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Unified Tests for a Dynamic Predictive Regression

Author

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  • Bingduo Yang
  • Xiaohui Liu
  • Liang Peng
  • Zongwu Cai

Abstract

Testing for predictability of asset returns has been a long history in economics and finance. Recently, based on a simple predictive regression, Kostakis, Magdalinos, and Stamatogiannis derived a Wald type test based on the context of the extended instrumental variable (IVX) methodology for testing predictability of stock returns, and Demetrescu showed that the local power of the standard IVX-based test could be improved for some range of alternative hypotheses and the tuning parameter when a lagged predicted variable is added to the predictive regression on purpose, which poses an important question on whether the predictive model should include a lagged predicted variable. This article proposes novel robust procedures for testing both the existence of a lagged predicted variable and the predictability of asset returns regardless of regressors being stationary or nearly integrated or unit root and the AR model for regressors with or without an intercept. A simulation study confirms the good finite sample performance of the proposed tests before illustrating their practical usefulness in analyzing real financial datasets.

Suggested Citation

  • Bingduo Yang & Xiaohui Liu & Liang Peng & Zongwu Cai, 2021. "Unified Tests for a Dynamic Predictive Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 684-699, July.
    • Handle: RePEc:taf:jnlbes:v:39:y:2021:i:3:p:684-699
    DOI: 10.1080/07350015.2020.1714632
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    Citations

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    Cited by:

    1. Christis Katsouris, 2023. "Unified Inference for Dynamic Quantile Predictive Regression," Papers 2309.14160, arXiv.org, revised Nov 2023.
    2. Yijie Fei & Yiu Lim Lui & Jun Yu, 2024. "Testing Predictability in the Presence of Persistent Errors," Working Papers 202401, University of Macau, Faculty of Business Administration.
    3. Zhan Gao & Ji Hyung Lee & Ziwei Mei & Zhentao Shi, 2024. "On LASSO Inference for High Dimensional Predictive Regression," Papers 2409.10030, arXiv.org.
    4. Xiaosai Liao & Xinjue Li & Qingliang Fan, 2024. "Robust Inference for Multiple Predictive Regressions with an Application on Bond Risk Premia," Papers 2401.01064, arXiv.org.
    5. Yannick Hoga, 2024. "Persistence-Robust Break Detection in Predictive Quantile and CoVaR Regressions," Papers 2410.05861, arXiv.org.
    6. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    7. Fukang Zhu & Mengya Liu & Shiqing Ling & Zongwu Cai, 2020. "Testing for Structural Change of Predictive Regression Model to Threshold Predictive Regression Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202021, University of Kansas, Department of Economics, revised Dec 2020.
    8. Tu, Yundong & Xie, Xinling, 2023. "Penetrating sporadic return predictability," Journal of Econometrics, Elsevier, vol. 237(1).
    9. Cai, Zongwu & Chen, Haiqiang & Liao, Xiaosai, 2023. "A new robust inference for predictive quantile regression," Journal of Econometrics, Elsevier, vol. 234(1), pages 227-250.

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