Evolutionary Computation in Economics and Finance

✍ Scribed by Shu-Heng Chen (auth.), Professor Shu-Heng Chen (eds.)

• Publisher: Physica-Verlag Heidelberg
• Year: 2002
• Tongue: English
• Leaves: 459
• Series: Studies in Fuzziness and Soft Computing 100
• Edition: 1
• Category: Library

✦ Synopsis

After a decade's development, evolutionary computation (EC) proves to be a powerful tool kit for economic analysis. While the demand for this equipment is increasing, there is no volume exclusively written for economists. This volume for the first time helps economists to get a quick grasp on how EC may support their research. A comprehensive coverage of the subject is given, that includes the following three areas: game theory, agent-based economic modelling and financial engineering. Twenty leading scholars from each of these areas contribute a chapter to the volume. The reader will find himself/herself treading the path of the history of this research area, from the fledgling stage to the burgeoning era. The results on games, labour markets, pollution control, institution and productivity, financial markets, trading systems design and derivative pricing, are new and interesting for different target groups. The book also includes informations on useful web sites, conferences, and computer software.

✦ Table of Contents

Front Matter....Pages I-XII
Front Matter....Pages 1-1
Evolutionary Computation in Economics and Finance: An Overview of the Book....Pages 3-28
Front Matter....Pages 29-29
Playing Games with Genetic Algorithms....Pages 31-44
Genetic Algorithm Learning and Economic Evolution....Pages 45-60
Using Symbolic Regression to Infer Strategies from Experimental Data....Pages 61-82
Front Matter....Pages 83-83
The Efficiency of an Artificial Double Auction Stock Market with Neural Learning Agents....Pages 85-105
On AIE-ASM: Software to Simulate Artificial Stock Markets with Genetic Programming....Pages 107-122
Exchange Rate Volatility in the Artificial Foreign Exchange Market....Pages 123-134
Using an Artificial Market Approach to Analyze Exchange Rate Scenarios....Pages 135-157
Emulating Trade in Emissions Permits: An Application of Genetic Algorithms....Pages 159-173
Cooperative Computation with Market Mechanism....Pages 175-188
Hysteresis in an Evolutionary Labor Market with Adaptive Search....Pages 189-210
Computable Learning, Neural Networks and Institutions....Pages 211-232
On Two Types of GA-Learning....Pages 233-243
Evolutionary Computation and Economic Models: Sensitivity and Unintended Consequences....Pages 245-269
Front Matter....Pages 271-271
Tinkering with Genetic Algorithms: Forecasting and Data Mining in Finance and Economics....Pages 273-286
Forecasting Ability But No Profitability: An Empirical Evaluation of Genetic Algorithm-Optimised Technical Trading Rules....Pages 287-310
Evolutionary Induction of Trading Models....Pages 311-331
Optimizing Technical Trading Strategies with Split Search Genetic Algorithms....Pages 333-358
GP Forecasts of Stock Prices for Profitable Trading....Pages 359-381
Option Pricing Via Genetic Programming....Pages 383-397
Front Matter....Pages 271-271
Evolutionary Computation in Option Pricing: Determining Implied Volatilities Based on American Put Options....Pages 399-415
Front Matter....Pages 417-417
Evolutionary Computation in Economics and Finance: A Bibliography....Pages 419-455
Back Matter....Pages 456-460

✦ Subjects

Artificial Intelligence (incl. Robotics); Game Theory/Mathematical Methods; Finance/Investment/Banking; Algorithm Analysis and Problem Complexity; Game Theory, Economics, Social and Behav. Sciences