Testing Lead-Lag Effects under Game-Theoretic Efficient Market Hypotheses

36 Pages Posted: 20 Mar 2007 Last revised: 30 Apr 2010

See all articles by Wei Wu

Wei Wu

Cal Poly Pomona

Glenn Shafer

Rutgers, The State University of New Jersey - Accounting & Information Systems

Date Written: January 20, 2010

Abstract

A game-theoretic efficient market hypothesis says that a trading strategy will not multiply the capital it risks substantially relative to a specified market index. This implies that the autocorrelation of returns with respect to the index will be small and that a signal x will have approximately the same lead-lag effect on all traded securities. These predictions do not depend on assumptions about probabilities and preferences. Instead they rely on the game-theoretic framework introduced by Shafer and Vovk in 2001, which unifies statistical testing with the notion of a trading strategy that risks only a fixed capital. In this framework, we reject market efficiency at significance level alpha when the capital risked is multiplied by 1/alpha or more. This approach identifies the same anomalies as the conventional approach: statistical significance for the autocorrelations of small-cap portfolios and equal-weighted indices, as well as for the ability of other portfolios to lead them. Because it bases statistical significance directly on trading strategies, the approach allows us to measure the degree of market friction needed to account for this statistical significance. We find that market frictions provide adequate explanation.

Keywords: Efficient Market Hypothesis, Game Theoretic, Lead-Lag, Correlations, Stock Returns

JEL Classification: C72, C12, G14

Suggested Citation

Wu, Wei and Shafer, Glenn, Testing Lead-Lag Effects under Game-Theoretic Efficient Market Hypotheses (January 20, 2010). Available at SSRN: https://ssrn.com/abstract=972743 or http://dx.doi.org/10.2139/ssrn.972743

Wei Wu (Contact Author)

Cal Poly Pomona ( email )

3801 W Temple Ave
Pomona, CA 91768
United States

Glenn Shafer

Rutgers, The State University of New Jersey - Accounting & Information Systems ( email )

180 University Avenue
Newark, NJ 07102
United States
973-353-1604 (Phone)

HOME PAGE: http://www.glennshafer.com

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
311
Abstract Views
1,749
rank
125,335
PlumX Metrics