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Do Winners Perform Better Than Losers? A Stochastic Dominance Approach

In: Advances In Quantitative Analysis Of Finance And Accounting

Author

Listed:
  • Wing-Keung Wong

    (National University of Singapore, Singapore)

  • Howard E. Thompson

    (University of Wisconsin-Madison, USA)

  • Steven X. Wei

    (The Hong Kong Polytechnic University, Hong Kong, China)

  • Ying-Foon Chow

    (Chinese University of Hong Kong, Hong Kong, China)

Abstract

This paper offers an alternative view supporting the risk-based explanation of the momentum effect. Using stochastic dominance criteria, we find that the winners portfolio and the losers portfolio do not dominate each other. In general, the winners portfolio dominates at the right-hand side of the distribution of returns while the losers portfolio dominates at the left-hand side of the distribution. Our empirical results imply that the momentum profits provide neither an arbitrage opportunity nor a welfare improvement for rational investors ex ante. We interpret the evidence as follows: momentum profits are consistent with the notion of market rationality and market efficiency and are likely to be explained by omitted risk factors. Our findings also suggest that one possible reason why some investors prefer losers is because of less downside risk.

Suggested Citation

  • Wing-Keung Wong & Howard E. Thompson & Steven X. Wei & Ying-Foon Chow, 2006. "Do Winners Perform Better Than Losers? A Stochastic Dominance Approach," World Scientific Book Chapters, in: Cheng-Few Lee (ed.), Advances In Quantitative Analysis Of Finance And Accounting, chapter 10, pages 219-254, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812772824_0010
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    Citations

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    Cited by:

    1. Nguyen Huu Hau & Tran Trung Tinh & Hoa Anh Tuong & Wing-Keung Wong, 2020. "Review of Matrix Theory with Applications in Education and Decision Sciences," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(1), pages 28-69, March.
    2. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," JRFM, MDPI, vol. 11(1), pages 1-29, March.
    3. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, And Big Data: Connections," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 36-94, December.
    4. Kim-Hung Pho & Tuan-Kiet Tran & Thi Diem-Chinh Ho & Wing-Keung Wong, 2019. "Optimal Solution Techniques in Decision Sciences A Review," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(1), pages 114-161, March.
    5. Chang, C-L. & McAleer, M.J. & Wong, W.-K., 2018. "Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections," Econometric Institute Research Papers 18-024/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Eric S. Fung & Kin Lam & Tak-Kuen Siu & Wing-Keung Wong, 2011. "A Pseudo-Bayesian Model for Stock Returns In Financial Crises," JRFM, MDPI, vol. 4(1), pages 1-31, December.
    7. Thomas Clauss & Ricarda B. Bouncken & Sven Laudien & Sascha Kraus, 2019. "BUSINESS MODEL RECONFIGURATION AND INNOVATION IN SMEs: A MIXED-METHOD ANALYSIS FROM THE ELECTRONICS INDUSTRY," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 24(02), pages 1-35, April.
    8. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Market Efficiency of Oil Spot and Futures: A Stochastic Dominance Approach," CIRJE F-Series CIRJE-F-705, CIRJE, Faculty of Economics, University of Tokyo.
    9. Fathi Abid & Pui Lam Leung & Mourad Mroua & Wing Keung Wong, 2014. "International Diversification Versus Domestic Diversification: Mean-Variance Portfolio Optimization and Stochastic Dominance Approaches," JRFM, MDPI, vol. 7(2), pages 1-22, May.
    10. Kim-Hung Pho & Thi Diem-Chinh Ho & Tuan-Kiet Tran & Wing-Keung Wong, 2019. "Moment Generating Function, Expectation And Variance Of Ubiquitous Distributions With Applications In Decision Sciences: A Review," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(2), pages 65-150, June.
    11. Hooi Lean & Kok Phoon & Wing-Keung Wong, 2013. "Stochastic dominance analysis of CTA funds," Review of Quantitative Finance and Accounting, Springer, vol. 40(1), pages 155-170, January.
    12. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 11(1), pages 1-29, March.
    13. Lam, Kin & Liu, Taisheng & Wong, Wing-Keung, 2010. "A pseudo-Bayesian model in financial decision making with implications to market volatility, under- and overreaction," European Journal of Operational Research, Elsevier, vol. 203(1), pages 166-175, May.

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