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Balanced predictive regressions

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  • Ren, Yu
  • Tu, Yundong
  • Yi, Yanping

Abstract

In a predictive regression, a less persistent return series is regressed on the first lag of some highly persistent predictors. Therefore, predictability could often be missed due to the persistence imbalance. The aim of this paper is to balance the predictive regression by augmenting it with an additional lag of the predictors. This second lag generally reduces the persistence level on the right-hand side of the equation to achieve balance. We then propose a simple test procedure for univariate and multivariate predictive regressions, based on least squares estimation. Empirically, we reexamine the popular predictors in the literature and find quite different results.

Suggested Citation

  • Ren, Yu & Tu, Yundong & Yi, Yanping, 2019. "Balanced predictive regressions," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 118-142.
    • Handle: RePEc:eee:empfin:v:54:y:2019:i:c:p:118-142
    DOI: 10.1016/j.jempfin.2019.09.001
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    Cited by:

    1. Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
    2. Yang, Bingduo & Long, Wei & Yang, Zihui, 2022. "Testing predictability of stock returns under possible bubbles," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 246-260.
    3. Lin, Yingqian & Tu, Yundong, 2020. "Robust inference for spurious regressions and cointegrations involving processes moderately deviated from a unit root," Journal of Econometrics, Elsevier, vol. 219(1), pages 52-65.
    4. Un, Kuok Sin & Ausloos, Marcel, 2022. "Equity premium prediction: Taking into account the role of long, even asymmetric, swings in stock market behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    5. Tu, Yundong & Wang, Ying, 2022. "Spurious functional-coefficient regression models and robust inference with marginal integration," Journal of Econometrics, Elsevier, vol. 229(2), pages 396-421.
    6. Tu, Yundong & Liang, Han-Ying & Wang, Qiying, 2022. "Nonparametric inference for quantile cointegrations with stationary covariates," Journal of Econometrics, Elsevier, vol. 230(2), pages 453-482.

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    More about this item

    Keywords

    Nearly integrated process; Predictive regression; Predictability; Stock return;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • 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
    • 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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