Time-varying variance and skewness in realized volatility measures
Tinbergen Institute Discussion Paper 2019-051/IV
33 Pages Posted: 5 Aug 2019 Last revised: 1 Mar 2022
Date Written: July 23, 2019
Abstract
We propose new empirical models to capture the dynamics of the variance and skewness in realized volatility measures. We find that time-variation in variance and skewness of realized measures is a key empirical feature, even after accounting for well- known stylized facts of realized measures such as long-memory-type persistence and incidental large observations. Using a broad range of 89 U.S. stocks across different sectors over the period 2001-2019, we show that these phenomena are not incidental phenomena of a few stocks, but are widely shared. Accounting for dynamics in the variance and skewness of realized measures results in significantly better in-sample fit and out-of-sample unconditional density and quantile forecasts.
Keywords: realized kernel, heavy tails, F distribution, time-varying shape-parameter, Vol-of-Vol, score-driven dynamics
JEL Classification: C32, C58
Suggested Citation: Suggested Citation