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When Do Stop-Loss Rules Stop Losses?

Author

Listed:
  • Kaminski, Kathryn

    (Risk & Portfolio Management)

  • Lo, Andrew W.

    (MIT Sloan School of Management)

Abstract
Stop-loss rules-predetermined policies that reduce a portfolio's exposure after reaching a certain threshold of cumulative losses-are commonly used by retail and institutional in- vestors to manage the risks of their investments, but have also been viewed with some skep- ticism by critics who question their e±cacy. In this paper, we develop a simple framework for measuring the impact of stop-loss rules on the expected return and volatility of an arbitrary portfolio strategy, and derive conditions under which stop-loss rules add or subtract value to that portfolio strategy. We show that under the Random Walk Hypothesis, simple 0/1 stop-loss rules always decrease a strategy's expected return, but in the presence of momen- tum, stop-loss rules can add value. To illustrate the practical relevance of our framework, we provide an empirical analysis of a stop-loss policy applied to a buy-and-hold strategy in U.S. equities, where the stop-loss asset is U.S. long-term government bonds. Using monthly returns data from January 1950 to December 2004, we find that certain stop-loss rules add 50 to 100 basis points per month to the buy-and-hold portfolio during stop-out periods. By computing performance measures for several price processes, including a new regime- switching model that implies periodic "flights-to-quality", we provide a possible explanation for our empirical results and connections to the behavioral finance literature.

Suggested Citation

  • Kaminski, Kathryn & Lo, Andrew W., 2008. "When Do Stop-Loss Rules Stop Losses?," SIFR Research Report Series 63, Institute for Financial Research.
    • Handle: RePEc:hhs:sifrwp:0063
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    Cited by:

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    2. Hwang, Yoontae & Park, Junpyo & Lee, Yongjae & Lim, Dong-Young, 2023. "Stop-loss adjusted labels for machine learning-based trading of risky assets," Finance Research Letters, Elsevier, vol. 58(PA).
    3. Žikica Lukić & Bojana Milošević, 2024. "A novel two-sample test within the space of symmetric positive definite matrix distributions and its application in finance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(5), pages 797-820, October.
    4. Białkowski, Jędrzej, 2020. "Cryptocurrencies in institutional investors’ portfolios: Evidence from industry stop-loss rules," Economics Letters, Elsevier, vol. 191(C).
    5. Yang, Chunpeng & Zhang, Zhanpei, 2021. "Realization utility with stop-loss strategy," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 261-275.
    6. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    7. Ardia, David & Boudt, Kris & Hartmann, Stefan & Nguyen, Giang, 2022. "Properties of the Margrabe Best-of-two strategy to tactical asset allocation," International Review of Financial Analysis, Elsevier, vol. 81(C).
    8. Gregory Gadzinski & Markus Schuller & Shabnam Mousavi, 2022. "Long-lasting heuristics principles for efficient investment decisions," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 14(4), pages 570-583, March.
    9. Edmond Lezmi & Jules Roche & Thierry Roncalli & Jiali Xu, 2020. "Improving the Robustness of Trading Strategy Backtesting with Boltzmann Machines and Generative Adversarial Networks," Papers 2007.04838, arXiv.org.
    10. Chun-Hao Chen & Yu-Hsuan Chen & Vicente Garcia Diaz & Jerry Chun-Wei Lin, 2023. "RETRACTED ARTICLE: An intelligent trading mechanism based on the group trading strategy portfolio to reduce massive loss by the grouping genetic algorithm," Electronic Commerce Research, Springer, vol. 23(1), pages 3-42, March.
    11. Bochuan Dai & Ben R. Marshall & Nhut H. Nguyen & Nuttawat Visaltanachoti, 2021. "Risk reduction using trailing stop‐loss rules," International Review of Finance, International Review of Finance Ltd., vol. 21(4), pages 1334-1352, December.
    12. Hong, Xin & Pang, Ningjing & Wang, Zhibin, 2022. "Stop-loss early termination clause and hedge fund performance," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).
    13. Rui Wang, 2021. "Discriminating modelling approaches for Point in Time Economic Scenario Generation," Papers 2108.08818, arXiv.org.
    14. Jessica James & Louis Yang, 2010. "Stop-losses, maximum drawdown-at-risk and replicating financial time series with the stationary bootstrap," Quantitative Finance, Taylor & Francis Journals, vol. 10(1), pages 1-12.
    15. Sadaqat, Mohsin & Butt, Hilal Anwar, 2023. "Stop-loss rules and momentum payoffs in cryptocurrencies," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    16. Dimitrios Vezeris & Themistoklis Kyrgos & Christos Schinas, 2018. "Take Profit and Stop Loss Trading Strategies Comparison in Combination with an MACD Trading System," JRFM, MDPI, vol. 11(3), pages 1-23, September.
    17. Henderson, Vicky & Hobson, David & Tse, Alex S.L., 2018. "Probability weighting, stop-loss and the disposition effect," Journal of Economic Theory, Elsevier, vol. 178(C), pages 360-397.
    18. Gerritsen, Dirk F., 2016. "Are chartists artists? The determinants and profitability of recommendations based on technical analysis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 179-196.

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    More about this item

    Keywords

    Investments; Portfolio Management; Risk Management; Performance Attribution; Behavioral Finance;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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