文件名称：Biologically_Inspired_Algorithms_for_Financial_modelling
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更新时间：2021-07-05 17:03:20
神经网络 金融
神经网络算法在金融学中的运用 The field of biologically inspired computing has advanced rapidly over the past decade. One offshoot of this progress has been the development of a large family of biologically inspired algorithms. Broadly speaking, biologically inspired algorithms draw metaphorical inspiration from diverse sources, including the operation of biological neurons, processes of evolution, models of social interaction amongst organisms, and natural immune systems, in order to develop tools for solving real-world problems. This book provides an introduction to a broad range of biologically inspired algorithms and illustrates how they can be applied for financial modelling using a series of case studies. These cases include the modelling of financial markets, the development of financial trading systems, the creation of solvency prediction systems, and the creation of credit rating models. In this book particular emphasis is placed on evolutionary methodologies, particularly the novel, powerful, modelling methodology Grammatical Evolution. No prior knowledge of either biologically inspired algorithms or financial modelling is assumed.
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Biologically_Inspired_Algorithms_for_Financial_modelling.pdf