论文标题
股票投资组合选择的模糊专家系统：孟买证券交易所的申请
Fuzzy Expert System for Stock Portfolio Selection: An Application to Bombay Stock Exchange
论文作者
论文摘要
在分配投资比率之前，选择适当的股票始终是投资者的至关重要的任务。股票绩效中许多影响因素的存在促使研究人员采用各种人工智能（AI）技术，以使这项具有挑战性的任务更容易。在本文中，提出了一种新颖的模糊专家系统模型来评估和对孟买证券交易所（BSE）下的股票进行排名。 Dempster-Shafer（DS）证据理论首次使用自动产生模糊规则基础的结果，以减少专家系统知识基础发展的努力。后来，构建了一个投资组合优化模型，其中目标函数被视为模糊投资组合返回差的比率，而无风险回报与已使用的资产的加权平均半变化。通过偏爱最高排名的股票，通过应用蚂蚁菌落优化（ACO）算法来解决该模型。与最近的股票绩效相比，该模型的表现在短期投资期间被证明是令人满意的。
Selection of proper stocks, before allocating investment ratios, is always a crucial task for the investors. Presence of many influencing factors in stock performance have motivated researchers to adopt various Artificial Intelligence (AI) techniques to make this challenging task easier. In this paper a novel fuzzy expert system model is proposed to evaluate and rank the stocks under Bombay Stock Exchange (BSE). Dempster-Shafer (DS) evidence theory is used for the first time to automatically generate the consequents of the fuzzy rule base to reduce the effort in knowledge base development of the expert system. Later a portfolio optimization model is constructed where the objective function is considered as the ratio of the difference of fuzzy portfolio return and the risk free return to the weighted mean semi-variance of the assets that has been used. The model is solved by applying Ant Colony Optimization (ACO) algorithm by giving preference to the top ranked stocks. The performance of the model proved to be satisfactory for short-term investment period when compared with the recent performance of the stocks.
