Stock Screening Based on Fuzzy Comprehensive Evaluation Model: A Case Study of the U.S. Financial Services Industry Banking under the COVID-19 pandemic

Abstract

Faced with the strong impact of the epidemic, investment strategies also need to be optimized according to the actual situation. This paper analyzes the data of 282 stocks in the financial services industry and banking industry in the U.S. stock market from 2015-2021 through the fuzzy comprehensive analysis model, and selects a relatively appropriate intra industry portfolio according to the Sharpe ratio. In the process of research, based on the existing data and the social assessment of the covid-19 epidemic, a fuzzy comprehensive analysis model was initially constructed. This provides corresponding evaluation rules for each influencing factor, and determines its weight in a certain level of fuzzy comprehensive analysis model. Then, the experiment can screen out 29 high-quality stocks in the industry according to the total score. Then, the experiment classifies high-quality stocks according to their different characteristics, and selects the stocks with the highest scores in each category to participate in portfolio comparison. Finally, the experiment will focus on the Sharpe ratio and select a relatively good portfolio example at this stage after comprehensively evaluating the rationality of other values. At present, this example has strong investment value, and the investment strategy discussed in this paper may also have strong applicability in other industries after appropriate adjustment.