We propose optimal mean-variance dynamic hedging strategies in discrete time under a multivariate Gaussian regime-switching model. The methodology, which also performs pricing, is robust to time-varying and clustering risk observed in financial time series. As such, it overcomes the main...

We provide a multi-horizon characterization of the strength of the relationship between market realized variance components, namely continuous volatility and jump, and future market excess return. Building on quadratic variation theory, we find that continuous volatility is a key driver of...

Realized variance can be broken down into continuous volatility and jumps. We show that these two components have very different predictive powers on future long-term excess stock market returns. While continuous volatility is a key driver of medium to long-term risk-return relationships, jumps...