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Testing against constant factor loading matrix with large panel high-frequency data

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  • Kong, Xin-Bing
  • Liu, Cheng

Abstract

In this paper, we introduce a nonparametric test against the constancy of the factor loading matrix of a high-dimensional continuous-time factor model using high-frequency data. The central limit theorems on the test statistics with and without perturbation are established under the null hypothesis that the factor loading matrix is constant as time evolves. The tests perform well in size and power. Interestingly, the test statistic without perturbation converges at a rate that depends not only on the sample size but also on the dimension through the cross-sectional dependence of the residual process, which is a distinctive feature that contrasts with the low-dimensional setting. Extensive numerical studies, including Monte Carlo simulations and real data analysis, validate the performance of our test.

Suggested Citation

  • Kong, Xin-Bing & Liu, Cheng, 2018. "Testing against constant factor loading matrix with large panel high-frequency data," Journal of Econometrics, Elsevier, vol. 204(2), pages 301-319.
    • Handle: RePEc:eee:econom:v:204:y:2018:i:2:p:301-319
    DOI: 10.1016/j.jeconom.2018.03.001
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    Cited by:

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    2. Sun, Yucheng & Xu, Wen & Zhang, Chuanhai, 2023. "Identifying latent factors based on high-frequency data," Journal of Econometrics, Elsevier, vol. 233(1), pages 251-270.
    3. Chen, Dachuan & Mykland, Per A. & Zhang, Lan, 2024. "Realized regression with asynchronous and noisy high frequency and high dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).

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    More about this item

    Keywords

    Continuous-time factor model; Factor loading matrix; High dimensional itô process;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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