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

64 Pages Posted: 2 May 2013

See all articles by Victor DeMiguel

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 2013

Abstract

We study whether investors can exploit stock return serial dependence to improve out-of- sample portfolio performance. To do this, we first show that a vector-autoregressive (VAR) model estimated with ridge regression captures daily stock return serial dependence in a stable manner. Second, we characterize (analytically and empirically) expected returns of VAR-based arbitrage portfolios, and show that they compare favorably to those of existing arbitrage portfolios. Third, we evaluate the performance of VAR-based investment (positive-cost) portfolios. We show that, subject to a suitable norm constraint, these portfolios outperform the traditional (unconditional) portfolios for transaction costs below 10 basis points.

Keywords: out-of-sample performance, portfolio choice, Serial dependence, vector autoregression

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 2013). CEPR Discussion Paper No. DP9456, Available at SSRN: https://ssrn.com/abstract=2258944

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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