This paper introduces a no-arbitrage framework to assess how macroeconomic factors help explain the risk-premium agents require to bear the risk of fluctuations in stock market volatility. We develop a model in which stock volatility and volatility risk-premia are stochastic and derive...

This paper introduces a no-arbitrage framework to assess how macroeconomic factors help explain the risk-premium agents require to bear the risk of fluctuations in stock market volatility. We develop a model in which return volatility and volatility risk-premia are stochastic and derive...

We investigate how individual equity prices react to stock specific expected jump components. We find that a portfolio buying stocks with negative expected jump component and selling stocks with positive expected jump component earns significant returns, equal to 51 basis points per month.The...

Many asset pricing theories treat the cross-section of returns volatility and correlations as two intimately related quantities driven by common factors, which hinders achieving a neat definition of a correlation premium. We formulate a model without factors, but with a continuum of securities...

In this paper, we use factor-augmented HAR-type models to predict the daily integrated volatility of asset returns. Our approach is based on a proposed two-step dimension reduction procedure designed to extract latent common volatility factors from a large dimensional and high-frequency returns...

In this paper, we review econometric methodology that is used to test for jumps and to decompose realized volatility into continuous and jump components. In order to illustrate how to implement the methods discussed, we also present the results of an empirical analysis in which we separate...