The Performance of Stock Portfolios formed using Fuzzy Logic

Amit K. Sinha, Andrew J. Jacob

Article ID: 814
Vol 3, Issue 1, 2020

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Expert systems, a type of artificial intelligence that replicate how experts think, can aide unskilled users in making decisions or apply an expert’s thought process to a sample much larger than could be examined by a human expert. In this paper, an expert system that ranks financial securities using fuzzy membership functions is developed and applied to form portfolios. Our results indicate that this approach to form stock portfolios can result in superior returns than the market as measured by the return on the S&P 500. These portfolios may also provide superior risk-adjusted returns when compared to the market.


Expert Systems; Stock returns; portfolios; fuzzy logic; Sharpe ratio; Treynor ratio

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