Although speculative activity is central to black markets for currency, the out‐of‐sample performance of structural models in those settings is unknown. We substantially update the literature on empirical determinants of black market rates and evaluate the out‐of‐sample performance of linear models and non‐parametric Bayesian treed Gaussian process (BTGP) models against the random walk benchmark. Fundamentals‐based models outperform the benchmark in out‐of‐sample prediction accuracy and trading rule profitability measures given future values of fundamentals. In simulated real‐time trading exercises, however, the BTGP achieves superior realized profitability, accuracy and market timing, while linear models do no better than a random walk. Copyright © 2013 John Wiley & Sons, Ltd.