Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias

Po-Hsuan Hsu, Yu-Chin Hsu and Chung-Ming Kuan ()

Journal of Empirical Finance, 2010, vol. 17, issue 3, 471-484

Abstract: In the finance literature, statistical inferences for large-scale testing problems usually suffer from data snooping bias. In this paper we extend the "superior predictive ability" (SPA) test of Hansen (2005, JBES) to a stepwise SPA test that can identify predictive models without potential data snooping bias. It is shown analytically and by simulations that the stepwise SPA test is more powerful than the stepwise Reality Check test of Romano and Wolf (2005, Econometrica). We then apply the proposed test to examine the predictive ability of technical trading rules based on the data of growth and emerging market indices and their exchange traded funds (ETFs). It is found that technical trading rules have significant predictive power for these markets, yet such evidence weakens after the ETFs are introduced.

Keywords: Data; snooping; Exchange; traded; funds; Reality; check; SPA; test; Stepwise; test; Technical; trading; rules (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (68)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0927-5398(10)00002-2
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:17:y:2010:i:3:p:471-484

Access Statistics for this article

Journal of Empirical Finance is currently edited by R. T. Baillie, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff

More articles in Journal of Empirical Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().