Momentum Strategies and Investor Sentiment in the REIT Market

Date01 March 2016
Published date01 March 2016
DOIhttp://doi.org/10.1111/irfi.12060
Momentum Strategies and Investor
Sentiment in the REIT Market*
YING HAO,HSIANG-HUI CHU,KUAN-CHENG KOAND LIN LIN
School of Economics and Business Administration, Chongqing University,
Chongqing, China and
Department of Banking and Finance, National Chi Nan University, Puli, Taiwan
ABSTRACT
Comparing across three momentum measures, we empirically find that the
52-week high strategy plays a dominant role in generating momentum
profits in the Real Estate Investment Trust (REIT) market. The profitability of
the 52-week high strategy, however, varies with the state of investor senti-
ment. Specifically, we find that the 52-week high momentum earns signifi-
cantly positive returns following optimistic periods and significantly
negative returns following pessimistic periods. Further evidence indicates
that investor sentiment serves as a better predictive variable in explaining the
REIT momentum than market states, business cycles, legislation changes,
and monetary policy changes. Overall, our findings are in line with behav-
ioral theories in explaining the REIT momentum.
JEL classification: G11; G12; G14
I. INTRODUCTION
Starting from the seminal work of Jegadeesh and Titman (1993), the momen-
tum premium that involves buying past winner stocks and short selling past
loser stocks is one of the most pronounced and prevalent anomalies docu-
mented in asset-pricing literature. In addition to the equity market, the profit-
ability of the momentum strategy has been extensively investigated in several
financial markets, including foreign currency (Okunev and White 2003; Chong
and Ip 2009; Menkhoff et al. 2012), commodity (Miffre and Rallis 2007; Gorton
et al. 2013), corporate bond (Gebhardt et al. 2005; Jostova et al. 2013), Ameri-
can depositary receipts (Parhizgari and Nguyen 2008), residential real estate
(Beracha and Skiba 2011), and Real Estate Investment Trust (REIT) markets
(Chui et al. 2003a, 2003b; Hung and Glascock 2008, 2010; Derwall et al. 2009;
* We are especially indebted to the anonymous referee, Hong Yan (the editor) and Stephen H.
Penman, for their valuable comments that significantly enrich the content of the paper. YingHao
acknowledges financial support from the National Natural Science Foundation of China (grant
numbers: 71372137, 71232004, and 70902030) and the Fundamental Research Funds for the
Central Universities of China (grant number: CD JSK11002). Kuan-Cheng Ko acknowledges
financial support from the Ministry of Science and Technology of Taiwan (grant number: MOST
103-2410-H-260-005-MY3). We are responsible for any remaining errors.
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DOI: 10.1111/irfi.12060
© 2015 International Review of Finance Ltd. 2015
International Review of Finance, 16:1, 2016: pp. 41–71
Simon 2009). In particular, Chui et al. (2003a) find that Jegadeesh and Titman’s
price momentum generates significantly positive returns in the REIT market
from 1982 to 2000, and that the profitability is more significant during the
1993–2000 period.
Despite the soundness of momentum profits in the REIT market, the inves-
tigation of the sources behind this phenomenon has drawn little attention in
the literature. The first objective of this paper is to examine this issue by
comparing the relative performance of three momentum strategies that are
associated with different behavioral theories in the REIT market. The momen-
tum strategies of our interest include Jegadeesh and Titman’s (1993) price
momentum, George and Hwang’s (2004) 52-week high momentum, and Blitz
et al.’s (2011) residual momentum.
Jegadeesh and Titman’s (1993) price momentum is perhaps the most popular
trading strategy documented in the literature. Hong and Stein’s (1999) infor-
mation diffusion theory and Daniel et al.’s (1998) overconfidence hypothesis
are important behavioral theories to underpin the profitability of this strategy.
In particular, Hong and Stein show that momentum returns can be generated by
investors’ under-reaction to information, whereas Daniel et al. incorporate
overconfidence and self-attribution biases to describe the patterns of momen-
tum returns.
Motivated by the theory of adjustment and anchoring biases proposed by
Kahneman and Tversky (1979) and Kahneman et al. (1982), George and Hwang
(2004) construct an alternative momentum strategy based on the nearness of
stocks’ current prices to their 52-week high prices. The strategy is constructed by
buying stocks with current prices close to their past 52-week high prices and
short selling stocks with current prices far from their past 52-week high prices.
They argue that the return continuation arises because of investors’ misreaction
to individual stocks’ information conditional on their 52-week high prices. We
include the 52-week high strategy because Northcraft and Neale (1987) and
Lambson et al. (2004) suggest that investors are likely to be subject to the
anchoring bias in the real estate market.
Blitz et al. (2011), on the other hand, extend the information diffusion
theory of Hong and Stein (1999) and argue that investors are more likely to
under-react to firm-specific information than to public price information. They
propose the residual momentum strategy by ranking stocks according to their
residual returns estimated using the Fama and French (1993) three-factor model
and document that it generates higher risk-adjusted momentum returns and
higher Sharpe ratios than Jegadeesh and Titman’s (1993) price momentum. We
include the residual momentum strategy because Ooi et al. (2009) find that
idiosyncratic risk matters in REIT pricing. The 52-week high momentum and
the residual momentum are both demonstrated to be profitable in the equity
market, but they have yet been applied to the REIT market.
We first investigate the sources of the REIT momentum by comparing the
relative performance of the three aforementioned strategies based on a sample
of all US REITs over the sample period from January 1978 to December 2011. We
International Review of Finance
© 2015 International Review of Finance Ltd. 2015
42

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