Modeling Exchange Rate Behavior with a Genetic Algorithm

被引：16

作者：

C. Lawrenz

F. Westerhoff

机构：

[1] Department of Economics, University of Osnabrueck, D-49069 Osnabrueck

来源：

Computational Economics | 2003年 / 21卷 / 3期

关键词：

exchange rate theory; genetic algorithm; technical and fundamental trading rules;

D O I：

10.1023/A:1023943726237

中图分类号：

学科分类号：

摘要：

Motivated by empirical evidence, we construct a model where heterogeneous, boundedly-rational market participants rely on a mix of technical and fundamental trading rules. The rules are applied according to a weighting scheme. Traders evaluate and update their mix of rules by genetic algorithm learning. Even for fundamental shocks with a low probability, the interaction between the traders produces a complex behavior of exchange rates. Our model simultaneously produces several stylized facts like high volatility, unit roots in the exchange rates, a fuzzy relationship between news and exchange-rate movements, cointegration between the exchange rate and its fundamental value, fat tails for returns, a declining kurtosis under time aggregation, weak evidence of mean reversion, and strong evidence of clustering in both volatility and trading volume. © 2003 Kluwer Academic Publishers.

引用

页码：209 / 229

页数：20

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