Fuzzy-Based Stock Selection System through Suitability Index and Position Sizing

With the rapid development of quantitative trading, stock selection is an enduring task, that requires consideration of the characteristic of stocks and investment strategies. Fuzzy-set theory is outstanding in modeling abstract characteristics, which is suitable for building the connection between stocks and strategies. In this paper, we propose a stock selection system (SSS) based on the suitability index (SI) and fuzzy-set theory. SSS utilizes position sizing to extract stock characteristics, SI, which expresses not only the characteristics of stocks but also the suitability for strategies. The SI is then transformed by the designed fuzzy-set modules for stock selection and investment. Several stock selection mechanisms are proposed, denoted as SSS-T1, SSS-T2, SSS-WT1, and SSS-WT2. Experimental results show that SSS has a slight improvement in precision, but leads to a significant improvement in investment. The proposed SSS-WT1 and SSS-WT2 systems achieve the highest annual returns of 6.2% and the highest Sharpe ratios of 0.924, outperforming the benchmark with the annual return of 1.9% and the Sharpe ratio of 0.201.