Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk

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.

Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk features in the following genres: Artificial intelligence, Management decision making, Operational research, Macroeconomics

Hardback. Not Available.

Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk was written by Fahed Mostafa, Tharam S Dillon, Elizabeth Chang and published by Springer an imprint of Springer International Publishing

Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk has 171 pages

Yes it is part of Studies in Computational Intelligence series