Quantile-based GARCH-MIDAS: Estimating value-at-risk using mixed-frequency information

Finance Research Letters（2021）

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摘要

•We propose a semi-parametric QR-GARCH-MIDAS model to estimate value at risk.•QR-GARCH-MIDAS model is an extension of CAViaR model towards mixed-frequency modeling.•We employ an error bootstrapping method to obtain the p-values of model coefficients.•Evidences indicate it can improve the predictive accuracy of crude oil market risk.

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关键词

Quantile regression,GARCH-MIDAS,Value-at-risk forecast,Error bootstrapping method

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