Description
Book SynopsisThe result of the selection of papers presented at a special session entitled 'Applications of Artificial Intelligence in Economics and Finance' at the '2003 International Conference on Artificial Intelligence'. This volume will appeal to economists interested in adopting an interdisciplinary approach to the study of economic problems.
Table of Contents1. Statistical analysis of genetic algorithms in discovering technical trading strategies (S.H. Chen, C.Y. Tsao). 2. A genetic programming approach to model international short-term capital flow (T. Yu, S.H. Chen, T.W. Kuo). 3. Tools for non-linear time series forecasting in economics: An empirical comparison of regime switching vector autoregressive models and recurrent neural networks (J.M. Binner, T. Elger, B. Nilsson, J.A. Tepper). 4. Using non-parametric search algorithms to forecast daily excess stock returns (N.L. Joseph, D.S. Bree, E. Kalyvas). 5. Co-evolving neural networks with evolutionary strategies: A new application to Divisia Money (J. Binner, G. Kendall, A. Gazely). 6. Forecasting the EMU inflation rate: Linear econometric versus non-linear computational models using genetic neural fuzzy systems (S. Kooths, T. Mitze, E. Ringhut). 7. Finding or not finding rules in time series (J. Lin, E. Keogh). 8. A comparison of VAR and neural networks with genetic algorithm in forecasting price of oil (S. Mirmirani, H.C. Li). 9. Searching for Divisia/Inflation Relationships with the aggregate feed forward neural network (V.A. Schmidt, J.M. Binner). 10. Predicting housing value: Genetic algorithm attribute selection and dependence modelling utilising the gamma test (I.D. Wilson, A. J. Jones, D.H. Jenkins, J.A. Ware).
