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Plenary Lecture 9 Innovative methods for improving portfolio management based on artificial intelligence instruments

机译:全体会议第九讲基于人工智能工具的改善投资组合管理的创新方法

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Financial markets represent one of the most complex environments for business and there are a lot of types of external factors which impact their dynamics. The recent financial turbulence materialized by the global financial crisis 2008-2009 and the European sovereign debt crisis (2010-2012) made serious pressure on financial markets that proved their fragility and sensitivity in a different manner.The use of different instruments used on artificial intelligence could be applied in decision making process in financial markets because they offer a unique capability of learning.The conventional theories regarding the anticipation of financial markets evolution are represented by the efficient market hypothesis (Fama, 1970) and the paradigm regarding the methods to anticipate the future performance of financial assets. The actual interest is to identify optimal strategies for portfolio management by using artificial intelligence.The basic steps of incorporating different types of artificial intelligences on the study of the future dynamic of the performance of different financial assets are the following: the analysis of the strategies used by different portfolio managers and their performances; the identification of new instruments capable to improve the strategy references;the selection/ development and testing of the new instrument; the analysis of the differential performance.Actual artificial intelligence instruments are difficult to create/develop and to use because in this paper will be presented a new concept in which the basis will be the application data transformation in order to build different sets of training artificial neuronal networks in order to optimize/modify in an easy way their behavior. This module for simulating the artificial neuronal network is improved by using genetic algorithms to select the best network regarding the predictions of the performance of financial instruments, but also the optimal timing in the process of portfolio management.
机译:金融市场是业务最复杂的环境之一,并且有许多类型的外部因素会影响其动态。 2008-2009年全球金融危机和欧洲主权债务危机(2010-2012)造成的近期金融动荡给金融市场带来了沉重压力,这些金融市场以不同的方式证明了它们的脆弱性和敏感性。可以用于金融市场的决策过程,因为它们提供了独特的学习能力。有关金融市场发展预期的传统理论以有效的市场假设(Fama,1970年)和有关预测金融市场的方法范式为代表。金融资产的未来表现。实际的兴趣是使用人工智能来确定投资组合管理的最佳策略。将不同类型的人工智能纳入研究不同金融资产绩效的未来动态的基本步骤如下:分析所使用的策略不同的投资组合经理及其表现;确定能够改善战略参考的新工具;选择/开发和测试新工具;实际的人工智能仪器很难创建/开发和使用,因为在本文中将介绍一个新的概念,在该概念中,将以应用数据转换为基础,以构建不同的训练人工神经元集。网络以方便地优化/修改其行为。通过使用遗传算法选择关于金融工具的绩效预测的最佳网络,以及投资组合管理过程中的最佳时机,改进了模拟人工神经网络的模块。

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