["International Journal of Finance &Economics, EarlyView. ", "\nABSTRACT\nWe examine whether two major alternative data sources, limit order book information and firm‐specific news, provide incremental predictive information for daily realised volatility forecasting within the HAR‐family, using a parsimonious framework to ensure practical implementation and comparability. The framework is designed for practical real‐time forecasting, requiring minimal changes to the benchmark specification and no auxiliary models. Relative to a strong benchmark, both sources contain incremental predictive information, although the gains are more consistent for firm‐specific news, which emerges as the most reliable signal. The news volume measure delivers the most robust improvements overall, while sentiment‐based measures provide less consistent gains, indicating that news arrival matters more than news tone; within the order book, depth measures contribute more to forecasting performance than slope measures. Predictive gains are strongest on high volatility days, and a trade‐off between performance on normal and high volatility days is evident across signals.\n"]