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Computational intelligence applicati...

Chang, Elizabeth.

Computational intelligence applications to option pricing, volatility forecasting and value at risk

Record Type:	Electronic resources : Monograph/item
Title/Author:	Computational intelligence applications to option pricing, volatility forecasting and value at riskby Fahed Mostafa, Tharam Dillon, Elizabeth Chang.
Author:	Mostafa, Fahed.
other author:	Dillon, Tharam.
Published:	Cham :Springer International Publishing :2017.
Description:	x, 171 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Computational intelligence.
Online resource:	http://dx.doi.org/10.1007/978-3-319-51668-4
ISBN:	9783319516684$q(electronic bk.)

Computational intelligence applications to option pricing, volatility forecasting and value at risk
Mostafa, Fahed.

Computational intelligence applications to option pricing, volatility forecasting and value at risk[electronic resource] /by Fahed Mostafa, Tharam Dillon, Elizabeth Chang. - Cham :Springer International Publishing :2017. - x, 171 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.6971860-949X ;. - Studies in computational intelligence ;v. 216..

CHAPTER 1 Introduction -- CHAPTER 2 Time Series Modelling -- CHAPTER 3 Options and Options Pricing Models -- CHAPTER 4 Neural Networks and Financial Forecasting -- CHAPTER 5 Important Problems in Financial Forecasting -- CHAPTER 6 Volatility Forecasting -- CHAPTER 7 Option Pricing -- CHAPTER 8 Value-at-Risk -- CHAPTER 9 Conclusion and Discussion.

The results in this book demonstrate the power of neural networks in learning complex behavior from the underlying financial time series data. The results in this book also demonstrate how neural networks can successfully be applied to volatility modeling, option pricings, and value at risk modeling. These features allow them to be applied to market risk problems to overcome classical issues associated with statistical models.

ISBN: 9783319516684$q(electronic bk.)

Standard No.: 10.1007/978-3-319-51668-4doiSubjects--Topical Terms:

210824
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Computational intelligence applications to option pricing, volatility forecasting and value at risk
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505 0 $a CHAPTER 1 Introduction -- CHAPTER 2 Time Series Modelling -- CHAPTER 3 Options and Options Pricing Models -- CHAPTER 4 Neural Networks and Financial Forecasting -- CHAPTER 5 Important Problems in Financial Forecasting -- CHAPTER 6 Volatility Forecasting -- CHAPTER 7 Option Pricing -- CHAPTER 8 Value-at-Risk -- CHAPTER 9 Conclusion and Discussion.
520 $a The results in this book demonstrate the power of neural networks in learning complex behavior from the underlying financial time series data. The results in this book also demonstrate how neural networks can successfully be applied to volatility modeling, option pricings, and value at risk modeling. These features allow them to be applied to market risk problems to overcome classical issues associated with statistical models.
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