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Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk
Elizabeth Chang
€ 149.71
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Description for Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk
Hardback. Series: Studies in Computational Intelligence. Num Pages: 171 pages, 23 black & white illustrations, biography. BIC Classification: JFFR; KJT; UYM; UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155. .
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.
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.
Product Details
Format
Hardback
Publication date
2017
Publisher
Springer International Publishing AG Switzerland
Number of pages
171
Condition
New
Series
Studies in Computational Intelligence
Number of Pages
171
Place of Publication
Cham, Switzerland
ISBN
9783319516660
SKU
V9783319516660
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk
“The book describes how to deal with the different sorts of financial market risk. … The book can be used by advanced undergraduate students and graduate students in its entirety. It is also interesting for the specialists in financial market risk and is of considerable importance to practitioners in the field.” (Yuliya S. Mishura, zbMath 1410.91004, 2019)