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Discovering optimal weights in weighted-scoring stock-picking models: a mixture design approach

Author

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  • I-Cheng Yeh

    (Tamkang University)

  • Yi-Cheng Liu

    (Tamkang University)

Abstract

Certain literature that constructs a multifactor stock selection model adopted a weighted-scoring approach despite its three shortcomings. First, it cannot effectively identify the connection between the weights of stock-picking concepts and portfolio performances. Second, it cannot provide stock-picking concepts’ optimal combination of weights. Third, it cannot meet various investor preferences. Thus, this study employs a mixture experimental design to determine the weights of stock-picking concepts, collect portfolio performance data, and construct performance prediction models based on the weights of stock-picking concepts. Furthermore, these performance prediction models and optimization techniques are employed to discover stock-picking concepts’ optimal combination of weights that meet investor preferences. The samples consist of stocks listed on the Taiwan stock market. The modeling and testing periods were 1997–2008 and 2009–2015, respectively. Empirical evidence showed (1) that our methodology is robust in predicting performance accurately, (2) that it can identify significant interactions between stock-picking concepts’ weights, and (3) that which their optimal combination should be. This combination of weights can form stock portfolios with the best performances that can meet investor preferences. Thus, our methodology can fill the three drawbacks of the classical weighted-scoring approach.

Suggested Citation

  • I-Cheng Yeh & Yi-Cheng Liu, 2020. "Discovering optimal weights in weighted-scoring stock-picking models: a mixture design approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-28, December.
    • Handle: RePEc:spr:fininn:v:6:y:2020:i:1:d:10.1186_s40854-020-00209-x
    DOI: 10.1186/s40854-020-00209-x
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    1. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    2. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    3. Piotroski, JD, 2000. "Value investing: The use of historical financial statement information to separate winners from losers," Journal of Accounting Research, Wiley Blackwell, vol. 38, pages 1-41.
    4. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
    5. van der Hart, Jaap & de Zwart, Gerben & van Dijk, Dick, 2005. "The success of stock selection strategies in emerging markets: Is it risk or behavioral bias?," Emerging Markets Review, Elsevier, vol. 6(3), pages 238-262, September.
    6. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
    7. Kent Daniel & Lira Mota & Simon Rottke & Tano Santos, 2020. "The Cross-Section of Risk and Returns," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 1927-1979.
    8. Jarno Tikkanen & Janne Äijö, 2018. "Does the F-score improve the performance of different value investment strategies in Europe?," Journal of Asset Management, Palgrave Macmillan, vol. 19(7), pages 495-506, December.
    9. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    10. Richardson, Scott & Tuna, Irem & Wysocki, Peter, 2010. "Accounting anomalies and fundamental analysis: A review of recent research advances," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 410-454, December.
    11. Clifford S. Asness & Tobias J. Moskowitz & Lasse Heje Pedersen, 2013. "Value and Momentum Everywhere," Journal of Finance, American Finance Association, vol. 68(3), pages 929-985, June.
    12. I. Roko & M. Gilli, 2008. "Using economic and financial information for stock selection," Computational Management Science, Springer, vol. 5(4), pages 317-335, October.
    13. Kent Daniel & Lira Mota & Simon Rottke & Tano Santos & Andrew KarolyiEditor, 2020. "The Cross-Section of Risk and Returns," Review of Finance, European Finance Association, vol. 33(5), pages 1927-1979.
    14. Durán-Vázquez, Rocío & Lorenzo-Valdés, Arturo & Castillo-Ramírez, Claudia, 2014. "Effectiveness of corporate finance valuation methods: Piotroski score in an Ohlson model: the case of Mexico," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 19(37), pages 104-107.
    15. Noma, Mikiharu & 野間, 幹晴, 2010. "Value Investing and Financial Statement Analysis," Hitotsubashi Journal of commerce and management, Hitotsubashi University, vol. 44(1), pages 29-46, October.
    16. Wen, Fenghua & Xu, Longhao & Ouyang, Guangda & Kou, Gang, 2019. "Retail investor attention and stock price crash risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 65(C).
    17. Fama, Eugene F. & French, Kenneth R., 2012. "Size, value, and momentum in international stock returns," Journal of Financial Economics, Elsevier, vol. 105(3), pages 457-472.
    18. Sohyung Kim & Cheol Lee, 2014. "Implementability of Trading Strategies Based on Accounting Information: Piotroski (2000) Revisited," European Accounting Review, Taylor & Francis Journals, vol. 23(4), pages 553-558, December.
    19. van der Hart, Jaap & Slagter, Erica & van Dijk, Dick, 2003. "Stock selection strategies in emerging markets," Journal of Empirical Finance, Elsevier, vol. 10(1-2), pages 105-132, February.
    20. Derick Kong & Cheng-Ping Lin & I-Cheng Yeh & Wei Chang, 2019. "Building growth and value hybrid valuation model with errors-in-variables regression," Applied Economics Letters, Taylor & Francis Journals, vol. 26(5), pages 370-386, March.
    21. Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
    22. I-Cheng Yeh & Tzu-Kuang Hsu, 2011. "Growth Value Two-Factor Model," Journal of Asset Management, Palgrave Macmillan, vol. 11(6), pages 435-451, February.
    23. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
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    Cited by:

    1. I-Cheng Yeh, 2023. "Synergy frontier of multi-factor stock selection model," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 445-480, March.

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