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Do realized higher moments have information content? - VaR forecasting based on the realized GARCH-RSRK model

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  • Wang, Tianyi
  • Liang, Fang
  • Huang, Zhuo
  • Yan, Hong

Abstract

In this paper, we develop a new model, the Realized GARCH-RSRK, to determine the time-varying distribution of financial returns with realized higher moments. Based on Gram-Charlier expansion (GCE) density, we first explicitly link the expansion parameters with moments that are calculated based on intraday returns using our new model. Then, the Cornish-Fisher expansion is applied to forecast Value-at-Risk (VaR) with estimated moments to demonstrate the economic significance of this new model. Compared with the daily-return-based dynamic higher moments models, the inclusion of realized higher moments significantly improves this model's ability to forecast extreme tails. The empirical results indicate that this new model outperforms the benchmark models when forecasting extreme VaR. In addition, we provide a formula to correct the moments associated with the commonly used squared transformation of GCE. Our empirical evidence highlights the importance of using corrected moments in VaR forecasting.

Suggested Citation

  • Wang, Tianyi & Liang, Fang & Huang, Zhuo & Yan, Hong, 2022. "Do realized higher moments have information content? - VaR forecasting based on the realized GARCH-RSRK model," Economic Modelling, Elsevier, vol. 109(C).
    • Handle: RePEc:eee:ecmode:v:109:y:2022:i:c:s026499932200027x
    DOI: 10.1016/j.econmod.2022.105781
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    More about this item

    Keywords

    Realized GARCH-RSRK; Realized higher moments; Realized GARCH; Gram-Charlier expansion; 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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