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Backtesting VaR under the COVID-19 sudden changes in volatility

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  • Castillo, Brenda
  • León, Ángel
  • Ñíguez, Trino-Manuel

Abstract

We analyze the impact of the COVID-19 pandemic on the conditional variance of stock returns. We look at this effect from a global perspective, so we employ series of major stock market and sector indices. We use the Hansen’s Skewed-t distribution with EGARCH extended to control for sudden changes in volatility. We oversee the COVID-19 effect on measures of downside risk such as the Value-at-Risk. Our results show that there is a significant sudden shift up in the return distribution variance post the announcement of the pandemic, which must be explained properly to obtain reliable measures for financial risk management.

Suggested Citation

  • Castillo, Brenda & León, Ángel & Ñíguez, Trino-Manuel, 2021. "Backtesting VaR under the COVID-19 sudden changes in volatility," Finance Research Letters, Elsevier, vol. 43(C).
    • Handle: RePEc:eee:finlet:v:43:y:2021:i:c:s1544612321001057
    DOI: 10.1016/j.frl.2021.102024
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    2. Di, Michael & Xu, Ke, 2022. "COVID-19 vaccine and post-pandemic recovery: Evidence from Bitcoin cross-asset implied volatility spillover," Finance Research Letters, Elsevier, vol. 50(C).

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    More about this item

    Keywords

    Backtesting; EGARCH; Monte Carlo; Skewed-t; Value-at-Risk;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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