Prediction accuracy of volatility using the score-driven Meixner distribution: an application to the Dow Jones

Szabolcs Blazsek and Adrian Licht

Applied Economics Letters, 2022, vol. 29, issue 2, 111-117

Abstract: The score-driven QAR-EGARCH-M (quasi-autoregressive, exponential generalized autoregressive conditional heteroscedasticity-in-mean) model using the Meixner distribution is introduced to improve the prediction accuracy of GARCH. QAR-EGARCH-M extends the recent EGARCH-M model in a statistically innovative way because a new score-driven filter is included in the risk premium. Volatility forecasts of QAR-EGARCH-M, EGARCH-M, and GARCH, all with leverage effects, are compared for the Dow Jones Industrial Average (DJIA). QAR-EGARCH-M is superior to EGARCH-M and GARCH, which is relevant for DJIA options investors at Chicago Mercantile Exchange Globex and Chicago Board Options Exchange.

Date: 2022
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DOI: 10.1080/13504851.2020.1859445

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