Data-Snooping, Technical Trading Rule Performance, and the Bootstrap

University of California at San Diego, Department of Economics, Discussion Paper No. 97-31

Posted: 8 Mar 1998

See all articles by Ryan Sullivan

Ryan Sullivan

Bates White & Ballentine

Allan Timmermann

UCSD ; Centre for Economic Policy Research (CEPR)

Halbert L. White, Jr.

University of California, San Diego (UCSD) - Department of Economics

Multiple version iconThere are 2 versions of this paper

Date Written: December 1997

Abstract

Numerous studies in the finance literature have investigated technical analysis to determine its validity as an investment tool. Several of these studies conclude that technical analysis does have merit, however, it is noted that the effects of data-snooping are not fully accounted for. In this paper we utilize White's Reality Check bootstrap methodology (White (1997)) to evaluate simple technical trading rules while quantifying the data-snooping bias and fully adjusting for its effect in the context of the full universe from which the trading rules were drawn. Hence, for the first time, the paper presents a means of calculating a comprehensive test of performance across all trading rules. In particular, we consider the study of Brock, Lakonishok, and LeBaron (1992), expand their universe of 26 trading rules, apply the rules to 100 years of daily data on the Dow Jones Industrial Average, and determine the effects of data-snooping. During the sample period inspected by Brock, Lakonishok and LeBaron, we find that the best technical trading rule is capable of generating superior performance even after accounting for data-snooping. However, we also find that the best technical trading rule does not provide superior performance when used to trade in the subsequent 10-year post-sample period. We also perform a similar analysis, applying technical trading rules to the Standard and Poor's 500 futures contract. Here, too, we find no evidence that the best technical rule outperforms, once account is taken of data-snooping effects.

JEL Classification: C12, C52, C63, G12, G14

Suggested Citation

Sullivan, Ryan M. and Timmermann, Allan and White, Halbert L., Data-Snooping, Technical Trading Rule Performance, and the Bootstrap (December 1997). University of California at San Diego, Department of Economics, Discussion Paper No. 97-31. Available at SSRN: https://ssrn.com/abstract=65140

Ryan M. Sullivan

Bates White & Ballentine ( email )

Del Mar, CA
United States

Allan Timmermann (Contact Author)

UCSD ( email )

9500 Gilman Drive
La Jolla, CA 92093-0553
United States
858-534-0894 (Phone)

HOME PAGE: http://rady.ucsd.edu/people/faculty/timmermann/

Centre for Economic Policy Research (CEPR)

London
United Kingdom

Halbert L. White

University of California, San Diego (UCSD) - Department of Economics ( email )

9500 Gilman Drive
La Jolla, CA 92093-0508
United States
858-534-3502 (Phone)
858-534-7040 (Fax)

HOME PAGE: http://www.econ.ucsd.edu/~mbacci/white/

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