Computational intelligence applications to option pricing, volatility forecasting and value at risk
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 modelin...
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| Main Authors | , , |
|---|---|
| Format | Electronic eBook |
| Language | English |
| Published |
Cham, Switzerland :
Springer,
2017.
|
| Series | Studies in computational intelligence ;
v. 697. |
| Subjects | |
| Online Access | Full text |
| ISBN | 9783319516684 9783319516660 |
| ISSN | 1860-949X ; |
| Physical Description | 1 online resource (x, 171 pages) : illustrations |
Cover
Table of Contents:
- 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.