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Identifying the number of factors using a white noise test

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  • Li, Shuangbo
  • Zhang, Li-Xin

Abstract

We propose a new method to estimate the number of factors in a factor model using a new test for vector white noise for high-dimensional cases. We provide the theoretical basis for this method, and the simulation results indicate that the present method outperforms previous methods in some finite sample cases.

Suggested Citation

  • Li, Shuangbo & Zhang, Li-Xin, 2019. "Identifying the number of factors using a white noise test," Statistics & Probability Letters, Elsevier, vol. 152(C), pages 92-99.
    • Handle: RePEc:eee:stapro:v:152:y:2019:i:c:p:92-99
    DOI: 10.1016/j.spl.2019.04.011
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    References listed on IDEAS

    as
    1. Jinyuan Chang & Qiwei Yao & Wen Zhou, 2017. "Erratum: Testing for high-dimensional white noise using maximum cross-correlations," Biometrika, Biometrika Trust, vol. 104(1), pages 2-2.
    2. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    3. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    4. Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2012. "Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors," Papers 1212.6906, arXiv.org, revised Jan 2018.
    5. Lam, Clifford & Yao, Qiwei, 2012. "Factor modeling for high-dimensional time series: inference for the number of factors," LSE Research Online Documents on Economics 45684, London School of Economics and Political Science, LSE Library.
    6. Jinyuan Chang & Qiwei Yao & Wen Zhou, 2017. "Testing for high-dimensional white noise using maximum cross-correlations," Biometrika, Biometrika Trust, vol. 104(1), pages 111-127.
    7. Chang, Jinyuan & Yao, Qiwei & Zhou, Wen, 2017. "Testing for high-dimensional white noise using maximum cross-correlations," LSE Research Online Documents on Economics 68531, London School of Economics and Political Science, LSE Library.
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