Using Genetic Algorithms for Robust Optimization in Financial Applications

Posted: 25 Aug 1998

See all articles by Olivier V. Pictet

Olivier V. Pictet

Pictet Asset Management

Michel M. Dacorogna

DEAR-Consulting

Bastien Chopard

University of Geneva

Mouloud Oussaidene

University of Geneva

Roberto Schirru

Olsen Group (Olsen & Associates Ltd.)

Marco Tomassini

University of Lausanne

Abstract

In this study, optimal indicators and strategies for foreign exchange trading models are investigated in the framework of genetic algorithms. We first explain how the relevant quantities of our application can be encoded in "genes" so as to fit the requirements of the genetic evolutionary optimization technique. In financial problems, sharp peaks of high fitness are usually not representative of a general solution but, rather, indicative of some accidental fluctuations. Such fluctuations may arise out of inherent noise in the time series or due to threshold effects in the trading model performance. Peaks in such a discontinuous, noisy and multimodal fitness space generally correspond to trading models which will not perform well in out-of-sample tests. In this paper we show that standard genetic algorithms will be quickly attracted to one of the accidental peaks of the fitness space whereas genetic algorithms for multimodal functions employing clustering and a specially designed fitness sharing scheme will find optimal parameters which correspond to broad regions where the fitness function is higher on average. The optimization and the quality tests have been performed over eight years of high frequency data of the main foreign exchange rates. The authors acknowledge a careful review of the manuscript by Rakhal D. Dave and useful discussions with Ulrich M. Muller. The Swiss National Science Foundation is gratefully acknowledged for its financial support.

JEL Classification: C52

Suggested Citation

Pictet, Olivier V. and Dacorogna, Michel M. and Chopard, Bastien and Oussaidene, Mouloud and Schirru, Roberto and Tomassini, Marco, Using Genetic Algorithms for Robust Optimization in Financial Applications. Available at SSRN: https://ssrn.com/abstract=6443

Olivier V. Pictet (Contact Author)

Pictet Asset Management ( email )

Geneva
Switzerland

Michel M. Dacorogna

DEAR-Consulting ( email )

Scheuchzerstrasse 160
Zurich, 8057
Switzerland
+41795447327 (Phone)

Bastien Chopard

University of Geneva ( email )

40, Boulevard du Pont-d'Arve
Genève, CH - 1205
Switzerland

Mouloud Oussaidene

University of Geneva

Genève, CH - 1205
Switzerland

Roberto Schirru

Olsen Group (Olsen & Associates Ltd.)

Seefeldstrasse 233
CH-8008 Zurich
Switzerland

Marco Tomassini

University of Lausanne ( email )

Quartier Chambronne
Lausanne, Vaud CH-1015
Switzerland

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