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A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

机译:人工智能在金融中的应用比较研究:人工神经网络,专家系统和混合智能系统

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摘要

Nowadays, many current real financial applications have nonlinear and uncertain behaviors which change across the time. Therefore, the need to solve highly nonlinear, time variant problems has been growing rapidly. These problems along with other problems of traditional models caused growing interest in artificial intelligent techniques. In this paper, comparative research review of three famous artificial intelligence techniques, i.e., artificial neural networks, expert systems and hybrid intelligence systems, in financial market has been done. A financial market also has been categorized on three domains: credit evaluation, portfolio management and financial prediction and planning. For each technique, most famous and especially recent researches have been discussed in comparative aspect. Results show that accuracy of these artificial intelligent methods is superior to that of traditional statistical methods in dealing with financial problems, especially regarding nonlinear patterns. However, this outperformance is not absolute.
机译:如今,许多当前的实际金融应用都具有非线性和不确定的行为,这些行为会随时间而变化。因此,解决高度非线性的时变问题的需求迅速增长。这些问题以及传统模型的其他问题引起了人们对人工智能技术的日益增长的兴趣。本文对金融市场上三种著名的人工智能技术,即人工神经网络,专家系统和混合智能系统进行了比较研究综述。金融市场也分为三个领域:信用评估,投资组合管理以及财务预测和计划。对于每种技术,已经在比较方面讨论了最著名的,尤其是最近的研究。结果表明,这些人工智能方法在处理财务问题(尤其是在非线性模式方面)方面优于传统的统计方法。但是,这种表现并不是绝对的。

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