Combined soft computing model for value stock selection based on fundamental analysis

摘要: A combined soft computing model for value investing is proposed.The DRSA generated 20 rules to classify stocks.Two strong decision were obtained conducting FCA analysis.The selected "Good" stock portfolio outperformed the market index.Implications selection are by and FCA. The problem one of major issues in investment industry, which mainly solved analyzing financial ratios. However, considering complexity imprecise patterns market, obvious easy-to-understand rules, based on fundamental analysis, difficult obtain. Therefore, this paper, we propose a tackling problem, includes dominance-based rough set approach, formal concept decision-making trial evaluation laboratory technique. objectives proposed approach (1) obtain (2) identify core attributes that may distinguish stocks, (3) explore cause-effect relationships among or criteria gain more insights. To examine illustrate model, study used group IT stocks Taiwan as an empirical case. findings contribute in-depth understanding practice.