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Multivariate Hyper-Rotated GARCH-BEKK

Author

Listed:
  • Asai Manabu

    (Faculty of Economics, Soka University, Tokyo, Japan)

  • McAleer Michael

    (Department of Finance, Asia University, Taichung City, Taiwan)

Abstract

For large multivariate models of generalized autoregressive conditional heteroskedasticity (GARCH), it is important to reduce the number of parameters to cope with the ‘curse of dimensionality’. Recently, Laurent, Rombouts and Violante (2014 “Multivariate Rotated ARCH Models” Journal of Econometrics 179: 16–30) developed the rotated multivariate GARCH model, which focuses on the parameters for standardized variables. This paper extends the rotated multivariate GARCH model by considering a hyper-rotation, which uses a more flexible structure for the rotation matrix. The paper shows an alternative representation based on a random coefficient vector autoregressive and moving-average (VARMA) process, and provides the regularity conditions for the consistency and asymptotic normality of the quasi-maximum likelihood (QML) estimator for VARMA with hyper-rotated multivariate GARCH. The paper investigates the finite sample properties of the QML estimator for the new model. Empirical results for four exchange rate returns show the new specifications works satisfactory for reducing the number of parameters.

Suggested Citation

  • Asai Manabu & McAleer Michael, 2022. "Multivariate Hyper-Rotated GARCH-BEKK," Journal of Time Series Econometrics, De Gruyter, vol. 14(2), pages 175-198, July.
  • Handle: RePEc:bpj:jtsmet:v:14:y:2022:i:2:p:175-198:n:3
    DOI: 10.1515/jtse-2021-0006
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    Citations

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    Cited by:

    1. Tanin, Tauhidul Islam & Hasanov, Akram Shavkatovich & Shaiban, Mohammed Sharaf Mohsen & Brooks, Robert, 2022. "Risk transmission from the oil market to Islamic and conventional banks in oil-exporting and oil-importing countries," Energy Economics, Elsevier, vol. 115(C).

    More about this item

    Keywords

    rotated BEKK; hyper-rotated BEKK; diagonal BEKK; multivariate GARCH; quasi-maximum likelihood estimation; consistency; asymptotic normality;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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