Policy Uncertainty and Stock Market Volatility Revisited: The Predictive Role of Signal Quality

This paper provides novel mixed-frequency insight to the growing literature on the (monthly) economic policy uncertainty-(daily) stock market volatility nexus by examining the out-of-sample predictive ability of the quality of political signals over stock market volatility at various forecast horizons, and whether or not accounting for the signal quality in forecasting models can help achieve economic gains for investors. Both in- and out-of-sample tests, based on a GARCH-MIDAS framework, show that the quality of the policy signal indeed matters when it comes to the predictive role played by policy uncertainty over subsequent stock market volatility. While high EPU is found to predict high volatility, particularly when the signal quality is high, the positive relationship between EPU and volatility breaks down when the signal quality is low. The improved out-of-sample volatility forecasts obtained from the models that account for the quality of policy signals also helps typical mean-variance investors achieve improved economic outcomes captured by higher certainty equivalent returns and Sharpe ratios. Although our results indicate clear distinctions between the U.S. and U.K. stock markets in terms of how policy signals are processed by market participants, they highlight the role of the quality of policy signals as a driver of volatility forecasts with significant economic implications.