Work

Using genetic algorithms to find technical trading rules

Year: 1999

Type: article

Abstract: We use a genetic algorithm to learn technical trading rules for the S&P 500 index using daily prices from 1928 to 1995. After transaction costs, the rules do not earn consistent excess returns over a simple buy-and-hold strategy in the out-of-sample test periods. The rules are able to identify periods to be in the index when daily returns are positive and volatility is low and out when the reverse is true. These latter results can largely be explained by low-order serial correlation in stock index returns.

Source: Journal of Financial Economics

DOI: 10.1016/s0304-405x(98)00052-x

Authors: Franklin Allen, Risto Karjalainen

Institution: University of Pennsylvania

Language: English

Topic: Financial Markets and Investment Strategies

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $4,740

OpenAlex ID: W2149214223

FWCI: 44.76

Cites: 34

Cited by: 866

Related to: 10