Computational intelligence applications to option pricing, volatility forecasting and value at risk
type: Item
instance of: scholarly article
title: Computational intelligence applications to option pricing, volatility forecasting and value at risk
zbMATH Open document ID: 1410.91004
DOI: 10.1007/978-3-319-51668-4
author: Fahed Mostafa
author: E. Chang
author: Tharam S. Dillon
published in: Studies in Computational Intelligence
publication date: 2017-12-08T00:00:00Z
review text: The book describes how to deal with the different sorts of financial market risk. In the book, market risk is grouped into four main categories: volatility forecasting, option pricing, hedging and portfolio risk management. When developing these quantitative methods, the focus in the book has been twofold: first, to build on the existing methodologies such as the GARCH and Black-Scholes models and second to develop approaches to overcome the disadvantages inherent in the models arising from the underlying assumptions which have been found to not properly reflect the behaviours inherent in the markets. The book consists of 9 chapters. Chapter 1 provides a broad introduction to some of the important concepts involved in market risk. Time series models are reviewed in Chapter 2. The weakness of each of the modelling techniques is highlighted and explained with reference to research. Chapter 3 introduces options, existing option-pricing models and hedging, Chapter 4 provides a review of neural networks. Chapter 5 outlines important problems in financial forecasting including volatility forecasting, options pricing and hedging. Volatility forecasting models are considered and evaluated in Chapter 6 including the GARCH, EGARCH and mixture density models. Chapter 7 considers option-pricing models including GARCH option-pricing model (GOPM), BSOPM model, implied volatility and existing neural net models. Value-at-risk is considered in Chapter 8 including definitions and models, and Chapter 9 provides a recapitulation and conclusions. 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.
Mathematics Subject Classification ID: 91-02
Mathematics Subject Classification ID: 91-04
Mathematics Subject Classification ID: 91G20
Mathematics Subject Classification ID: 62P05
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 91G70
Mathematics Subject Classification ID: 91G10
zbMATH DE Number: 6816564
zbMATH Keywords: market risk
zbMATH Keywords: volatility forecasting
zbMATH Keywords: option pricing
zbMATH Keywords: hedging and portfolio risk management
zbMATH Keywords: computation intelligence
zbMATH Keywords: neural networks
zbMATH Keywords: Black-Scholes implied volatility
zbMATH Keywords: time series models
zbMATH Keywords: GARCH, EGARCH and mixture density models
reviewed by: Yuliya S. Mishura
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1007/978-3-319-51668-4
OpenAlex ID: W2592549843
description: scientific article; zbMATH DE number 6816564