Volatility forecasting is crucial for portfolio management, risk management, and pricing of derivative securities. Still, little is known about the accuracy of volatility forecasts and the horizon of volatility predictability. This paper aims to fill these gaps in the literature. We begin this...

The empirical literature has extensively documented several notable features of implied volatility. These features encompass the presence of a smirk shape, a term structure pattern, as well as volatility and skewness risk premia. The theoretical literature suggests that preference-free option...

Recent literature on stock return predictability suggests that it varies substantially across economic states being strongest during bad economic times. In line with this evidence, we document that stock volatility predictability is also state dependent. In particular, using a large data set of...

There is evidence that volatility forecasting models that use intraday data provide better forecast accuracy as compared with that delivered by the models that use daily data. Exactly how much better is still unknown. The present paper fills this gap in the literature and extends previous...

Numerous empirical studies demonstrate the superiority of dynamic strategies with volatility weighting over time mechanism. These strategies control the portfolio risk over time by adjusting the risk exposure according to updated volatility forecasts. Yet, in order to reap all benefits promised...

In this paper we document that at the aggregate stock market level the unexpected volatility is negatively related to expected future returns and positively related to future volatility. We demonstrate how the predictive ability of unexpected volatility can be utilized in dynamic asset...