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Managing downside risk of low-risk anomaly portfolios

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  • Kim, Hyuksoo
  • Kim, Saejoon

Abstract

In this paper, we present a novel risk-scaling strategy based on a measure of downside risk and investigate its performance on underlying portfolios that are formed on low-risk anomaly. The downside risk-scaling strategy addresses two challenges of the volatility-scaling strategy, namely, underestimation of and indirect management of downside risk. We demonstrate that our downside risk-scaled strategy improves the unscaled underlying low-risk anomaly strategy as well as outperforms volatility-scaled strategy in terms of risk-adjusted return and various performance metrics that are related to downside events.

Suggested Citation

  • Kim, Hyuksoo & Kim, Saejoon, 2022. "Managing downside risk of low-risk anomaly portfolios," Finance Research Letters, Elsevier, vol. 46(PB).
    • Handle: RePEc:eee:finlet:v:46:y:2022:i:pb:s1544612321003883
    DOI: 10.1016/j.frl.2021.102388
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    References listed on IDEAS

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    1. Paul Schneider & Christian Wagner & Josef Zechner, 2020. "Low‐Risk Anomalies?," Journal of Finance, American Finance Association, vol. 75(5), pages 2673-2718, October.
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    Cited by:

    1. Yun, Jaesun & Kwon, Kyung Yoon, 2023. "Biweekly performance of low-risk anomalies over the FOMC cycle," Finance Research Letters, Elsevier, vol. 58(PC).

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    More about this item

    Keywords

    Conditional value-at-risk; Value-at-risk; Volatility scaling; Betting against beta;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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