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Application in financial data prediction of neural networks based on Monte-Carlo-Adaptation rule

Abstract

上个世纪全球金融市场最重要变革来自于金融衍生品的创新和繁荣。但随后频繁而剧烈的金融危机却使得人们对基于有效市场假说的传统金融理论开始进行反思。随着行为经济学和经济物理学等领域的开创性研究,人们发现了经济系统明显违背传统理论的假设,经济代理人并非全同的理性而具有异质性和非理性,市场不能自动演化到均衡状态而具有长程时间和空间关联,在特定的条件下具有自组织临界性。因此,基于复杂非线性系统的统计物理和动力学理论正被广泛用于经济金融领域研究。人工神经网络是一个典型的多体非线性动力学系统,通过吸引子来学习和记忆系统特征信息,正被广泛用于金融时间序列的预测。 本文利用“蒙特卡洛随机变异-优化选择”的设计规...The global financial markets had a great change due to the innovation and prosperity of financial derivatives during last century. However, frequent financial crisis makes people began to reflect on the traditional financial theories which based on effective market hypothesis. Along with the pioneering study on behavioral economics and econophysics, people found out that the economic system obviou...学位:理学硕士院系专业:物理与机电工程学院物理学系_理论物理学号:1982009115252

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