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Time-varying variance and skewness in realized volatility measures

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  • Opschoor, Anne
  • Lucas, André

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 such as long-memory-type persistence and large incidental observations. Using a broad range of 89 US stocks across different sectors over 2001–2019, we show that these 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.

Suggested Citation

  • Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.
    • Handle: RePEc:eee:intfor:v:39:y:2023:i:2:p:827-840
    DOI: 10.1016/j.ijforecast.2022.02.009
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