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- W160021815 abstract "Publisher Summary Data-driven modeling approaches, such as Artificial Neural Networks (ANN), are becoming more and more popular in financial applications. ANNs are nonlinear nonparametric models. ANNs allow one to fully utilize the data and let the data determine the structure and parameters of a model without any restrictive parametric modeling assumptions. They are appealing in financial area because of the abundance of high quality financial data and the paucity of testable financial models. As the speed of computers increases and the cost of computing declines exponentially, this computer intensive method becomes attractive. This chapter introduces ANN and point out its relation to some familiar statistical models. Some practical ANN modeling methods are reviewed. The chapter also reviews empirical studies in several major fields of financial applications, including option pricing, forecasting o f foreign exchange rates, bankruptcy prediction, and stock market prediction." @default.
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- W160021815 date "1996-01-01" @default.
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- W160021815 title "18 Financial applications of Artificial Neural Networks" @default.
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