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

Date01 August 2017
Published date01 August 2017
AuthorLicheng Sun,Mohammad Najand,Liang Meng
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
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:
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.
C2017 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
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

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