Evolutionary Money Management

Authors:
Philip Saks;Dietmar Maringer
Affiliations:
Centre for Computational Finance and Economic Agents, University of Essex,;Department for Quantitative Methods, Economics and Business Faculty, University of Basel,
Venue:
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Year:
2009

Citing 2
Cited 3

Genetic programming in statistical arbitrage

Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Knowledge-intensive genetic discovery in foreign exchange markets

IEEE Transactions on Evolutionary Computation

A stock market decision support system with a hybrid evolutionary algorithm for many-core graphics processors

Euro-Par 2010 Proceedings of the 2010 conference on Parallel processing
Evolving trading rule-based policies

EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
Combining technical analysis and grammatical evolution in a trading system

EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper evolves trading strategies using genetic programming on high-frequency tick data of the USD/EUR exchange rate covering the calendar year 2006. This paper proposes a novel quad tree structure for trading system design. The architecture consists of four trees each solving a separate task, but mutually dependent for overall performance. Specifically, the functions of the trees are related to initiating ("entry") and terminating ("exit") long and short positions. Thus, evaluation is contingent on the current market position. Using this architecture the paper investigates the effects of money management. Money management refers to certain measures that traders use to control risk and take profits, but it is found that it has a detrimental effects on performance.