Data-Snooping, Technical Trading Rule Performance, and the Bootstrap
In this paper we utilize White's Reality Check bootstrap methodology (White (1999)) 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 comprehensive test of performance across all technical trading rules examined. 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. Copyright The American Finance Association 1999.
Year of publication: |
1999
|
---|---|
Authors: | Sullivan, Ryan ; Timmermann, Allan ; White, Halbert |
Published in: |
Journal of Finance. - American Finance Association - AFA, ISSN 1540-6261. - Vol. 54.1999, 5, p. 1647-1691
|
Publisher: |
American Finance Association - AFA |
Saved in:
Saved in favorites
Similar items by person
-
Forecast evaluation with shared data sets
Sullivan, Ryan, (2003)
-
ARTICLES - Data-Snooping, Technical Trading Rule Performance, and the Bootstrap
Sullivan, Ryan, (1999)
-
The Dangers of Data-Driven Inference: The Case of Calendar Effects in Stock Returns
Timmermann, Allan, (1998)
- More ...