Stock Return Serial Dependence and Out-of-Sample Portfolio Performance

71 Pages Posted: 17 Mar 2010 Last revised: 14 Nov 2013

Victor DeMiguel

London Business School

Francisco J. Nogales

Universidad Carlos III de Madrid - Department of Statistics; Institute of Financial Big Data UC3M-BS

Raman Uppal

EDHEC Business School; Centre for Economic Policy Research (CEPR)

Multiple version iconThere are 2 versions of this paper

Date Written: April 22, 2013

Abstract

We study whether investors can exploit serial dependence in stock returns to improve out-of-sample portfolio performance. We show that a vector-autoregressive (VAR) model captures stock return serial dependence in a statistically significant manner. Analytically, we demonstrate that, unlike contrarian and momentum portfolios, an arbitrage portfolio based on the VAR model attains positive expected returns regardless of the sign of asset return cross-covariances and autocovariances. Empirically, we show, however, that both the arbitrage and mean-variance portfolios based on the VAR model outperform the traditional unconditional portfolios only for transaction costs below ten basis points.

JEL Classification: G11

Suggested Citation

DeMiguel, Victor and Nogales, Francisco J. and Uppal , Raman, Stock Return Serial Dependence and Out-of-Sample Portfolio Performance (April 22, 2013). AFA 2011 Denver Meetings Paper. Available at SSRN: https://ssrn.com/abstract=1572526 or http://dx.doi.org/10.2139/ssrn.1572526

Victor DeMiguel (Contact Author)

London Business School ( email )

Sussex Place
Regent's Park
London, London NW1 4SA
United Kingdom

Francisco J. Nogales

Universidad Carlos III de Madrid - Department of Statistics ( email )

Avda. de la Universidad, 30
Leganes, Madrid 28911
Spain
+34 916248773 (Phone)

HOME PAGE: http://www.est.uc3m.es/Nogales

Institute of Financial Big Data UC3M-BS ( email )

CL. de Madrid 126
Madrid, Madrid 28903
Spain

Raman Uppal

EDHEC Business School ( email )

58 rue du Port
Lille, 59046
France

Centre for Economic Policy Research (CEPR)

90-98 Goswell Road
London, EC1V 7RR
United Kingdom

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