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

ISBN-13: 9783319516660 / Angielski / Twarda / 2017 / 171 str.

Fahed Mostafa; Tharam Dillon; Elizabeth Chang

Opis

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.

Recenzje

"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)

Spis treści

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.

Blurb

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.