Applications of Artificial Intelligence in Finance and Economics

by Binner; Kendall; Chen

• ISBN13: 9780762311507
• ISBN10: 0762311509
• Format: Hardcover
• Copyright: 2005-03-24
• Publisher: Elsevier Science & Technology
• More Book Details

Summary

Artificial intelligence is a consortium of data-driven methodologies which includes artificial neural networks, genetic algorithms, fuzzy logic, probabilistic belief networks and machine learning as its components. We have witnessed a phenomenal impact of this data-driven consortium of methodologies in many areas of studies, the economic and financial fields being of no exception. In particular, this volume of collected works will give examples of its impact on the field of economics and finance. This volume is the result of the selection of high-quality papers presented at a special session entitled 'Applications of Artificial Intelligence in Economics and Finance' at the '2003 International Conference on Artificial Intelligence' (IC-AI '03) held at the Monte Carlo Resort, Las Vegas, Nevada, USA, June 23-26 2003. The special session, organised by Jane Binner, Graham Kendall and Shu-Heng Chen, was presented in order to draw attention to the tremendous diversity and richness of the applications of artificial intelligence to problems in Economics and Finance. This volume should appeal to economists interested in adopting an interdisciplinary approach to the study of economic problems, computer scientists who are looking for potential applications of artificial intelligence and practitioners who are looking for new perspectives on how to build models for everyday operations. There are still many important Artificial Intelligence disciplines yet to be covered. Among them are the methodologies of independent component analysis, reinforcement learning, inductive logical programming, classifier systems and Bayesian networks, not to mention many ongoing and highly fascinating hybrid systems. A way to make up for their omission is to visit this subject again later. We certainly hope that we can do so in the near future with another volume of 'Applications of Artificial Intelligence in Economics and Finance'.

Table of Contents

List of Contributors	vii
Statistical Analysis of Genetic Algorithms in Discovering Technical Trading Strategies	1	(44)
Chueh-Yung Tsao
Shu-Heng Chen
A Genetic Programming Approach to Model International Short-Term Capital Flow	45	(26)
Tina Yu
Shu-Heng Chen
Tzu-Wen Kuo
Tools for Non-Linear Time Series Forecasting in Economics -- An Empirical Comparison of Regime Switching Vector Autoregressive Models and Recurrent Neural Networks	71	(22)
Jane M. Binner
Thomas Elger
Birger Nilsson
Jonathan A. Tepper
Using Non-Parametric Search Algorithms to Forecast Daily Excess Stock Returns	93	(34)
Nathan Lael Joseph
David S. Bree
Efstathios Kalyvas
Co-Evolving Neural Networks with Evolutionary Strategies: A New Application to Divisia Money	127	(18)
Jane M. Binner
Graham Kendall
Alicia Gazely
Forecasting the EMU Inflation Rate: Linear Econometric Vs. Non-Linear Computational Models Using Genetic Neural Fuzzy Systems	145	(30)
Stefan Kooths
Timo Mitze
Eric Ringhut
Finding or Not Finding Rules in Time Series	175	(28)
Jessica Lin
Eamonn Keogh
A Comparison of Var and Neural Networks with Genetic Algorithm in Forecasting Price of Oil	203	(22)
Sam Mirmirani
Hsi Cheng Li
Searching for Divisia/Inflation Relationships with the Aggregate Feedforward Neural Network	225	(18)
Vincent A. Schmidt
Jane M. Binner
Predicting Housing Value: Genetic Algorithm Attribute Selection and Dependence Modelling Utilising the Gamma Test	243
Ian D. Wilson
Antonia J. Jones
David H. Jenkins
J. A. Ware