RETRACTED ARTICLE: Optimizing Stock Portfolio Performance with a Combined RG1-TOPSIS Model: Insights from the Chinese Market

YingShuang Tan (), Wanshuo Yang (), Sid Suntrayuth (), Xin Yu (), Stavros Sindakis () and Saloome Showkat ()
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YingShuang Tan: Chongqing University
Wanshuo Yang: Chongqing University
Sid Suntrayuth: International College, National Institute of Development Administration
Xin Yu: International College, National Institute of Development Administration
Stavros Sindakis: Chongqing Technology and Business University
Saloome Showkat: Institute of Strategy, Entrepreneurship and Education for Growth

Journal of the Knowledge Economy, 2024, vol. 15, issue 2, No 155, 9029-9052

Abstract: Abstract Quantitative investment has gained popularity in the global financial market, and China is no exception. However, existing quantitative stock selection methods have several limitations that restrict their effectiveness. This study proposes a novel approach called the regression corrected G1-TOPSIS (RG1-TOPSIS) method to address these shortcomings. This method combines the G1 and regression methods to objectively assign weights to each factor in multi-factor stock selection. Subsequently, a scoring method is employed to comprehensively rank stocks based on the derived weighting results. Lastly, utilizing the closeness metric, the G1 algorithm is applied to optimize fund allocation within the investment portfolio. We empirically apply this proposed method to stocks in the A-share market of the Shanghai Stock Exchange, covering the period from July 1, 2012, to June 30, 2022. We then compare the obtained results with the market index. Our back-testing results demonstrate that the rate of return (ROR) achieved by our stock selection model significantly surpasses that of the market index. Furthermore, our fund allocation method proves to be more suitable in bear markets. The comprehensive set of investment models we present showcases a high investment value, thereby establishing the effectiveness of this method in the Chinese stock market.

Keywords: Quantitative stock selection; TOPSIS; RG1 weighting method (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13132-023-01438-y

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