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<p>This paper examines how a change in health policy uncertainty affects US industry returns using monthly data from January 1985 to September 2020. We employ in-sample and out-of-sample analyses, and we find evidence that 25 out of 49 considered industries are predictable during the health crisis periods, including severe acute respiratory syndrome and the ongoing coronavirus pandemic. The out-of-sample tests corroborate the evidence for the in-sample predictability. Furthermore, using a mean–variance utility function-based trading strategy, we observe that investors can use this simple tool for their trading strategies and make profits from 2.99 to 11.44% per annum. Our findings are robust after accounting for different business cycles, macroeconomic factor effects, the fluctuation in economic policy uncertainty, and different pandemic phases. These results complement the existing literature on industry return predictability and have potential implications for asset pricing and risk management.</p>

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Industry return predictability using health policy uncertainty

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月10日

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  • Thach Pham,
  • Deepa Bannigidadmath,
  • Robert Powell

摘要

This paper examines how a change in health policy uncertainty affects US industry returns using monthly data from January 1985 to September 2020. We employ in-sample and out-of-sample analyses, and we find evidence that 25 out of 49 considered industries are predictable during the health crisis periods, including severe acute respiratory syndrome and the ongoing coronavirus pandemic. The out-of-sample tests corroborate the evidence for the in-sample predictability. Furthermore, using a mean–variance utility function-based trading strategy, we observe that investors can use this simple tool for their trading strategies and make profits from 2.99 to 11.44% per annum. Our findings are robust after accounting for different business cycles, macroeconomic factor effects, the fluctuation in economic policy uncertainty, and different pandemic phases. These results complement the existing literature on industry return predictability and have potential implications for asset pricing and risk management.