The short-run impact of investor expectations’ past volatility on current predictions: The case of VIX

Abstract

Understanding the risk premium and its impact on current and expected returns is a critical research problem. The present study contributes to the investigation of risk premium decomposition over short-run periods via two key advancements. First, it presents a model that incorporates past uncertainties regarding investors’ trade outcome expectations into current predictions. This model enables a short-run decomposition of the risk premium. Second, the study examines the relationship between past volatility and current expected trading results for the Chicago Board Options Exchange Volatility Index (VIX) using daily data from January 5, 2016, to January 20, 2023. The findings indicate that current expected losses are influenced by the volatility of previously predicted unfavourable trade outcomes, underscoring the relevance of this study to portfolio management decisions. The parameter that captures this impact exhibits significant time variation. This result remains robust across various specifications of a time-varying parameter model with shrinkage. We further validate this robustness by testing different time frequencies, analysing various types of instruments and markets, and employing an alternative risk estimation method. Ultimately, the findings suggest that proactive stabilisation policies must be implemented to enhance the quality, relevance, and availability of information disseminated by financial asset issuers throughout the market.