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Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk
About this item
This book demonstrates the power of neural networks in learning complex behavior from the underlying financial time series data. The results presented also show how neural networks can successfully be applied to volatility modeling, option pricing, and value-at-risk modeling. These features mean that they can be applied to market-risk problems to overcome classic problems associated with statistical models.
Genre: Computers + Internet, Business + Money Management
Series Title: Studies in Computational Intelligence
Publisher: Springer Verlag
Author: Fahed Mostafa & Tharam Dillon & Elizabeth Chang
Street Date: March 10, 2017
Item Number (DPCI): 248-41-0022
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