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Forecasting stock market volatility using implied volatility: evidence from extended realized EGARCH-MIDAS model

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  • Xinyu Wu
  • Xiaona Wang
  • Haiyun Wang

Abstract

This paper extends the realized EGARCH-MIDAS (REGARCH-MIDAS) model to incorporate implied volatility (IV) derived from option prices. The extension allows us to examine the incremental information content of IV for forecasting volatility. An empirical investigation with S&P 500 index shows that IV contains valuable information for forecasting volatility. Our proposed model provides more accurate out-of-sample volatility forecasts compared to the EGARCH, the REGARCH and the REGARCH-MIDAS models as well as the EGARCH-IV and the REGARCH-IV models.

Suggested Citation

  • Xinyu Wu & Xiaona Wang & Haiyun Wang, 2021. "Forecasting stock market volatility using implied volatility: evidence from extended realized EGARCH-MIDAS model," Applied Economics Letters, Taylor & Francis Journals, vol. 28(11), pages 915-920, June.
    • Handle: RePEc:taf:apeclt:v:28:y:2021:i:11:p:915-920
    DOI: 10.1080/13504851.2020.1785617
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    Cited by:

    1. Julien Chevallier & Bilel Sanhaji, 2023. "Jump-Robust Realized-GARCH-MIDAS-X Estimators for Bitcoin and Ethereum Volatility Indices," Stats, MDPI, vol. 6(4), pages 1-32, December.

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