Advances in variance analysis permit the splitting of the total quadratic variation of a jump-diffusion process into upside and downside components. Recent studies establish that this decomposition enhances volatility predictions, and highlight the upside/downside variance spread as a driver of...

The horizon effect in the long-run predictive relationship between market excess return and historical market variance is investigated. To this end, the asymptotic multivariate distribution of the term structure of risk-return trade-offs is derived, accounting for short- and long-memory in the...

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...