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首页> 外文期刊>African Journal of Business Management >Optimized classification approach to modeling an expert system for selecting stock portfolio
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Optimized classification approach to modeling an expert system for selecting stock portfolio

机译：优化分类方法以建模专家系统来选择股票投资组合

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摘要

An expert system for automatically selecting stock portfolio is presented. The expert system involved Grey Relational Analysis (GRA) model, the VPRS-index clustering / classification method, and Variable Precision Rough Set (VPRS) theory. The GRA model is applied to consolidate the 53 financial indices into six financial ratios (Grey Relational Grades (GRGs)) for each stock item. The VPRS-index method is used to determine the optimal number of clusters per GRG. VPRS theory is then applied to identify the stocks within the?-lower approximate sets. Finally, the GRGs of each candidate stock item are consolidated to a single GRG indicating the ability of the stock item to maximize the rate of return. The validity and effectiveness of the VPRS-index clustering / classification method is first evaluated prior to that of the expert system. After that, results of this study showed that this expert system yields a higher rate of return than those of several existing portfolio selection systems.
机译：提出了一种自动选择股票投资组合的专家系统。专家系统涉及灰色关联分析（GRA）模型，VPRS索引聚类/分类方法和可变精度粗糙集（VPRS）理论。 GRA模型用于将53个财务指标合并为每个库存项目的六个财务比率（灰色关联等级（GRG））。 VPRS索引方法用于确定每个GRG的最佳群集数。然后，将VPRS理论应用于识别低等近似集内的股票。最终，将每个候选库存商品的GRG合并为一个GRG，表明库存商品最大化回报率的能力。首先评估VPRS索引聚类/分类方法的有效性和有效性，然后评估专家系统的有效性。此后，这项研究的结果表明，该专家系统比几种现有的投资组合选择系统产生更高的回报率。

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