Forecasting Ability But No Profitability: An Empirical Evaluation of Genetic Algorithm-optimised Technical Trading Rules

Robert Pereira ()

MPRA Paper from University Library of Munich, Germany

Abstract: This paper evaluates the performance of several popular technical trading rules applied to the Australian share market. The optimal trading rule parameter values over the in-sample period of 4/1/82 to 31/12/89 are found using a genetic algorithm. These optimal rules are then evaluated in terms of their forecasting ability and economic profitability during the out-of-sample period from 2/1/90 to the 31/12/97. The results indicate that the optimal rules outperform the benchmark given by a risk-adjusted buy and hold strategy. The rules display some evidence of forecasting ability and profitability over the entire test period. But an examination of the results for the sub-periods indicates that the excess returns decline over time and are negative during the last couple of years. Also, once an adjustment for non–synchronous trading bias is made, the rules display very little, if any, evidence of profitability.

JEL-codes: C45 C53 G0 (search for similar items in EconPapers)
Date: 1999
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Citations: View citations in EconPapers (1)

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Working Paper: Forecasting Ability but No Profitability: an Empirical Evaluation of Genetic Algorithm-Optimized Technical Trading Rules (1999)
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