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A unified approach to standardized-residuals-based correlation tests for GARCH-type models

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  • Yi-Ting Chen

    (Institute of Economics, Academia Sinica, Taipei, Taiwan)

Abstract

In this paper, we propose a unified approach to generating standardized-residuals-based correlation tests for checking GARCH-type models. This approach is valid in the presence of estimation uncertainty, is robust to various standardized error distributions, and is applicable to testing various types of misspecifications. By using this approach, we also propose a class of power-transformed-series (PTS) correlation tests that provides certain robustifications and power extensions to the Box-Pierce, McLeod-Li, Li-Mak, and Berkes-Horváth-Kokoszka tests in diagnosing GARCH-type models. Our simulation and empirical example show that the PTS correlation tests outperform these existing autocorrelation tests in financial time series analysis. Copyright © 2008 John Wiley & Sons, Ltd.

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  • Yi-Ting Chen, 2008. "A unified approach to standardized-residuals-based correlation tests for GARCH-type models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 111-133.
    • Handle: RePEc:jae:japmet:v:23:y:2008:i:1:p:111-133
    DOI: 10.1002/jae.985
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    4. John C. Nankervis & Nathan E. Savin, 2012. "Testing for uncorrelated errors in ARMA models: non‐standard Andrews‐Ploberger tests," Econometrics Journal, Royal Economic Society, vol. 15(3), pages 516-534, October.
    5. Chen, Yi-Ting, 2012. "A simple approach to standardized-residuals-based higher-moment tests," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 427-453.

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