The Role of U.S. Market on International Risk‐Return Tradeoff Relations

• Date: 01 August 2017
• Published date: 01 August 2017
• DOI: http://doi.org/10.1111/fire.12139

The Financial Review 52 (2017) 499–526

The Role of U.S. Market on International

Risk-Return Tradeoff Relations

Licheng Sun∗, Liang Meng, and Mohammad Najand

Old Dominion University

Abstract

We study the intertemporal risk-return tradeoff relations based on returns from 18 inter-

national markets. We find striking new empirical evidence that the inclusion of U.S. market

returns significantly changes the estimated risk-return tradeoff relations in international mar-

kets from mostly negativeto predominantly positive. Our results are consistent with the lead-lag

effect between U.S. and international markets in the sense of Rapach, Strauss and Zhou.

Keywords: risk-return tradeoff, international markets, intertemporal CAPM, lead-lag effect,

multivariate GARCH-in-Mean

JEL Classifications: G11, G12, G15

1. Introduction

We investigate the risk-return tradeoff relation in the context of international

markets. Although a positive tradeoff relation between risk and return is probably

one of most widely taught principles in finance, empirically the sign of this relation

is ambiguous. Over the past several decades, numerous studies have estimated the

∗Corresponding author: Strome College of Business, Old Dominion University, Norfolk, VA 23456;

Phone: (757) 683-6552; Fax: (757) 683-3258; E-mail: lsun@odu.edu.

We thank David Selover, seminar participants at Old Dominion University, the journal editor, and two

anonymous referees for helpful comments. Wealso thankKathy Mikell for editorial assistance.

C2017 The Eastern Finance Association 499

500 L. Sun et al./The Financial Review 52 (2017) 499–526

relation between risk and return using the U.S. stock market returns. However, the

results are mixed. For example, French, Schwert and Stambaugh (1987) findevidence

of a positive relation, but Glosten, Jagannathan and Runkle (1993) (GJR) show a

negative relation. Hence, the risk-return tradeoff relation remains an interesting but

unresolved puzzle.

Most researchers conjecture that the inconclusive results are likely due to model

misspecifications. Many studies have attempted to identify the correct specifications

for the expected returns. For example, Pastor,Sinha and Swaminathan (2008) use the

implied cost of capital (ICC) derived from earnings forecasts to proxy for expected

stock returns. They find a positiverelation between the conditional mean and variance

of stock returns. Guo and Whitelaw (2006) estimate an empirical model that separately

identifies two components of expected returns: the risk component and the component

due to the desire to hedge changes in investmentopportunities. They find that expected

returns are driven primarily by the hedge component, and the estimated risk-return

relation is positive. Anderson, Ghysels and Juergens (2009) study asset pricing in

economies featuring both risk and uncertainty. They measure uncertainty via the

disagreement among professional forecasters and find evidence for an uncertainty-

return tradeoff.

Other researchers focus on the misspecification of the conditional variance. For

instance, Harvey (2001, p. 573) concludes that “the relation between the conditional

mean and variance depends on the specification of the conditional variance.”Ghysels,

Santa-Clara and Valkanov (2005) introduce a mixed data sampling (MIDAS) estima-

tor for the conditional variance that forecasts monthly variancewith past daily squared

returns and find a significantly positive relation between risk and return. Brandt and

Kang (2004) find a strong negative relation using the latent vector autoregression

(VAR) approach.

Some researchers argue that the nebulous risk-return relation found in the lit-

erature could be due to a regime-dependent risk-aversion parameter. It is certainly

plausible that changes in the state of an economy could result in time variations in

investors’ risk tolerance. For example, Nyberg (2012) introduces regime-switching

dynamics into the benchmark GARCH-in-Mean model by augmenting it with an

autoregressive probit model. Nyberg (2012, p. 137) estimates the model with U.S.

stock returns and concludes that “there is a positive risk-return relationship between

volatility and expected return independent of the state of the economy.” Ghysels,

Guerin and Marcellino (2014) estimate a regime-switching MIDAS model with

U.S. market returns in a univariate setting. They identify two regimes and find that

the positive risk-return relation only shows up in the low-volatility and high-return

regime.

In contrast to the voluminous amount of research based on the U.S. market

data, there are relatively fewer studies that examine international evidence on the

risk-return tradeoff relation. For example, Pastor, Sinha and Swaminathan (2008)

apply their ICC approach to the G-7 countries. However, due to data limitation,

their sample periods are relatively short: 1981–2002 for the United States and