Knowledge-intensive genetic discovery in foreign exchange markets

Author

Bhattacharyya, Siddhartha ; Pictet, Olivier V. ; Zumbach, Gilles

Author_Institution

Dept. of Inf. & Decision Sci., Illinois Univ., Chicago, IL, USA

Volume

6

Issue

2

fYear

2002

fDate

4/1/2002 12:00:00 AM

Firstpage

169

Lastpage

181

Abstract

This paper considers the discovery of trading decision models from high-frequency foreign exchange (FX) markets data using genetic programming (GP). It presents a domain-related structuring of the representation and incorporation of semantic restrictions for GP-based searching of trading decision models. A defined symmetry property provides a basis for the semantics of FX trading models. The symmetry properties of basic indicator types useful in formulating trading models are defined, together with semantic restrictions governing their use in trading model specification. The semantics for trading model specification have been defined with respect to regular arithmetic, comparison and logical operators. This study also explores the use of two fitness criteria for optimization, showing more robust performance with a risk-adjusted measure of returns

Keywords

data mining; financial data processing; foreign exchange trading; genetic algorithms; knowledge representation; learning (artificial intelligence); mathematical operators; symmetry; arithmetic operators; comparison operators; data mining; domain-related structuring; financial markets; genetic programming; high-frequency foreign exchange markets; indicator types; knowledge-intensive genetic discovery; logical operators; machine learning; optimization fitness criteria; risk-adjusted return measure; robust performance; semantic restrictions; symmetry properties; trading decision model discovery; trading model specification; Arithmetic; Asset management; Availability; Data analysis; Data mining; Fractals; Genetic programming; Investments; Machine learning; Robustness;

fLanguage

English

Journal_Title

Evolutionary Computation, IEEE Transactions on

Publisher

ieee

ISSN

1089-778X

Type

jour

DOI

10.1109/4235.996016

Filename

996016