Dynamic VaR forecasts using conditional Pearson type IV distribution

Wei Kuang

Journal of Forecasting, 2021, vol. 40, issue 3, 500-511

Abstract: This paper generalizes the exponentially weighted maximum likelihood (EWML) procedure to account for volatility and higher moment dynamics of the returns distribution. Prior research uses EWML to forecast value at risk (VaR) by assuming daily equity returns following a scaled t distribution. This approach does not capture the significant degree of skewness inherent in the data, which potentially leads to an underestimation of VaR. We employ the EWML procedure to estimate a time‐varying Pearson IV distribution. Our results show that VaR forecasts based on Pearson IV using the EWML procedure are generally more accurate than those generated by scaled t and generalized autoregressive conditional heteroskedasticity (GARCH)‐type models, particularly for assets with high leptokurtosis and negative skewness.

Date: 2021
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https://doi.org/10.1002/for.2726

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:40:y:2021:i:3:p:500-511

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