risk on Stock Returns: Evidence from VIX and VIX Futures.
  Xi Fu, Matteo Sandri, Mark B. Shackleton.
  Journal of Futures Markets. February 04, 2016
  First, to separate different market conditions, this study focuses on how VIX spot (VIX), VIX futures (VXF), and their basis (VIX − VXF) perform different roles in asset pricing. Secondly, this study decomposes the VIX index into two parts: volatility calculated from out‐of‐the‐money call options and volatility calculated from out‐of‐the‐money put options. The analysis shows that out‐of‐the‐money put options capture more useful information in predicting future stock returns. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1029–1056, 2016

  February 04, 2016   doi: 10.1002/fut.21772   open full text
• CDS Inferred Stock Volatility.
  Biao Guo.
  Journal of Futures Markets. January 15, 2016
  Both CDS and out‐of‐money put option can protect investors against downside risk, so they are related while not being mutually replaceable. This study provides a straightforward linkage between corporate CDS and equity option by inferring stock volatility from CDS spread and, thus, enables a direct analogy with the implied volatility from option price. I find CDS inferred volatility (CIV) and option implied volatility (OIV) are complementary, both containing some information that is not captured by the other. CIV dominates OIV in forecasting stock future realized volatility. Moreover, a trading strategy based on the CIV–OIV mean reverting spreads generates significant risk‐adjusted return. These findings complement existing empirical evidence on cross‐market analysis. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:745–757, 2016

  January 15, 2016   doi: 10.1002/fut.21768   open full text
• Risk‐Free Rates and Variance Futures Prices.
  Leonidas S. Rompolis.
  Journal of Futures Markets. December 23, 2015
  This paper investigates the relation between risk‐free rates and ex‐ante market volatility. It derives a theoretical model implying a negative linear relation between risk‐free rates and variance futures prices. The latter are employed as a direct market‐based ex‐ante estimate of risk‐neutral volatility. Empirical analysis, conducted using LIBOR and variance futures prices written on the S&P 500 index, indicates that the predictions of the model are supported by the data. The paper also provides evidence that, first, this negative relation varies smoothly over time following business cycles, and, second, the variance risk premium is a significant component of this documented relation. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:943–967, 2016

  December 23, 2015   doi: 10.1002/fut.21767   open full text
• Estimation and Hedging Effectiveness of Time‐Varying Hedge Ratio: Nonparametric Approaches.
  Rui Fan, Haiqi Li, Sung Y. Park.
  Journal of Futures Markets. December 18, 2015
  Many studies have estimated the optimal time‐varying hedge ratio using futures, with most employing a bivariate generalized autoregressive conditional heteroscedasticity (BGARCH) model or a random coefficient model to estimate the time‐varying hedge ratio. However, it has been argued that when the variability of the estimated time‐varying hedge ratio is large, this ratio's hedging performance is not as good as that of the unconditional (constant) hedge ratio. This study proposes a nonparametric estimation approach to estimate and evaluate the optimal conditional hedge ratio. This method produces a time‐varying hedge ratio with less volatility than those obtained from the BGARCH and random coefficient models. We evaluate the hedging performance of the various models using soybean oil, corn, S&P 500, and Hang Seng futures indices. The empirical results support the proposed nonparametric approach in terms of both in‐sample and out‐of‐sample performance. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:968–991, 2016

  December 18, 2015   doi: 10.1002/fut.21766   open full text
• A Generalization of the Recursive Integration Method for the Analytic Valuation of American Options.
  Lung‐Fu Chang, Jia‐Hau Guo, Mao‐Wei Hung.
  Journal of Futures Markets. November 27, 2015
  This article provides a general accelerated recursive integration method for pricing American options based on stochastic volatility and double jump processes. Our proposed model is a generalization of the recursive integral representation method. American option prices can be evaluated by the sum of a corresponding European option price and an early exercise premium integral. Numerical results show that our proposed method is efficient and accuracy in pricing American options with stochastic volatility and double jump processes. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:887–901, 2016

  November 27, 2015   doi: 10.1002/fut.21765   open full text
• Futures Price Response to Crop Reports in Grain Markets.
  Fabio L. Mattos, Rodrigo L. F. Silveira.
  Journal of Futures Markets. November 20, 2015
  The purpose of this study is to investigate the impact of crop reports from U.S. and Brazil on corn and soybean futures markets over the period 2004–2014. A TARCH model with dummy variables to measure the impact of crop reports is used. Results indicate that U.S. reports consistently affect corn and soybean futures price volatility, while Brazilian crop reports' impact on volatility is of smaller magnitude. Further, these impacts are generally found to be stronger when crop reports are released in the months preceding the beginning of harvest. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:923–942, 2016

  November 20, 2015   doi: 10.1002/fut.21764   open full text
• Tests on the Monotonicity Properties of KOSPI 200 Options Prices.
  Myounghwa Sim, Doojin Ryu, Heejin Yang.
  Journal of Futures Markets. November 20, 2015
  This study demonstrates that the basic properties predicted by one‐dimensional diffusion option pricing models are often violated, even in a highly liquid and leading options market. We analyze a high‐quality intraday dataset of KOSPI 200 index options, one of the most actively traded options markets in the world, and find that option prices often do not monotonically correlate with underlying prices. We also empirically show that option prices often do not change, despite changes in underlying prices, when options are heavily traded by individual investors, who are normally noisy and uninformed. Our evidence is partially consistent with the implications of demand‐based option pricing models, which predict that investor demand can significantly influence option prices in the presence of limits to arbitrage. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:625–646, 2016

  November 20, 2015   doi: 10.1002/fut.21763   open full text
• On the Intraday Relation Between the VIX and its Futures.
  Bart Frijns, Alireza Tourani‐Rad, Robert I. Webb.
  Journal of Futures Markets. October 27, 2015
  We study the intraday dynamics of the VIX and VIX futures for the period January 2, 2008 to December 31, 2014. Considering first the results of a Vector Autoregression (VAR) using daily data, we observe that there is some evidence of causality from VIX futures to the VIX. Estimating a VAR using our ultra‐high frequency data, we find strong evidence for bi‐directional Granger causality between the VIX and the VIX futures. Overall, this effect appears to be stronger from VIX futures to the VIX than the other way around. Impulse response functions and variance decompositions confirm the dominance of the VIX futures. Lastly, we show that the causality from the VIX futures to the VIX has been increasing over our sample period, whereas the reverse causality has been decreasing. We observe that the VIX futures have become increasingly more important in the pricing of volatility. We further document that the VIX futures dominate the VIX more on days with negative returns, and on days with high values of the VIX, suggesting that those are the days when investors use VIX futures to hedge their positions rather than trading in the S&P500 index options. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:870–886, 2016

  October 27, 2015   doi: 10.1002/fut.21762   open full text
• Heston‐Type Stochastic Volatility with a Markov Switching Regime.
  Robert J. Elliott, Katsumasa Nishide, Carlton‐James U. Osakwe.
  Journal of Futures Markets. October 26, 2015
  We construct a Heston‐type stochastic volatility model with a Markov switching regime to price a plain‐vanilla stock option. A semi‐analytic solution, which contains a matrix ODE is obtained and numerically calculated. Our model is flexible enough to provide a wide variety of volatility surfaces for the same volatility level but different regimes. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:902–919, 2016

  October 26, 2015   doi: 10.1002/fut.21761   open full text
• Price Discovery in Thinly Traded Futures Markets: How Thin is Too Thin?
  Philipp Adämmer, Martin T. Bohl, Christian Gross.
  Journal of Futures Markets. October 21, 2015
  It is still an unanswered question how much trading activity is needed for efficient price discovery in commodity futures markets. For this purpose, we investigate the price discovery process of two thinly traded agricultural futures contracts traded at the European Exchange in Frankfurt. Our empirical results show that the trading volume threshold which is necessary to facilitate efficient price discovery is very low. As our findings are based on constant and time‐varying vector error correction models, we also show that neglecting time‐variation in the parameters can lead to misleading results. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:851–869, 2016

  October 21, 2015   doi: 10.1002/fut.21760   open full text
• Do Jumps Matter for Volatility Forecasting? Evidence from Energy Markets.
  Marcel Prokopczuk, Lazaros Symeonidis, Chardin Wese Simen.
  Journal of Futures Markets. October 21, 2015
  This paper characterizes the dynamics of jumps and analyzes their importance for volatility forecasting. Using high‐frequency data on four prominent energy markets, we perform a model‐free decomposition of realized variance into its continuous and discontinuous components. We find strong evidence of jumps in energy markets between 2007 and 2012. We then investigate the importance of jumps for volatility forecasting. To this end, we estimate and analyze the predictive ability of several Heterogenous Autoregressive (HAR) models that explicitly capture the dynamics of jumps. Conducting extensive in‐sample and out‐of‐sample analyses, we establish that explicitly modeling jumps does not significantly improve forecast accuracy. Our results are broadly consistent across our four energy markets, forecasting horizons, and loss functions. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:758–792, 2016

  October 21, 2015   doi: 10.1002/fut.21759   open full text
• Pricing American Put Options Using the Mean Value Theorem.
  Humphrey K.K. Tung.
  Journal of Futures Markets. October 19, 2015
  This paper proposes a unique framework for the determination of the exercise boundary of American put option utilizing the mean value theorem for integration. We have isolated the path‐dependent feature of the problem through a small term, and formulated an iteration procedure that avoids an explicit integration over the exercise boundary in the integral representation of the pricing. Our method outperforms other methods in the literature in terms of accuracy and efficiency for the pricing of American put options with maturity in the region of most practical uses. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:793–815, 2016

  October 19, 2015   doi: 10.1002/fut.21758   open full text
• Risk Analysis and Hedging of Parisian Options under a Jump‐Diffusion Model.
  Kyoung‐Kuk Kim, Dong‐Young Lim.
  Journal of Futures Markets. October 13, 2015
  A Parisian option is a variant of a barrier option such that its payment is activated or deactivated only if the underlying asset remains above or below a barrier over a certain amount of time. We show that its complex payoff feature can cause dynamic hedging to fail. As an alternative, we investigate a quasi‐static hedge of Parisian options under a more general jump‐diffusion process. Specifically, we propose a strategy of decomposing a Parisian option into the sum of other contingent claims which are statically hedged. Through numerical experiments, we show the effectiveness of the suggested hedging strategy. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:819–850, 2016

  October 13, 2015   doi: 10.1002/fut.21757   open full text
• To Squeeze or Not to Squeeze? That Is No Longer the Question.
  Ramzi Ben‐Abdallah, Michèle Breton.
  Journal of Futures Markets. September 28, 2015
  This paper provides an investigation into an anomaly called a short squeeze, in the CBOT T‐Bonds Futures Market, for the period spanning January 1985 to December 2014. A short squeeze occurs when market manipulations cause the cheapest‐to‐deliver bond to be in short supply, resulting in significant price distortions. The incentive for market manipulation, or squeeze potential, is evaluated over the last 30 years and is related to documented episodes of the CBOT futures market. It is observed that conditions are presently very favorable to the occurrence of short squeezes, and that shortages would imply large losses for short traders. We also find that the incentive for market manipulation would be significantly reduced by lowering the notional underlying security coupon rate. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:647–670, 2016

  September 28, 2015   doi: 10.1002/fut.21754   open full text
• The Prevalence, Sources, and Effects of Herding.
  Naomi E. Boyd, Bahattin Büyükşahin, Michael S. Haigh, Jeffrey H. Harris.
  Journal of Futures Markets. September 25, 2015
  We test the prevalence, sources and effects of herding among large speculative traders in thirty U.S. futures markets over 2004–2009. We find significant herding levels within the large trader category of managed money traders (hedge funds) who are known to have similar performance evaluation measures. Our results support for the notion that greater public information takes away incentives to herd. The number of traders and floor‐based markets are positively associated with herding, while trading volume and electronic trading are negatively related to herding. Notably, we find little evidence that herding by managed money traders serves to destabilize prices in futures markets. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:671–694, 2016

  September 25, 2015   doi: 10.1002/fut.21756   open full text
• Information Flow Between Forward and Spot Markets: Evidence From the Chinese Renminbi.
  Jiadong Tong, Zijun Wang, Jian Yang.
  Journal of Futures Markets. September 18, 2015
  We apply a new model selection approach that allows for the joint determination of structural breaks and cointegration to examine the term structure of Chinese Renminbi (RMB)‐U.S. dollar spot and forward exchange rates during the managed‐floating period of 2005–2013. We find that the RMB market has exhibited different dynamic relationships between spot and forward exchange rates over time, apparently due to significant policy changes. Offshore forward rates with either shorter or longer maturities can substantially explain the in‐sample variation of the onshore spot exchange rate at longer horizons, while only the offshore forward rate with a shorter maturity can significantly predict RMB onshore spot rate changes out‐of‐sample. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:695–718, 2016

  September 18, 2015   doi: 10.1002/fut.21753   open full text
• Do Momentum‐Based Trading Strategies Work in the Commodity Futures Markets?
  Paresh Kumar Narayan, Huson Ali Ahmed, Seema Narayan.
  Journal of Futures Markets. May 23, 2014
  This article examines whether momentum‐based trading strategies work in the commodity futures markets. Using a wide range of moving average trading rules, commodities are ranked from best‐ to worst‐performing. Then investors are allowed to take long positions in best‐performing commodities and a short position in the least attractive commodity. Findings suggest that investors can earn statistically significant profits from the commodity futures markets. Moreover, it is found that short‐selling improves commodity profits and profits are both data frequency and sub‐sample dependent. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  May 23, 2014   doi: 10.1002/fut.21685   open full text
• The Distribution of Uncertainty: Evidence from the VIX Options Market.
  Clemens Völkert.
  Journal of Futures Markets. May 15, 2014
  This article investigates the informational content implied in the risk‐neutral distribution of the VIX, a leading barometer of economic uncertainty. We extract the risk‐neutral distribution from VIX option prices over the sample period from 2006 to 2011 using a non‐parametric approach. We analyze the time‐series behavior of the option‐implied moments and assess whether the information implied in the risk‐neutral distribution has predictive power. The risk‐neutral distribution considerably changed shape during the financial crisis. Furthermore, risk‐neutral moments contain useful information with respect to the likelihood of upward jumps in volatility. Consistent with investors disliking high levels of economic uncertainty, we find that the overall shape of the estimated volatility pricing kernel is increasing. For certain periods, there is a puzzling U‐shape. The behavior of the volatility pricing kernel over time reveals that the financial crisis has affected investors’ attitudes towards risk. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  May 15, 2014   doi: 10.1002/fut.21673   open full text
• Valuing Retail Credit Tranches with Structural, Double Mixture Models.
  Taehan Bae, Ian Iscoe, Changki Kim.
  Journal of Futures Markets. May 13, 2014
  This study considers the class of double mixtures to model a general dependence structure beyond the typical conditional independence assumption among the entities in a homogeneous credit portfolio. The two mixing components are (i) the marginal distributions of the systemic and idiosyncratic factors and (ii) the conditional probability measure that incorporates the further dependence structure among the idiosyncratic factors, given the systemic factor. For a large portfolio, the fair spread of a structured retail credit tranche is expressed in terms of the sums of single integrals, which can be easily computed numerically. We discuss the behaviors of tranche spreads under several double mixture models, and calibrate these models to market data. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  May 13, 2014   doi: 10.1002/fut.21684   open full text
• Volatility Risk Premium in Indian Options Prices.
  Sonia Garg, Vipul.
  Journal of Futures Markets. May 13, 2014
  The article examines the volatility forecasting and option pricing performance of model‐free implied volatility (MFIV) in comparison to that of the forecasts based on model‐free realized volatility (RV). There is evidence that the forecasts based on RV are significantly more efficient and less biased than those based on MFIV, whereas the option prices based on MFIV are significantly more efficient and less biased than those based on RV. These contrasting results can be reconciled by accounting for the volatility risk premium (VRP), which is found to follow an autoregressive process in this study. The significant daily returns, observed for various option strategies used to exploit the VRP, are substantially reduced, when the normal transaction costs are accounted for. Although the VRP is priced in the Indian options market, it can provide economic benefits only to those option writers, who have sufficiently low transaction costs. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  May 13, 2014   doi: 10.1002/fut.21680   open full text
• Ambiguity and the Value of Hedging.
  Kit Pong Wong.
  Journal of Futures Markets. April 23, 2014
  This paper examines the optimal production and hedging decisions of the competitive firm under price uncertainty when the firm's preferences exhibit smooth ambiguity aversion and an unbiased forward hedging opportunity is available. Ambiguity is modeled by a second‐order probability distribution that captures the firm's uncertainty about which of the subjective beliefs govern the price risk. Ambiguity preferences are modeled by the (second‐order) expectation of a concave transformation of the (first‐order) expected utility of profit conditional on each plausible subjective distribution of the price risk. Within this framework, the separation and full‐hedging theorems remain intact. Banning the firm from trading its output forward at the unbiased forward price has adverse effect on the firm's production decision. The firm finds the unbiased forward hedging opportunity more valuable in the presence than in the absence of ambiguity. Furthermore, the value of hedging increases when the firm's beliefs are more ambiguous, or when the firm becomes more ambiguity averse. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  April 23, 2014   doi: 10.1002/fut.21678   open full text
• Hoarding the Herd: The Convenience of Productive Stocks.
  Frank Asche, Atle Oglend, Dengjun Zhang.
  Journal of Futures Markets. April 22, 2014
  This paper investigates the convenience yield that emerges in markets with productive stocks. We isolate the economic fundamentals giving rise to the yield, and show how these map to the empirical convenience yield measure. A model for price dynamics is derived from an economic model for optimal stock levels. We show how the price process reduces to a simple non‐linear first‐order Markov process. The model is estimated for the Norwegian market for farmed salmon by Generalized Methods of Moments, where stock growth is approximated by sea‐water temperature. Our estimation result supports the theorized role of stock growth as a convenience yield component. Our results are relevant for the functioning of futures markets for commodities such as fish and other animal production where systematic stock growth affects the term structure. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  April 22, 2014   doi: 10.1002/fut.21679   open full text
• Clustering and Mean Reversion in a Hawkes Microstructure Model.
  José Da Fonseca, Riadh Zaatour.
  Journal of Futures Markets. April 22, 2014
  This paper provides explicit formulas for the first and second moments and the autocorrelation function of the number of jumps over a given interval for the multivariate Hawkes process. These computations are possible thanks to the affine property of this process. We unify the stock price models of Bacry et al. (2013a, Quantitative Finance, 13, 65–77) and Da Fonseca and Zaatour (forthcoming, Journal of Futures Markets) both of them based on the Hawkes process, the first one having a mean reverting behavior while the second one a clustering behavior, and build a model having these two properties. We compute various statistics as well as the diffusive limit for the stock price that determines the connection between the parameters driving the high‐frequency activity to the daily volatility. Lastly, the impulse function giving the impact on the stock price of a buy/sell trade is explicitly computed. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  April 22, 2014   doi: 10.1002/fut.21676   open full text
• Causes and Implications of Shifts in Financial Participation in Commodity Markets.
  Bassam Fattouh, Lavan Mahadeva.
  Journal of Futures Markets. April 22, 2014
  We assess the causes and implications of the greater financial participation in commodity markets post‐2003. Focusing on crude oil, we build a calibrated macro‐finance model of oil prices and quantities that also determines consumer welfare. We show that shifts in the preferences and constraints of financial speculators cannot explain the observed movement in the futures spread and so are unlikely to expose consumer welfare to shocks, even in the presence of belief disagreements. Shifts in the supply and demand for spot oil can better explain many of the features often attributed to financialization including financial participation itself. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  April 22, 2014   doi: 10.1002/fut.21674   open full text
• Derivatives Pricing on Integrated Diffusion Processes: A General Perturbation Approach.
  Minqiang Li.
  Journal of Futures Markets. April 16, 2014
  Many derivatives products are directly or indirectly associated with integrated diffusion processes. We develop a general perturbation method to price those derivatives. We show that for any positive diffusion process, the hitting time of its integrated process is approximately normally distributed when the diffusion coefficient is small. This result of approximate normality enables us to reduce many derivative pricing problems to simple expectations. We illustrate the generality and accuracy of this probabilistic approach with several examples in the Heston model. Major advantages of the proposed technique include extremely fast computational speed, ease of implementation, and analytic tractability. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  April 16, 2014   doi: 10.1002/fut.21677   open full text
• Dislocations in the Currency Swap and Interest Rate Swap Markets: The Case of Korea.
  Hail Park.
  Journal of Futures Markets. April 08, 2014
  This article empirically investigates the determinants of the deviations from fundamental levels of both the currency swap (CRS) and the interest rate swap (IRS) rates in Korea. This study also analyses the inter‐linkages between the swap and bond markets in Korea. To this end, a rolling VAR model is estimated incorporating the CRS rate, the IRS rate and the Korean Treasury bond (KTB) rate. It is found that hedging activities and risk factors are significant determinants of the deviations from fundamental levels of the IRS as well as the CRS rate in Korea. Moreover, the covered interest parity (CIP) deviation in the CRS market plays a role in explaining the deviation from the fundamental level of the IRS rate. There are contemporaneous links among the CRS rate, the IRS rate and the KTB rate, and a CRS rate shock significantly affects both the IRS and the KTB rates. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  April 08, 2014   doi: 10.1002/fut.21675   open full text
• The Impacts of Individual Day Trading Strategies on Market Liquidity and Volatility: Evidence from the Taiwan Index Futures Market.
  Robin K. Chou, George H. K. Wang, Yun‐Yi Wang.
  Journal of Futures Markets. April 06, 2014
  We investigate the investment strategies of individual day traders in the Taiwan Index Futures market, along with their impact on market liquidity and volatility. Our results indicate a tendency among most individual day traders to behave as irrational contrarian traders. We also present consistent evidence to show that most individual day traders provide market liquidity by reducing the bid‐ask spread, temporary price volatility, and the temporal price impacts. Our results, which are consistent with the experimental results of Bloomfield, O'Hara, and Saar (2009) [Review of Financial Studies, 22:2275–2302], provide no support for the general criticism that day trading destabilizes the market while also exacerbating market volatility. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  April 06, 2014   doi: 10.1002/fut.21665   open full text
• Commonality in Liquidity Across International Borders: Evidence from Futures Markets.
  Alex Frino, Vito Mollica, Zeyang Zhou.
  Journal of Futures Markets. April 03, 2014
  This study examines commonality in liquidity for stock index futures markets. We report strong evidence of commonality in global liquidity for nine index futures contracts over a 10‐year time period extending October 2002 to September 2012. Our results are robust to expiry effects and tests for liquidity commonality based on a market model and principal component method. We investigate the variation in global liquidity commonality through time and document that liquidity commonality is higher in significance and more pervasive in recent years. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  April 03, 2014   doi: 10.1002/fut.21663   open full text
• Hedging Industrial Metals With Stochastic Volatility Models.
  Qingfu Liu, Michael T. Chng, Dongxia Xu.
  Journal of Futures Markets. April 03, 2014
  The financialization of commodities documented in [Tang and Xiong (2012) Financial Analyst Journal, 68:54–74] has led commodity prices to exhibit not only time‐varying volatility, but also price and volatility jumps. Using the class of stochastic volatility (SV) models, we incorporate such extreme price movements to generate out‐of‐sample hedge ratios. In‐sample estimation on China's copper (CU) and aluminum (AL) spot and futures markets confirms the presence of price jumps and price‐volatility jump correlations. Out‐of‐sample hedge ratios from the [Bates (1996) Review of Financial Studies, 9:69–107] SV with price jumps model deliver the greatest risk reduction on the unhedged positions at 59.55% for CU and 49.85% for AL. But it is the [Duffie, Pan, and Singleton (2000) Econometrica, 68:1343–1376] SV model with correlated price and volatility jumps that produces hedge ratios which yield the largest Sharpe Ratios of 0.644 for CU and 0.886 for AL. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  April 03, 2014   doi: 10.1002/fut.21671   open full text
• Implied Risk Neutral Densities From Option Prices: Hypergeometric, Spline, Lognormal, and Edgeworth Functions.
  André Santos, João Guerra.
  Journal of Futures Markets. April 01, 2014
  This work examines the performance of four different methods to estimate the “true” Risk‐Neutral Density functions (RNDs) using European options. These methods are the Mixture of Lognormal distributions (MLN), the Smoothed Implied Volatility Smile (SML), the Density Functional Based on the Confluent Hypergeometric function (DFCH), and the Edgeworth expansions (EE). The “true” RND is unknown, so it was generated using the stochastic Heston model and considering parameters that reflect the characteristics of the options market for the US dollar and Brazilian real exchange rate (USD/BRL). We find that the DFCH and MLN have the best performance in capturing the “true” RNDs. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  April 01, 2014   doi: 10.1002/fut.21668   open full text
• Using Multivariate Densities to Assign Lattice Probabilities When There Are Jumps.
  Jimmy E. Hilliard, Jitka Hilliard.
  Journal of Futures Markets. March 27, 2014
  The lattice approximation to a continuous time process is an especially useful way to value American and real options. We choose lattice probabilities by extending density matching for diffusions to density matching for jump diffusions. Technically, this requires that diffusion and jump components be cast as independent state variables. In this setup, the diffusion probabilities are locally normal and the jump probabilities are locally a mixture of distributions. The lattice is structurally uniform and density matching ensures that all probabilities are legitimate without requiring jumps to non‐adjacent nodes. The approach generalizes easily to several state variables, does not require node adjustments, and does not appear to be dominated by more specialized numerical algorithms. We demonstrate the model for scenarios where the option may depend on a jump diffusion with possible stochastic interest rates and convenience yields. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  March 27, 2014   doi: 10.1002/fut.21667   open full text
• An Approach to the Option Market Model Based on End‐User Net Demand.
  Hiroshi Sasaki.
  Journal of Futures Markets. March 24, 2014
  In this paper, we study financial option prices and their related topics in terms of demand‐pressure effects of options contracts. Deriving equilibrium demand pressures for options, we provide an explicit representation of the pricing kernel in equilibrium between the supply and demand for options, which is a function of those of equilibrium demand pressures. On the basis of the demand‐based pricing kernel in equilibrium derived from our model setup, we provide some important implications for empirical evidence that have been provided in recent studies related to option pricing anomalies. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  March 24, 2014   doi: 10.1002/fut.21672   open full text
• A Random Field LIBOR Market Model.
  Tao L. Wu, Shengqiang Xu.
  Journal of Futures Markets. March 19, 2014
  A random field LIBOR market model (RFLMM) is proposed by extending the LIBOR market model, with interest rate uncertainties modeled via a random field. First, closed‐form formulas for pricing caplet and swaption are derived. Then the random field LIBOR market model is integrated with the lognormal‐mixture model to capture the implied volatility skew/smile. Finally, the model is calibrated to cap volatility surface and swaption volatilities. Numerical results show that the random field LIBOR market model can potentially outperform the LIBOR market model in capturing caplet volatility smile and the pricing of swaptions, in addition to possessing other advantages documented in the previous literature (no need of frequent recalibration or to specify the number of factors in advance). © 2014 Wiley Periodicals, Inc. Jrl Fut Mark 34:580–606, 2014

  March 19, 2014   doi: 10.1002/fut.21654   open full text
• A Partially Linear Approach to Modeling the Dynamics of Spot and Futures Prices.
  Jürgen Gaul, Erik Theissen.
  Journal of Futures Markets. March 18, 2014
  This paper considers the dynamics of spot and futures prices in the presence of arbitrage. A partially linear error correction model is proposed where the adjustment coefficient is allowed to depend nonlinearly on the lagged price difference. The model is estimated using data on the DAX index and the DAX futures contract. We find that the adjustment is indeed nonlinear. The linear alternative is rejected. The speed of price adjustment is increasing almost monotonically with the magnitude of the price difference. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  March 18, 2014   doi: 10.1002/fut.21669   open full text
• Futures Market Volatility: What Has Changed?
  Nicolas P.B. Bollen, Robert E. Whaley.
  Journal of Futures Markets. March 12, 2014
  The evolution of trading practices in futures markets, including growth of high‐frequency trading, has raised concerns about market quality. This study investigates whether excess futures return volatility, as an encompassing gauge of market quality, has changed over time. Daily measures of realized volatility are computed using 5‐minute returns of 15 electronically traded futures contracts. Two benchmarks are used to control for changes in the rate of information flow: option implied volatility and long horizon volatility estimates. Relative to the benchmarks, realized volatility has not changed, indicating that changes in trading practices have not led to a deterioration of market quality. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  March 12, 2014   doi: 10.1002/fut.21666   open full text
• Trading Patience, Order Flows, and Liquidity in an Index Futures Market.
  Caihong Xu.
  Journal of Futures Markets. March 05, 2014
  This study investigates the limit order book characteristics and the intertwined dynamics between trading patience, order flows, and liquidity in an index futures market. The limit order book displays a hump shape and the steepness of the hump is positively related to the number of large market orders. Bid and ask prices tend to move together in the same direction. Moreover, higher proportion of patient traders and higher order arrival rate lead to higher liquidity, after controlling for volatility and the intraday time effect. Liquidity is found to have a feedback effect on trading patience and the order arrival rate. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  March 05, 2014   doi: 10.1002/fut.21664   open full text
• Option‐Implied Preference with Model Uncertainty.
  Byung Jin Kang, Tong Suk Kim, Hyo Seob Lee.
  Journal of Futures Markets. March 03, 2014
  We present a theoretical model of option‐implied preferences with model uncertainty. An option‐implied risk aversion function with model uncertainty has a higher and a steeper level of risk aversion than an investor without model uncertainty. Based on the theoretical model, we try to extract empirical option‐implied risk aversion functions with S&P 500 index options. Our empirical option‐implied risk aversion with model uncertainty and option‐implied uncertainty premium show a decreasing and a smirk pattern across wealth. After subprime crisis, the shape of option‐implied risk aversion function with model uncertainty is not quite different, and both the level of option‐implied risk aversion function and the option‐implied uncertainty premium become slightly lowered. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark 34:498–515, 2014

  March 03, 2014   doi: 10.1002/fut.21660   open full text
• Petroleum Term Structure Dynamics and the Role of Regimes.
  Nikos K. Nomikos, Panos K. Pouliasis.
  Journal of Futures Markets. February 23, 2014
  This study investigates the dependence structure between correlated petroleum forward curves. After decomposing the term structure into level, slope, and curvature shocks we develop a flexible multi‐regime error‐correction factor model of the dynamics of the joint evolution of commodity pairs' curves. Volatilities and disequilibria across regimes are markedly different whereas the information content of the suggested framework is also tested in forecasting and value‐at‐risk experiments. The findings of this study have important implications for energy trading and risk management being particularly useful for predicting short‐term spreads and the correlation matrix among traded contracts. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark

  February 23, 2014   doi: 10.1002/fut.21657   open full text
• How Informed Investors Take Advantage of Negative Information in Options and Stock Markets.
  Jangkoo Kang, Hyoung‐Jin Park.
  Journal of Futures Markets. January 26, 2014
  We examine whether and how investors establish positions in options when they have negative information in the U.S. markets from August 2004 to January 2009. Our empirical results show that options seem to be actively and effectively used for the exploitation of negative information. General trading volumes and bid–ask spreads of options remarkably increase like those of stocks as the short sellers increase their selling pressure. Notably, we find that the difference between a stock's traded price and its implied price from the options market reaches its peak about 2 weeks before the short sale trading activity reaches its peak. We also observe that synthetic short positions measured by this difference are preferred over OTM put positions by investors with negative information. Finally, economically significant returns based on a strategy using the difference in the traded and implied stock prices as a trading signal support our evidence. Moreover, these profits confirm the findings of the previous research which argue that options are shelters for informed investors. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark 34:516–547, 2014

  January 26, 2014   doi: 10.1002/fut.21651   open full text
• Hawkes Process: Fast Calibration, Application to Trade Clustering, and Diffusive Limit.
  José Da Fonseca, Riadh Zaatour.
  Journal of Futures Markets. October 23, 2013
  This study provides explicit formulas for the moments and the autocorrelation function of the number of jumps over a given interval for a self‐excited Hawkes process. These computations are possible thanks to the affine property of this process. Using these quantities an implementation of the method of moments for parameter estimation that leads to an fast optimization algorithm is developed. The estimation strategy is applied to trade arrival times for major stocks that show a clustering behavior, a feature the Hawkes process can effectively handle. As the calibration is fast, the estimation is rolled to determine the stability of the estimated parameters. Lastly, the analytical results enable the computation of the diffusive limit in a simple model for the price evolution based on the Hawkes process. It determines the connection between the parameters driving the high‐frequency activity to the daily volatility. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:548–579, 2014

  October 23, 2013   doi: 10.1002/fut.21644   open full text
• Do option strategy traders have a disadvantage? Evidence from the Australian options market.
  Anthony Flint, Andrew Lepone, Jin Young Yang.
  Journal of Futures Markets. July 22, 2013
  This study measures the magnitude of execution costs of outright options and options which constitute strategies (“strategy‐linked options”), and examines if any differences in execution costs between these two groups is attributable to differences in market making costs on the Australian Options Market. Results reveal that execution costs for tailor‐made strategy‐linked options are greater than outright options. Also, this study provides evidence that the disadvantage of tailor‐made strategy‐linked options over outright options is driven by market makers' hedging costs. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  July 22, 2013   doi: 10.1002/fut.21634   open full text
• High moment variations and their application.
  Geon Ho Choe, Kyungsub Lee.
  Journal of Futures Markets. July 16, 2013
  We propose a new method of measuring the third and fourth moments of return distribution based on quadratic variation method when the return process is assumed to have zero drift. The realized third and fourth moment variations computed from high‐frequency return series are good approximations to corresponding actual moments of the return distribution. An investor holding an asset with skewed or fat‐tailed distribution is able to hedge the tail risk by contracting the third or fourth moment swap under which the float leg of realized variation and the predetermined fixed leg are exchanged. Thus, constructed portfolio follows more Gaussian‐like distribution and hence the investor effectively hedges the tail risk.

  July 16, 2013   doi: 10.1002/fut.21635   open full text
• The impact of co‐location of securities exchanges' and traders' computer servers on market liquidity.
  Alex Frino, Vito Mollica, Robert I. Webb.
  Journal of Futures Markets. July 12, 2013
  This study examines the impact of allowing traders to co‐locate their servers near exchange servers on the liquidity of futures contracts traded on the Australian Securities Exchange. It provides evidence of an increase in proxies for high‐frequency trading activity following the introduction of co‐location. There is strong evidence of a decrease in bid–ask spreads and an increase in market depth after the introduction of co‐location. We conclude that the introduction of co‐location enhances liquidity. We conjecture that co‐location improves the efficiency with which liquidity providers (including market maker high‐frequency traders) are able to make markets. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  July 12, 2013   doi: 10.1002/fut.21631   open full text
• Noisy inventory announcements and energy prices.
  Marketa W. Halova, Alexander Kurov, Oleg Kucher.
  Journal of Futures Markets. July 12, 2013
  This study examines the effect of oil and gas inventory announcements on energy prices. Previous estimates of this effect suffer from bias due to measurement error in inventory surprises. We utilize intraday futures data for three petroleum commodities and natural gas to estimate the price response coefficients using traditional event study regressions and the identification‐through‐censoring (ITC) technique proposed by Rigobon and Sack [Rigobon and Sack (2008). Asset prices and monetary policy (pp. 335–370). Chicago: University of Chicago Press]. The results show that the bias in OLS estimates of the price impact of inventory surprises is quite large. The ITC coefficient estimates are about twice as large as OLS estimates for petroleum commodities and about four times as large as OLS estimates for natural gas. These results imply that energy prices are more strongly influenced by unexpected changes in inventory than shown in previous research. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  July 12, 2013   doi: 10.1002/fut.21633   open full text
• Expiration‐day effects and the impact of short trading breaks on intraday volatility: Evidence from the Indian market.
  Sobhesh Kumar Agarwalla, Ajay Pandey.
  Journal of Futures Markets. June 28, 2013
  One distinct feature of the Indian stock market is the large trading volume of single stock futures, which are cash settled on the basis of the volume‐weighted average spot prices of the underlying stocks during the last half‐an‐hour of trading on the expiration day. We investigate the expiration day effect on intraday volatility and find that the volatility of the stocks increases in the last half‐an‐hour trade on the expiry day but not during the other time intervals. We also investigate the volatility surrounding the intraday trading breaks induced by satellite communication outages, a peculiar feature of the Indian stock market till 2008, and find that the volatility rises when the market reopens after the breaks but not before the breaks. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  June 28, 2013   doi: 10.1002/fut.21632   open full text
• Volatility discovery across stock limit order book and options markets.
  Qin Wang.
  Journal of Futures Markets. June 28, 2013
  Foucault [Journal of Financial Markets, 2, 99–134, 1999] provides a theoretical basis for how stock price volatility influences the aggressiveness of limit order traders. I investigate volatility discovery across stock limit order book and options markets using a broad panel of NYSE‐listed stocks from November 2007 to January 2008 and find strong evidence that, as predicted, the aggressiveness of the stock limit order book and option volatility trading Granger‐cause each other. Further, I find that the aggressiveness of the stock limit order book and option volatility trading are inversely related, which is both statistically and economically significant. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  June 28, 2013   doi: 10.1002/fut.21628   open full text
• Dynamic implied correlation modeling and forecasting in structured finance.
  Sebastian Löhr, Olga Mursajew, Daniel Rösch, Harald Scheule.
  Journal of Futures Markets. June 24, 2013
  Correlations are the main drivers for credit portfolio risk and constitute a major element in pricing credit derivatives such as synthetic single‐tranche collateralized debt obligation swaps. This study suggests a dynamic panel regression approach to model and forecast implied correlations. Random effects are introduced to account for unobservable time‐specific effects on implied tranche correlations. The implied‐correlation forecasts of tranche spreads are compared to forecasts using historical correlations from asset returns. The empirical findings support our proposed dynamic mixed‐effects regression correlation model. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  June 24, 2013   doi: 10.1002/fut.21626   open full text
• S&P 500 index‐futures price jumps and macroeconomic news.
  Hong Miao, Sanjay Ramchander, J. Kenton Zumwalt.
  Journal of Futures Markets. June 24, 2013
  This study examines the influence of macroeconomic news on price discontinuities in the S&P 500 index futures. Results document a strong association between macro news and price jumps. Over three‐fourths of the price jumps between 8:30 am and 8:35 am and over three‐fifths of the jumps between 10:00 am and 10:05 am are related to news released at 8:30 am and 10:30 am, respectively. Notably, among several types of news releases considered, Non‐farm Payroll and Consumer Confidence are found to be significantly related to price jumps. Our findings also provide insights into the speed of news absorption and the influence of alternative trading platforms on the jump return behavior. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  June 24, 2013   doi: 10.1002/fut.21627   open full text
• Multiscale Stochastic Volatility with the Hull–White Rate of Interest.
  Jeong‐Hoon Kim, Ji‐Hun Yoon, Seok‐Hyon Yu.
  Journal of Futures Markets. June 14, 2013
  Although interest rates fluctuate randomly, many option‐pricing models do not fully take into account their stochastic nature because of their generally limited impact on option prices. However, stochastic changes in stochastic interest rates may exert a significant impact on option prices when issues of maturity, hedging, or stochastic volatility are considered. This study incorporates the term structure of a stochastic interest rate driven by a Hull–White process into a stochastic volatility model in order to assess the sensitivity of option prices to changes in interest rate. It demonstrates that a stochastic volatility model with a stochastic interest rate outperforms a model with a constant interest rate, particularly, for short time‐to‐maturity European options. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  June 14, 2013   doi: 10.1002/fut.21625   open full text
• Testing the Efficient Market Hypothesis in Conditionally Heteroskedastic Futures Markets.
  Joakim Westerlund, Paresh Narayan.
  Journal of Futures Markets. June 10, 2013
  Most empirical evidence suggests that the efficient market hypothesis, stating that spot and futures prices should cointegrate with a unit slope on futures prices, does not hold. These results have recently motivated researchers to start looking for more “informative” tests, and the current paper takes a step in this direction. However, unlike existing tests, the test proposed here exploits the information contained in the heteroskedasticity of the data, which is expected to lead to more accurate inference, a result that is confirmed by our findings. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  June 10, 2013   doi: 10.1002/fut.21624   open full text
• Pricing Vulnerable Options with Correlated Credit Risk Under Jump‐Diffusion Processes.
  Lihui Tian, Guanying Wang, Xingchun Wang, Yongjin Wang.
  Journal of Futures Markets. June 07, 2013
  This study extends the framework of Klein [Journal of Banking & Finance, 20, 1211–1229] to price vulnerable options. We provide a pricing model for vulnerable options which face not only default risk but also rare shocks encountered by the underlying asset and the assets of the counterparty. The dynamics of asset prices are governed by jump‐diffusions with two sorts of assets correlated with each other. Jumps are divided into idiosyncratic component for each asset price and systematic component affecting the prices of all assets. A closed‐form valuation formula is derived for vulnerable European options. Numerical analysis compares the results of this model with those of other pricing formulae, and illustrates jump effects on the vulnerable option prices. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  June 07, 2013   doi: 10.1002/fut.21629   open full text
• Price Discovery in Futures and Options Markets.
  Naomi Boyd, Peter Locke.
  Journal of Futures Markets. May 21, 2013
  We evaluate price discovery in the natural gas futures and futures options markets using a transaction‐based approach. By sampling market maker prices, we allow for a distinction between market maker buy and sell futures prices, both directly from trades in the futures market, and futures prices implied by trades in the options market. Information shares are compared between futures and options markets as well as within the options market. Given the common architecture of the two markets, as expected we find little price information generated in the options market. Within the options market, the highly levered out‐of‐the‐money options offer less price discovery than other options. We attribute this to the higher transaction costs of out‐of‐the‐money options. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  May 21, 2013   doi: 10.1002/fut.21623   open full text
• Order Splitting Behavior by Different Types of Traders in the Taiwan Index Futures Markets Under Diverse Market Conditions.
  Yun‐Yi Wang.
  Journal of Futures Markets. May 03, 2013
  We set out in this study to empirically investigate the intraday pattern of order splitting behavior, along with the impacts of market conditions on the order splitting behavior of different types of traders. Our results indicate an intraday pattern in order splitting trading, which is found to be at its highest during the first hour of the trading day. We also present consistent evidence to show that order splitting behavior varies with market conditions, with a clear increase in such behavior when volume is at a high level, and when returns and volatility are at low levels. These results are particularly evident for foreign institutions and proprietary firms, although less so for domestic institutions and individual traders; this is possibly due to the greater sophistication of foreign institutional and proprietary firm traders, which enables them to dynamically alter their order submission strategies, depending upon the prevailing market conditions. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  May 03, 2013   doi: 10.1002/fut.21622   open full text
• Static Hedging with Traffic Light Options.
  Michael Schmutz, Thomas Zürcher.
  Journal of Futures Markets. May 03, 2013
  It is well known that sufficiently regular, one‐dimensional payoff functions have an explicit static hedge by bonds, forward contracts, and options in a continuum of strikes. An easy and natural extension of the corresponding representation leads to static hedges based on the same instruments along with traffic light options, which have recently been introduced in the market. It is well known that the second strike derivative of non‐discounted prices of vanilla options is related to the risk‐neutral density of the underlying asset price in the corresponding absolutely continuous settings. Similar statements hold for traffic light options in sufficiently regular, bivariate settings. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:690–702, 2014

  May 03, 2013   doi: 10.1002/fut.21621   open full text
• Options on Troubled Stock.
  António Câmara, Ivilina Popova, Betty Simkins.
  Journal of Futures Markets. April 18, 2013
  This study uses equilibrium arguments to derive closed‐form solutions for the price of European call and put options written on an individual stock when shareholders might lose all their claims on the firm. The stock price accounts for both a random probability of bankruptcy and a random probability of remaining a going concern. With a random probability of bankruptcy, shareholders lose all their claims in the firm. With a random probability of remaining a going concern, the stock price is lognormal as in the Black–Scholes model. The bankruptcy probability is correlated with aggregated wealth if the bankruptcy risk is systematic. The model is consistent with a bankruptcy probability negatively correlated with the firm's stock price. If the bankruptcy probability of a given firm increases then its stock price decreases which leads to the value of the call options written on that stock to decrease. This result is not obtainable under Merton's (1976) ruin model where the stock price and the bankruptcy probability are independent. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:637–657, 2014

  April 18, 2013   doi: 10.1002/fut.21616   open full text
• Expiration‐Day Effects of Stock and Index Futures and Options in Sweden: The Return of the Witches.
  Caihong Xu.
  Journal of Futures Markets. April 15, 2013
  Recently, the NASDAQ‐OMX Nordic Exchange announced a change of expiration day for the OMXS 30 index futures and options. The OMXS 30 index derivatives used to expire on the fourth Friday of the expiry month while derivatives on individual stocks expired on the third Friday. After the change, derivatives on both the index and individual stocks expire on the third Friday of the expiry month making the third Friday the “quadruple witching Friday” as stock futures, stock options, index futures, and index options expire simultaneously. This contractual change provides a unique opportunity to investigate its impact on expiration‐day effects. The results show that there is hardly any expiration‐day effect due to the derivatives' expirations before or after the contractual change, except the abnormally higher trading volumes at the stock derivatives' expirations before the change, and on the quadruple witching Fridays after the change. Most importantly, there is no significantly intensified abnormal volume, volatility, or price distortion effect due to the seemingly “extraordinary” change in the OMXS 30 index derivatives, despite the quadruple witching expirations after the change. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  April 15, 2013   doi: 10.1002/fut.21620   open full text
• Implied Pricing Kernels: An Alternative Approach for Option Valuation.
  Doojin Ryu, Jangkoo Kang, Sangwon Suh.
  Journal of Futures Markets. April 08, 2013
  This study proposes a new estimation approach for option valuation (an implied pricing kernel‐based approach), which estimates model parameters under the physical probability measure (P‐measure) using a pricing kernel implied by the GARCH option pricing model. Analyzing the dataset on the KOSPI 200 options market, we examine the empirical performance of the implied pricing kernel‐based approach and compare it with the performance of the classical GARCH option valuation approach (i.e., a pricing model‐based approach) that estimates model parameters under the risk‐neutral probability measure (Q‐measure). As proposed in this study, the implied pricing kernel‐based estimation approach requires approximation and discretization in order to derive the functional form of the pricing kernel. Regardless of this approximation, however, when it comes to pricing OTM calls, the implied pricing kernel‐based approach performs slightly better than the pricing model‐based approach that has been traditionally used for option valuation. Additional analysis based on the put option sample indicates that the implied pricing kernel‐based approach clearly dominates the classical pricing model‐based approach during the early stage of emergence of the KOSPI 200 options market (1999–2000) when the market was immature. During the recent global financial crisis (2007–2009), the pricing kernel‐based approach also yields smaller pricing errors for OTM puts than the classical approach does. These empirical results imply that the new approach suggested in this study can be advantageous for option valuation, particularly when the information embedded in options prices is not sufficient for estimation and/or the market is speculative and volatile. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  April 08, 2013   doi: 10.1002/fut.21618   open full text
• A Copula‐Based Quantile Risk Measure Approach to Estimate the Optimal Hedge Ratio.
  Massimiliano Barbi, Silvia Romagnoli.
  Journal of Futures Markets. April 04, 2013
  We propose an innovative theoretical model to determine the optimal hedge ratio (OHR) with futures contracts as the minimizer of a quantile risk measure. This class of measures is very large and allows to recover the minimum‐VaR and the minimum‐expected shortfall hedge ratios as special cases. The copula representation of quantiles yields an accurate and flexible estimation of the dependence structure between the spot and the futures position. Employing data for the main UK and US indices, and EUR/USD and EUR/GBP exchange rates, we investigate the hedging effectiveness of our model compared to that of existing approaches. We document that our model improves upon the hedging performance of minimum‐VaR and minimum‐expected shortfall hedge ratios, provided that the copula shows an acceptable fit to the data. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:658–675, 2014

  April 04, 2013   doi: 10.1002/fut.21617   open full text
• The Predictive Content of Commodity Futures.
  Menzie D. Chinn, Olivier Coibion.
  Journal of Futures Markets. March 30, 2013
  This study examines the predictive content of futures prices for energy, agricultural, precious and base metal commodities. In particular, we examine whether futures prices are (1) unbiased and/or (2) accurate predictors of subsequent prices. We document significant differences both across and within commodity groups. Precious and base metals fail most tests of unbiasedness and are poor predictors of subsequent price changes but energy and agricultural futures fare much better. We find little evidence that these differences reflect liquidity conditions across markets. In addition, we document a broad decline in the predictive content of commodity futures prices since the early 2000s. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:607–636, 2014

  March 30, 2013   doi: 10.1002/fut.21615   open full text
• Option Valuation Under a Double Regime‐Switching Model.
  Yang Shen, Kun Fan, Tak Kuen Siu.
  Journal of Futures Markets. March 28, 2013
  This paper is concerned with option valuation under a double regime‐switching model, where both the model parameters and the price level of the risky share depend on a continuous‐time, finite‐state, observable Markov chain. In this incomplete market set up, we first employ a generalized version of the regime‐switching Esscher transform to select an equivalent martingale measure which can incorporate both the diffusion and regime‐switching risks. Using an inverse Fourier transform, an analytical option pricing formula is obtained. Finally, we apply the fast Fourier transform method to compute option prices. Numerical examples and empirical studies are used to illustrate the practical implementation of our method.

  March 28, 2013   doi: 10.1002/fut.21613   open full text
• Incremental Value of a Futures Hedge Using Realized Ranges.
  Her‐Jiun Sheu, Yu‐Sheng Lai.
  Journal of Futures Markets. March 21, 2013
  This study investigates the information content of realized ranges for futures hedging. Hedge ratio estimation using generalized autoregressive conditional heteroscedasticity (GARCH) models augmented with intraday price range is proposed. Empirical investigations using the S&P 500 equity index data show that the in‐sample fitting of spot–futures distribution is improved by the information recovered from intraday price ranges. Furthermore, the out‐of‐sample forecasting results show that both the statistical and economic hedging effectiveness increase with the inclusion of intraday price ranges along with intraday and daily price returns. Results indicate that informative realized ranges are valuable for futures hedging. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:676–689, 2014

  March 21, 2013   doi: 10.1002/fut.21614   open full text
• Exercise to Lose Money? Irrational Exercise Behavior from the Chinese Warrants Market.
  Li Liao, Zhisheng Li, Weiqiang Zhang, Ning Zhu.
  Journal of Futures Markets. March 19, 2013
  Using a market‐level exercise data set and an individual‐level trading data set between August 2006 and June 2009, this study examines the incidence of two types of irrational exercise behavior in the Chinese warrants market. We find that 121.64 million shares of warrants (0.64% of all warrants) were either exercised with an immediate loss or failed to be exercised, resulting in foregone risk‐free profits. These irrational exercises caused warrant holders to lose over 717.79 million Yuan. Some of the irrational behavior can be attributed to “entertainment seeking” and the “T + 1” rule practiced in the Chinese security market, but the majority is attributed to warrant holders' ignorance and/or negligence of warrant mechanics. Our findings provide additional field evidence of clearly irrational exercise behavior in a derivatives market. We also find that investor education, information and guidance provision can mitigate the incidence of irrational exercise behavior significantly. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  March 19, 2013   doi: 10.1002/fut.21608   open full text
• Pricing Forward Skew Dependent Derivatives. Multifactor Versus Single‐Factor Stochastic Volatility Models.
  Jacinto Marabel Romo.
  Journal of Futures Markets. February 25, 2013
  Empirical evidence shows that, in equity options markets, the slope of the skew is largely independent of the volatility level. Single‐factor stochastic volatility models are not flexible enough to account for the stochastic behavior of the skew. On the other hand, multifactor stochastic volatility models are able to account for the existence of stochastic skew. This study studies the effects of introducing stochastic skew in the valuation of forward skew dependent exotic options. In particular, I consider cliquet, as well as reverse cliquet structures. The study also derives a semi‐closed‐form solution for the price of forward‐start options under the multifactor stochastic specification. The empirical results indicate that the consideration of additional volatility factors in the context of stochastic volatility models allows us to generate more flexible smile patterns. This additional flexibility has a relevant impact on the valuation of forward skew dependent derivatives. In this sense, this study shows that similar calibrations of single factor and multifactor stochastic volatility models to the current market prices of plain vanilla options can lead to important discrepancies in the pricing of exotic forward skew dependent derivatives such as regular cliquet structures and reverse cliquet options. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  February 25, 2013   doi: 10.1002/fut.21611   open full text
• Testing Alternative Measure Changes in Nonparametric Pricing and Hedging of European Options.
  Jamie Alcock, Godfrey Smith.
  Journal of Futures Markets. February 22, 2013
  Haley and Walker [Haley, M.R., & Walker, T. (2010). Journal of Futures Markets, 30, 983–1006] present the Euclidean and Empirical Likelihood nonparametric option pricing models as alternative tilts to Stutzer's [Stutzer, M. (1996). Journal of Finance, 51, 1633–1652] Canonical pricing method. We empirically test the comparative strengths of each of these methods using a large sample of traded options on the S&P100 Index. Furthermore, we explore an additional tilt based on Pearson's chi‐square, and derive and empirically test nonparametric delta hedges for each of these approaches. Differences in the pricing performance of the various tilts are a function of differences between the sample distribution and the real distribution of the underlying. When the sample distribution displays fatter (thinner) tails and/or higher (lower) volatility than the true distribution, the Euclidean (Pearson's chi‐square) model outperforms. Significantly, when these nonparametric methods utilize information contained in a small number of observed option prices they often outperform the implied volatility Black and Scholes [Black, F., & Scholes, M. (1973). Journal of Political Economy, 81, 637–654] model. These pricing performance differences do not translate into static and dynamic hedging performance differences. However, each of the nonparametric models induce an implied volatility smile and term structure that generally agree in form with the smile and term structure embedded in market prices.

  February 22, 2013   doi: 10.1002/fut.21602   open full text
• Do Seasonal Tropical Storm Forecasts Affect Crack Spread Prices?
  Jason Fink, Kristin Fink.
  Journal of Futures Markets. February 16, 2013
  Individual storms in the Gulf of Mexico have been shown to affect crack spread futures prices. As hurricanes strike refiner‐dense areas, prices of refined petroleum products rise. We find that crack spread prices are even affected by seasonal hurricane forecasts. We find this despite the difficulties of long horizon forecasting, and that refiners are only exposed in a small portion of the Atlantic basin. These effects are economically important. For example, a one standard deviation increase in the June forecast of the net tropical cyclone activity in the upcoming season increases 3‐2‐1 crack spread prices by over 9%.

  February 16, 2013   doi: 10.1002/fut.21607   open full text
• Municipal Bonds and Monetary Policy: Evidence from the Fed Funds Futures Market.
  Carlo Rosa.
  Journal of Futures Markets. February 15, 2013
  This paper examines the impact of conventional and unconventional monetary policy on municipal bonds using a novel high‐frequency dataset. I use three proxies for monetary policy surprises: the surprise change to the current federal funds target rate, the surprise component in the Federal Open Market Committee (FOMC) balance‐of‐risk statement, and the unanticipated announcements of future large‐scale asset purchases. Estimation results show that monetary policy news have economically important and highly significant effects on municipal bond prices. Their daily responses are, however, substantially lower than the reaction of comparable Treasury notes. This work documents that market (in)efficiency, and the slow adjustment of municipal bond prices, can partially rationalize this discrepancy.

  February 15, 2013   doi: 10.1002/fut.21606   open full text
• A Jump Diffusion Model for Agricultural Commodities with Bayesian Analysis.
  Adam Schmitz, Zhiguang Wang, Jung‐han Kimn.
  Journal of Futures Markets. February 15, 2013
  Stochastic volatility, price jumps, seasonality, and stochastic cost of carry have been included separately, but not collectively, in pricing models of agricultural commodity futures and options. We propose a comprehensive model that incorporates all four features. We employ a special Markov chain Monte Carlo algorithm, new in the agricultural commodity derivatives pricing literature, to estimate the proposed stochastic volatility (SV) and stochastic volatility with jumps (SVJ) models. Overall model fitness tests favor the SVJ model. The in‐sample and out‐of‐sample pricing results for corn, soybeans and wheat generally, with few exceptions, lend support for the SVJ model.

  February 15, 2013   doi: 10.1002/fut.21597   open full text
• Forward‐Looking Monetary Policy Rules and Option‐Implied Interest Rate Expectations.
  Jukka Sihvonen, Sami Vähämaa.
  Journal of Futures Markets. February 14, 2013
  This paper examines the association between option‐implied interest rate distributions and macroeconomic expectations in the context of a forward‐looking monetary policy rule. We presume that market participants view the policy rule as a guide to the path of future policy rates and price interest rate options in accordance with the policy rule fundamentals. Using data from the UK, we confirm that Libor expectations implied by option prices are consistent with the policy rule variables. The results demonstrate that changes in the distributional form of Libor expectations are strongly associated with changes in the expected inflation and output gaps and financial uncertainty.

  February 14, 2013   doi: 10.1002/fut.21596   open full text
• Closing Call Auctions at the Index Futures Market.
  Björn Hagströmer, Lars Nordén.
  Journal of Futures Markets. February 14, 2013
  We investigate the effects from the introduction of a closing call auction (CCA) at the index futures market. Limit order book models, where trader patience determines trading strategies, predict that a CCA increases trader patience and, hence, improves closing price accuracy and end‐of‐day liquidity. We find that the introduction leads to increased trader patience, improved futures closing price accuracy, unaffected tightness and resiliency, and decreased depth. Decreased depth is likely due to less order fishing activity. With the CCA, opportunistic patient traders' posting of limit orders deep in the order book, to profit from impatient traders, is no longer feasible.

  February 14, 2013   doi: 10.1002/fut.21603   open full text
• Measuring Hedging Effectiveness of Index Futures Contracts: Do Dynamic Models Outperform Static Models? A Regime‐switching Approach.
  Enrique Salvador, Vicent Aragó.
  Journal of Futures Markets. February 14, 2013
  This study estimates linear and nonlinear GARCH models to find optimal hedge ratios with futures contracts for some of the main European stock indexes. By introducing nonlinearities through a regime‐switching model, we can obtain more efficient hedge ratios and superior hedging performance in both an in‐sample and an out‐sample analysis compared to the other methodologies (constant hedge ratios and linear GARCH). Moreover, nonlinear models also reflect the different patterns followed by the dynamic relationship between the volatility of spot and futures returns during low‐ and high‐volatility periods.

  February 14, 2013   doi: 10.1002/fut.21598   open full text
• The Return‐Implied Volatility Relation for Commodity ETFs.
  Chaiyuth Padungsaksawasdi, Robert T. Daigler.
  Journal of Futures Markets. January 02, 2013
  We examine the return‐implied volatility relation by employing “commodity” option VIXs for the euro, gold, and oil. This relation is substantially weaker than for stock indexes. We propose several potential reasons for these unusually weak results. Also, gold possesses an unusual positive contemporaneous return coefficient, which is consistent with a demand volatility skew rather than the typical investment skew. Moreover, the euro and gold are not asymmetric. We relate the results to trading strategies, algorithmic trading, and behavioral theories. An important conclusion of the study is that important differences exist regarding implied volatility for certain types of assets that have not yet been explained in the literature; namely, the results in this study concerning commodity ETFs versus stock indexes, plus previous research on stock indexes versus individual stocks, and the pricing of stock index options versus individual stock options. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

  January 02, 2013   doi: 10.1002/fut.21592   open full text
• Pricing Multiasset Cross‐Currency Options.
  Kenichiro Shiraya, Akihiko Takahashi.
  Journal of Futures Markets. December 21, 2012
  This study develops a general pricing method for multiasset cross‐currency options, whose underlying asset consists of multiple different assets, and the evaluation currency is different from the ones used in the most liquid market of each asset; the examples include cross‐currency options, cross‐currency basket options, and cross‐currency average options. Moreover, in practice, fast calibration is necessary in the option markets relevant for the underlying assets and the currency, which is also achieved in this study. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  December 21, 2012   doi: 10.1002/fut.21590   open full text
• Price Discovery in Interrelated Markets.
  Donald Lien, Keshab Shrestha.
  Journal of Futures Markets. December 11, 2012
  In this study, we generalize the information share (IS) proposed by Hasbrouck (1995) and extended by Lien and Shrestha (2009). The new generalized information share (GIS) can be used to analyze the price discovery process in interrelated securities markets, whereas the previous two measures can only be applied to almost identical markets. Thus, using the GIS, we can analyze broader markets thereby improving our understanding of the price discovery process as well as the efficiency of securities markets. As an empirical demonstration of the proposed method, we apply the GIS to credit default swap (CDS) and bond markets, and find that for the majority of cases price discovery mostly takes place in the CDS markets. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  December 11, 2012   doi: 10.1002/fut.21593   open full text
• Aggregate Volatility and Market Jump Risk: An Option‐Based Explanation to Size and Value Premia.
  Yakup Eser Arisoy.
  Journal of Futures Markets. December 11, 2012
  It is well documented that stock returns have different sensitivities to changes in aggregate volatility, however less is known about their sensitivity to market jump risk. By using S&P 500 crash‐neutral at‐the‐money straddle and out‐of‐money put returns as proxies for aggregate volatility and market jump risk, I document significant differences between volatility and jump loadings of value versus growth, and small versus big portfolios. In particular, small (big) and value (growth) portfolios exhibit negative (positive) and significant volatility and jump betas. I also provide further evidence that both volatility and jump risk factors are priced and negative. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  December 11, 2012   doi: 10.1002/fut.21589   open full text
• Intraday Liquidity Provision by Trader Types in a Limit Order Market: Evidence from Taiwan Index Futures.
  Junmao Chiu, Huimin Chung, George H. K. Wang.
  Journal of Futures Markets. November 28, 2012
  This study examines the dynamic liquidity provision process by institutional and individual traders in the Taiwan index futures market, which is a pure limit order market. The empirical analysis obtains several interesting empirical results. We find that trader type affects liquidity provision in a number of interesting ways. First, although institutional traders use more limit orders than market orders, foreign institution (individual) traders use a relatively higher percentage of market (limit) orders in the early trading session and then switch to more limit (market) orders for the remainder of the day until close to the end of the trading day. Second, net limit order submissions by both institutional and individual traders are positively related to one‐period lagged transitory volatility and negatively related to informational volatility. Third, net limit order submissions by institutional traders are positively related to one‐period lagged spread. Finally, both the state of limit order book and order size significantly influence all types of traders’ strategy on submission of limit order versus market order during the intraday trading session. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  November 28, 2012   doi: 10.1002/fut.21586   open full text
• A Filtering Process to Remove the Stochastic Component from Intraday Seasonal Volatility.
  Jang Hyung Cho, Robert T. Daigler.
  Journal of Futures Markets. November 26, 2012
  The intraday seasonal variance pattern contains stochastic as well as deterministic components. Therefore, the estimation of information arrivals in the associated volatility process requires the proper filtering of both of these seasonal components. However, popular current models remove only the deterministic part of the typical U‐shape volatility. Here, we provide the first empirical results of the importance of the stochastic component, as developed by Cho and Daigler (2012). We show that a highly significant additional 8.5% to 12.9% of the total seasonal variance is explained by the stochastic seasonal variance component for S&P500 futures, live cattle futures, and the Japanese yen‐U.S. dollar spot exchange rate. Moreover, we show that the stochastic seasonal filtering model implemented here does not create any statistical distortions of the filtered series, as occurs with deterministic‐based seasonal adjustment processes, as well as comparing the model examined here with the most popular current deterministic model. As part of our analysis we examine the application of the model to macroeconomic news and out‐of‐sample results for the model. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  November 26, 2012   doi: 10.1002/fut.21585   open full text
• Recursive Formula for Arithmetic Asian Option Prices.
  Kyungsub Lee.
  Journal of Futures Markets. November 26, 2012
  I derive a recursive formula for arithmetic Asian option prices with finite observation times in semimartingale models. The method is based on the relationship between the risk‐neutral expectation of the quadratic variation of the return process and European option prices. The computation of arithmetic Asian option prices is straightforward whenever European option prices are available. Applications with numerical results under the Black–Scholes framework and the exponential Lévy model are proposed. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  November 26, 2012   doi: 10.1002/fut.21591   open full text
• Examining the Return–Volatility Relation for Foreign Exchange: Evidence from the Euro VIX.
  Robert T. Daigler, Ann Marie Hibbert, Ivelina Pavlova.
  Journal of Futures Markets. November 26, 2012
  We compare the return–volatility relation for the euro currency to the equivalent relation for the equity market, examining the sign, symmetry, and strength of the relation. We employ the euro‐currency exchange‐traded fund (FXE) and its associated option implied volatility index (the EVZ), whereas previous studies only employ equities and/or realized volatility. The equity studies find a negative asymmetric return–volatility relation for implied volatility, with a strong relation when large market movements occur. We find that the euro return–volatility relation can possess either a positive or negative sign, is asymmetric, and has a weaker relation. Thus, the sign and strength of the euro relation differs from the equivalent equity relation. Our quantile regressions show that both the positive and negative contemporaneous returns of the euro result in increased volatility in the extreme quantiles of the conditional distribution, with the contemporaneous effect showing a stronger relation when the euro depreciates. We also find that the volume of the euro‐currency ETF options affects the return–volatility relation for the euro ETF. Overall, the results here expand the concept originally restricted to equities, with the surprising results that the return‐implied volatility relation is weaker and the asymmetric return sometimes is positive for the euro currency. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  November 26, 2012   doi: 10.1002/fut.21582   open full text
• How Different Types of Traders Behave in the Taiwan Futures Market.
  Hung Chih Li, Chao Hsien Lin, Teng Yuan Cheng, Syouching Lai.
  Journal of Futures Markets. November 20, 2012
  This paper examines the heterogeneity of the disposition effect and its impact on profitability among three different types of traders, using complete trading data from Taiwan's futures market. More than 70% of the trading volume on this market comes from retail traders (RTs), with an additional 15% from foreign institutional traders (FIs) and proprietary traders (PTs). Both FIs and RTs exhibit the disposition effect whereas PTs do not, and FIs with a weaker disposition effect outperform RTs. This study provides evidence that RTs with the disposition effect tend to lessen the effect in the next period, exhibiting the phenomenon of mean reversion. While previous studies focus only on the static relationship between the disposition effect and profitability, ours explores the dynamic rather than the static behavior of RTs, providing a more complete and objective idea of their trading behavior. In addition, the positive relationship between the current disposition effect and prior profits suggests that the degree of the disposition effect increases when RTs have prior profits. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  November 20, 2012   doi: 10.1002/fut.21588   open full text
• Optimal Futures Hedging Under Multichain Markov Regime Switching.
  Her‐Jiun Sheu, Hsiang‐Tai Lee.
  Journal of Futures Markets. November 09, 2012
  Most of the existing Markov regime switching GARCH‐hedging models assume a common switching dynamic for spot and futures returns. In this study, we release this assumption and suggest a multichain Markov regime switching GARCH (MCSG) model for estimating state‐dependent time‐varying minimum variance hedge ratios. Empirical results from commodity futures hedging show that MCSG creates hedging gains, compared with single‐state‐variable regime‐switching GARCH models. Moreover, we find an average of 24% cross‐regime probability, indicating the importance of modeling cross‐regime dynamic in developing optimal futures hedging strategies.

  November 09, 2012   doi: 10.1002/fut.21583   open full text
• The Volatility Behavior and Dependence Structure of Commodity Futures and Stocks.
  Lin Gao, Lu Liu.
  Journal of Futures Markets. November 07, 2012
  This study finds substantial risk diversification potential between certain commodity groups and stocks by exploring the dependence between their patterns of regime switching. None of the commodity groups share a common volatility regime with stocks, nor are the regime‐switching patterns of grains, industrials, metals, or softs, dependent on that of stocks. Simultaneous volatile regimes of commodity futures and stocks tend to be infrequent and short‐lived. In addition, in spite of financial contagion, animal products, grains, and softs typically demonstrate very low correlations with stocks even in simultaneous volatile regimes. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  November 07, 2012   doi: 10.1002/fut.21587   open full text
• A Note on Exports and Hedging Exchange Rate Risks: The Multi‐Country Case.
  Kit Pong Wong.
  Journal of Futures Markets. November 07, 2012
  This study examines the behavior of an exporting firm that exports to two foreign countries, each of which has its own currency. Hedging is imperfect in that the firm can only trade one of the two foreign currencies forward. Compared to the case wherein hedging is perfect in that both foreign currencies can be traded forward, the firm is shown to produce less in the home country. Furthermore, the firm is shown to export more (less) to the foreign country whose currency can (cannot) be traded forward. The firm's optimal forward position is an over‐hedge or an under‐hedge, depending on whether the spot exchange rates are positively or negatively correlated in the sense of expectation dependence, respectively. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  November 07, 2012   doi: 10.1002/fut.21584   open full text
• Long‐term Futures Curves and Seasonal Structures of Wheat in the European Union and the United States.
  Sergio H. Lence, Hervé G. Ott, Chad E. Hart.
  Journal of Futures Markets. August 16, 2012
  A two‐factor affine theoretical model is used to estimate the long‐term futures curves for wheat in the European Union and the United States, as represented by the Euronext and CME markets, respectively. The CME futures curve exhibits a long‐term equilibrium; in contrast, the Euronext futures curve does not show a tendency for futures to revert to a long‐term equilibrium value. The estimated seasonality is relatively similar for both markets. However, the seasonal minimum and maximum points in the futures curve occur one to two months later for Euronext compared to the CME. More importantly, the futures curve for Euronext has a much more marked seasonality than the CME futures curve. Credible intervals of the futures curves are also estimated. The width clearly increases for longer maturities, but it does so much faster for Euronext than for the CME. For long‐maturity futures, variability in the parameter estimates (as opposed to the residual errors) accounts for most of the width of the credible intervals, especially for Euronext. The proposed model can be used to price long‐term futures options, long‐term price insurance, and long‐term swaps, among other applications.

  August 16, 2012   doi: 10.1002/fut.21581   open full text
• The Relation Between Market Liquidity and Anonymity in the Presence of Tick Size Constraints.
  Christine Brown, Astrophel Kim Choo, Sean Pinder.
  Journal of Futures Markets. August 03, 2012
  In February 2004, the Sydney Futures Exchange removed broker identifiers from the electronic limit order book for interest rate futures contracts, with the stated objective of maintaining transparency and improving market participation and liquidity. We show how the Exchange's aims were generally met by documenting an increase in volume and frequency of trades and a decline in time‐weighted quoted spreads. Although daily effective spreads do not decline, intraday analysis demonstrates that there are improvements in effective spreads which are concentrated to those points in time where the bid–ask spread is not constrained by the size of the minimum tick, and where information asymmetries are present.

  August 03, 2012   doi: 10.1002/fut.21580   open full text
• Does Index Futures Trading Reduce Volatility in the Chinese Stock Market? A Panel Data Evaluation Approach.
  Haiqiang Chen, Qian Han, Yingxing Li, Kai Wu.
  Journal of Futures Markets. July 30, 2012
  This study investigates the effect of introducing index futures trading on the spot price volatility in the Chinese stock market. We employ a recently developed panel data policy evaluation approach (Hsiao, Ching, and Wan, 2011) to construct counterfactuals of the spot market volatility, based mainly on cross‐sectional correlations between the Chinese and international stock markets. This new method does not need to specify a particular regression or a time‐series model for the volatility process around the introduction date of index futures trading, and thus avoids the potential omitted variable bias caused by uncontrolled market factors in the existing literature. Our results provide empirical evidence that the introduction of index futures trading significantly reduces the volatility of the Chinese stock market, which is robust to different model selection criteria and various prediction approaches. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark

  July 30, 2012   doi: 10.1002/fut.21573   open full text
• The Price Discovery Puzzle in Offshore Yuan Trading: Different Contributions for Different Contracts.
  David K. Ding, Yiuman Tse, Michael R. Williams.
  Journal of Futures Markets. July 23, 2012
  The People's Bank of China (PBC) lifted yuan trading restrictions in July of 2010 that led to offshore yuan spot trading in Hong Kong. Based on causality analyses, we find that price discovery is absent between the onshore and offshore spot markets. However, we document the presence of price discovery between onshore spot and offshore nondeliverable forward (NDF) rates. These seemingly inconsistent results present a puzzle wherein one offshore market appears to be more informationally integrated with the onshore market than another. We conclude that price discovery differences in the offshore markets stem from the offshore spot and forward contracts tracking different aspects of yuan rates (e.g., the offshore nondeliverable rate tracks onshore spot rates whereas the offshore spot rate tracks onshore interest rates). Moreover, the introduction of offshore spot trading in Hong Kong has led to an increase in cross‐market price discovery between onshore spot and offshore NDF rates.

  July 23, 2012   doi: 10.1002/fut.21575   open full text
• Can the Indicative Price System Mitigate Expiration‐Day Effects?
  J.B. Chay, Sol Kim, Hyeuk‐Sun Ryu.
  Journal of Futures Markets. July 13, 2012
  We investigate whether the indicative price system, introduced in the Korean derivatives market on July 1, 2003, has helped mitigate the options and futures expiration‐day effects. Prior to introduction of this system, we find evidence of high trading volume and significant price reversals during the first half hour of trading for the day immediately following the expiration day. These effects decline significantly after July 1, 2003. Our evidence suggests that the indicative price system can mitigate the expiration‐day effects.

  July 13, 2012   doi: 10.1002/fut.21574   open full text
• A Quasi‐Analytical Pricing Model for Arithmetic Asian Options.
  Jianqiang Sun, Langnan Chen, Shiyin Li.
  Journal of Futures Markets. July 11, 2012
  We develop a quasi‐analytical pricing method for discretely sampled arithmetic Asian options. We derive an asymptotic approximation of the arithmetic average with the geometric average of lognormal variables. Numerical experiments show that the asymptotic approximation is accurate and the absolute error converges very quickly as the number of observations increases. The absolute error is of the order of 10−5 to 10−6 for daily average. We then derive quasi‐analytical formulas for arithmetic Asian options under the Black–Scholes framework, in which the probability density of the geometric average is used. Extensive experiments are conducted to compare the proposed method with the various existing semianalytical methods. The overall accuracy of the proposed method is better than any other methods tested. The proposed method performs much better than the second best one for at‐the‐money Asian options under high volatility. The mean pricing error of the proposed method for a daily average Asian option is 37.5% less than the second best one.

  July 11, 2012   doi: 10.1002/fut.21576   open full text
• Strategic and Tactical Roles of Enhanced Commodity Indices.
  Georgios Rallis, Joëlle Miffre, Ana‐Maria Fuertes.
  Journal of Futures Markets. June 28, 2012
  This article formally compares two traditional long‐only commodity indices, Standard & Poor's Goldman Sachs Commodity Index (S&P‐GSCI) and Dow Jones‐UBS Commodity Index (DJ‐UBSCI), with their enhanced versions that exploit signals based on contract maturity, momentum, and term structure. The enhanced indices are found to be useful for tactical asset allocation. With alphas ranging from 2.77% to 5.49% per annum, the maturity‐enhanced indices offer the best abnormal performance after accounting for liquidity risk. Momentum and term structure enhancements also earn a positive, albeit smaller, alpha of 2.10% per annum on average. All the enhanced indices are found to have comparable effectiveness for risk diversification and inflation hedging as their traditional counterparts, making them useful for strategic asset allocation.

  June 28, 2012   doi: 10.1002/fut.21571   open full text
• Investigating the Information Content of the Model‐Free Volatility Expectation by Monte Carlo Methods.
  Yuanyuan Zhang, Stephen J. Taylor, Lili Wang.
  Journal of Futures Markets. June 25, 2012
  We explore the impact of both the number of option prices and the measurement errors in option prices upon the information content of the model‐free volatility expectation, and compare it with the Black–Scholes at‐the‐money (ATM) implied volatility. We simulate the realized volatility process and option prices using Heston's price dynamics and option valuation formula. The results show that the model‐free volatility expectation always contains important information about future realized volatilities. When the option prices contain random measurement noise, the informational efficiency of the model‐free volatility expectation increases monotonically with the number of out‐of‐the‐money options. The model‐free volatility expectation outperforms the ATM implied volatility, except when there are only a few option price observations. For the traded strikes for S&P 500 index options, we further show that fitting implied volatility curves before applying the current CBOE procedure for constructing the VIX index can improve the VIX's efficiency when forecasting future realized volatilities.

  June 25, 2012   doi: 10.1002/fut.21570   open full text
• Market Reaction to Information Shocks—Does the Bloomberg and Briefing.com Survey Matter?
  Linda H. Chen, George J. Jiang, Qin Wang.
  Journal of Futures Markets. June 12, 2012
  Bloomberg and Briefing.com provide competing forecasts for prescheduled macroeconomic announcements. This study examines the accuracy of these forecasts and market reactions to announcement surprises. Our results show that the Bloomberg survey is slightly more accurate than the Briefing.com survey. More importantly, although announcement surprises based on both surveys have a significant effect on the trading activities and returns of S&P 500 futures contracts, the Bloomberg survey subsumes the explanatory power of the Briefing.com survey. The findings suggest that on average Bloomberg forecasts are more consistent with the market consensus view. In addition, we provide evidence of asymmetric market reactions to positive versus negative announcement surprises. In particular, the market reacts strongly to inflation news in the Consumer Price Index (CPI) and Producer Price Index (PPI) announcements and negative shocks in housing price, personal spending, and retail sales.

  June 12, 2012   doi: 10.1002/fut.21564   open full text
• Inflation Derivatives Under Inflation Target Regimes.
  Mordecai Avriel, Jens Hilscher, Alon Raviv.
  Journal of Futures Markets. June 11, 2012
  Inflation targeting—the central bank practice of attempting to keep inflation levels within fixed bounds around a quantitative target—has been adopted by more than 20 economies. Such practice has an important impact on the stochastic nature of inflation and, consequently, on the pricing of inflation derivatives. We develop a flexible model of inflation targeting in which the central bank's intervention to steer inflation toward the target depends on past deviations and the policymaker's ability and will to enforce the target. We use our model to price inflation derivatives and demonstrate the impact of inflation targeting on derivative pricing.

  June 11, 2012   doi: 10.1002/fut.21568   open full text