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<p>This paper provides a robust test of predictability under the predictive regression model with possible heavy-tailed innovations assumption, in which the predictive variable is persistent and its innovations are highly correlated with returns. To this end, we propose a robust test which can capture empirical phenomena such as heavy tails, stationary, and local to unity. Moreover, we develop related asymptotic results without the second-moment assumption between the predictive variable and returns. To make the proposed test reasonable, we propose a <i>generalized correlation</i> and provide theoretical support. To illustrate the applicability of the test, we perform a simulation study for the impact of heavy-tailed innovations on predictability, as well as direct and/or indirect implementation of heavy-tailed innovations to predictability via the unit root phenomenon. Finally, we provide an empirical study for further illustration, to which the proposed test is applied to a U.S. equity data set.</p>

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Robust tests of stock return predictability under heavy-tailed innovations

  • 期刊论文

  • 发表日期：

    2025年3月25日

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  • Hsin-Chieh Wong,
  • Meng-Hua Chung,
  • Cheng-Der Fuh,
  • Tian-xiao Pang

摘要

This paper provides a robust test of predictability under the predictive regression model with possible heavy-tailed innovations assumption, in which the predictive variable is persistent and its innovations are highly correlated with returns. To this end, we propose a robust test which can capture empirical phenomena such as heavy tails, stationary, and local to unity. Moreover, we develop related asymptotic results without the second-moment assumption between the predictive variable and returns. To make the proposed test reasonable, we propose a generalized correlation and provide theoretical support. To illustrate the applicability of the test, we perform a simulation study for the impact of heavy-tailed innovations on predictability, as well as direct and/or indirect implementation of heavy-tailed innovations to predictability via the unit root phenomenon. Finally, we provide an empirical study for further illustration, to which the proposed test is applied to a U.S. equity data set.