Title:
Neural networks in finance : gaining predictive edge in the market
Personal Author:
Publication Information:
Burlington, MA : Elsevier Academic Press, 2005
ISBN:
9780124859678
Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000010075502 | HG4012.5 M36 2005 | Open Access Book | Book | Searching... |
On Order
Summary
Summary
This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong.
Table of Contents
| Preface |
| 1 Introduction |
| 2 What Are Neural Networks |
| 3 Estimation of a Network with Evolutionary Computation |
| 4 Evaluation of Network Estimation |
| 5 Estimation and Forecasting with Artificial Data |
| 6 Times Series: Examples from Industry and Finance |
| 7 Inflation and Deflation: Hong Kong and Japan |
| 8 Classification: Credit Card Default and Bank Failures |
| 9 Dimensionality Reduction and Implied Volatility Forecasting |
