Sentiment-Induced Institutional Trading Behavior and Asset Pricing in Securitized Real Estate Markets

Abstract

Institutional investors such as pension funds or insurance companies commonly invest in the unsecuritized and securitized real estate market. We investigate how institutional investor sentiment in the inefficient commercial real estate market affects institutional trading behavior in the REIT market and subsequently asset pricing. In particular, we test two alternative theories - flight to liquidity and style investing theory - to explain the sentiment-induced trading behavior of institutional investors in the REIT market for the pre-crisis (2002-2006), crisis (2007-2009) and post-crisis (2010-2012) period. We find that the applicability of either theory depends on economic conditions. In the pre-crisis period institutional investors switched capital in and out of REITs based on their sentiment in the private market (style investing). However, in the crisis period institutional investors switched capital from the illiquid private market to the more liquid REIT market (flight to liquidity). The flight to liquid REITs continues into the post-crisis to a lesser extent and suggests that the financial crisis has changed institutional investment behavior. Our findings hold across different groups of REITs (e.g. high and low institutional ownership, S&P and non-S&P REITs) and property types. We also find that institutional real estate investor sentiment introduces a non-fundamental component into REIT pricing.

Full text

Sentiment-Induced Institutional Trading Behavior and
Asset Pricing in Securitized Real Estate Markets
By
Prashant K. Das1
Julia Freybote2
Gianluca Marcato3
ABSTRACT
Institutional investors such as pension funds or insurance companies commonly invest in the
unsecuritized and securitized real estate market. We investigate how institutional investor
sentiment in the inefficient commercial real estate market affects institutional trading
behavior in the REIT market and subsequently asset pricing. In particular, we test two
alternative theories - flight to liquidity and style investing theory - to explain the sentiment-
induced trading behavior of institutional investors in the REIT market for the pre-crisis
(2002-2006), crisis (2007-2009) and post-crisis (2010-2012) period. We find that the
applicability of either theory depends on economic conditions. In the pre-crisis period
institutional investors switched capital in and out of REITs based on their sentiment in the
private market (style investing). However, in the crisis period institutional investors switched
capital from the illiquid private market to the more liquid REIT market (flight to liquidity).
The flight to liquid REITs continues into the post-crisis to a lesser extent and suggests that
the financial crisis has changed institutional investment behavior. Our findings hold across
different groups of REITs (e.g. high and low institutional ownership, S&P and non-S&P
REITs) and property types. We also find that institutional real estate investor sentiment
introduces a non-fundamental component into REIT pricing.
Keywords: Institutional investor sentiment, flight to liquidity theory, style investing,
asset pricing, real estate
1 Ecole Hôtelière de Lausanne, Lausanne, Switzerland; prashant.pkd@gmail.com
2 [Corresponding Author] Center for Real Estate, Portland State University, Portland, USA;
freybote@pdx.edu
3 Henley Business School, University of Reading, Reading, UK; g.marcato@henley.reading.ac.uk

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1. Introduction
Over the last couple of decades a number of studies have shown that fundamentals are not
sufficient to explain the comovement of asset returns (e.g. Barberis, Shleifer and Wurgler, 2005;
Pindyck and Rotemberg, 1993, 1990; Shiller, 1989). Investor sentiment has been identified as an
additional driver of comovement of assets that either form a category or are in the habitat of a
particular investor type (Barberis, Schleifer and Wurgler, 2005). The majority of studies
investigating sentiment-induced comovement focuses on the stock market and neglect assets that
are simultaneously traded in securitized and unsecuritized markets. However, particularly these
assets represent a unique laboratory to understand the role of investor sentiment in the
comovement of assets across and within asset categories, classes and markets.
Real estate represents an asset class for which securitized and unsecuritized markets coexist.
Both markets are used by institutional investors to obtain exposure to the “real estate category”
and provide data about transaction activity, returns and investor sentiment. Institutional real
estate investors commonly invest in real estate via direct investments in buildings and publicly
traded real estate investment trusts (REITs; Dhar and Goetzmann, 2006; Clayton and
MacKinnon, 2003a; Ciochetti et al., 2002). Exposure to the private real estate market provides
institutional investors with an information advantage about fundamentals when they trade REITs,
whose pricing is ultimately driven by underlying asset values (Graff and Young, 1997).
However, it also makes them susceptible to irrational sentiment, which is recognized to be an
important component of investor decision-making in the highly intransparent, informationally

3
inefficient and segmented commercial real estate market (Gallimore and Gray, 2002). As a
consequence, the following two questions arise:
 How does institutional investor sentiment in the inefficient unsecuritized market affect
institutional investor trading in the securitized market?
 How does institutional investor sentiment affect asset pricing in the securitized market?
The real estate laboratory offers a unique opportunity to assess the impact of sentiment in the
inefficient unsecuritized market on institutional trading behavior and asset pricing decisions in
the securitized market. In this study, we investigate this relationship over the period of 2002 to
2012 by testing the applicability of the style investing and flight to liquidity theory, which are
two alternative sentiment-based theories of comovement (Baker and Wurgler, 2007; Barberis,
Schleifer and Wurgler, 2005). In particular, we test the explanatory power of the two theories for
different periods: pre-crisis (2002 to 2006), crisis (2007 to 2009) and post-crisis (2010 to 2012).
These periods are motivated by the findings of Devos et al. (2013) who show that institutional
investment preferences in REITs changed around the most recent financial crisis.
The style investing theory predicts a capital switching in and out of the “real estate category”,
which includes securitized real estate assets (e.g. REIT stocks) and unsecuritized real estate
assets (e.g. commercial real estate), based on the sentiment of institutional investors in the
underlying private market. The flight to liquidity theory predicts a sentiment-induced capital
switching from illiquid unsecuritized investments to more liquid securitized assets due to
perceived liquidity risk. Previous studies provide evidence for both an institutional style
investing in REITs (Ambrose, Lee and Peek, 2007; Graff and Young, 1997) as well as a flight to

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quality/liquidity within the REIT market (Devos et al., 2013) or capital switching between REIT
and commercial real estate market (Lee, Lee and Chiang, 2008). The purpose of our study is to
combine the extensive literatures on style investing, coupled with institutional herding behavior,
and flight to liquidity/quality to explain the effect of sentiment in the unsecurititized real estate
market on institutional REIT trading behavior and create a link between the findings of these
earlier studies.
We also analyze whether institutional investor sentiment in the unsecuritized market adds a
component delinked from fundamentals into asset pricing in the securitized market in line with
the investor sentiment literature (e.g. Baker and Wurgler, 2007; Barberis, Shleifer and Wurgler,
2005; Barberis and Shleifer, 2003; De Long et al. 1990, 1989) and institutional investor herding
literature (e.g. Choi and Sias, 2009; Sias, 2004; Nofsinger and Sias, 1999).
We find evidence for the applicability of both theories, albeit at different points in time,
characterized by different economic conditions. In the pre-crisis period from 2002 to 2006, the
sentiment-driven REIT trading behavior of institutional investors is best explained by style
investing suggesting that institutional investors switched capital in and out of the real estate
category based on their unsecuritized market sentiment. However, during the financial crisis
from 2007 to 2009, the flight to liquidity theory best explains institutional trading behavior in the
securitized market (i.e. REITs), suggesting a sentiment-induced capital switching from the
illiquid unsecuritized to the more liquid securitized market to adjust portfolio weights within the
real estate category. The flight to liquidity theory also best explains the effect of private market
sentiment on institutional trading in the REIT market in the post-crisis period from 2010 to 2012,

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which suggests that the financial crisis has changed institutional investment behavior. Our
findings are in line with Devos et al. (2013) and complement this earlier study by providing
evidence that an institutional flight to quality/liquidity does not only exist within the REIT
market, but also between the unsecuritized and securitized real estate market. Our results hold for
securities forming the habitat of institutional investors (i.e. REITs included in the S&P500 index
and with high institutional ownership), securities forming the habitat of individual investors (i.e.
REITs not included in the S&P index and with low institutional ownership) and across REITs
with different property type specializations. Additionally, we find that the sentiment of
institutional investors in the unsecuritized market affects asset pricing in the securitized market.
Our study contributes to the style investing, herding and flight to liquidity/quality literatures as
follows. Firstly, we provide empirical evidence that institutions not only style invest across
different types of stocks, but also across the securitized and unsecuritized real estate market. We
also show that investor sentiment in the inefficient unsecuritized market affects institutional
investment across the real estate category and asset pricing decisions in the securitized market.
Thus, there appears to be a spillover of sentiment between markets within the same asset
category. Secondly, we provide evidence that the flight to liquidity/quality theory is not only
applicable to the stock market or stock & bond market, but also to the unsecuritized and
securitized real estate market. Lastly, our results suggest that the flight to liquidity and style
investing theory are complements, depending on economic conditions.
Furthermore, our study contributes to the existing literature on investor sentiment in private and
public real estate markets. With the exception of Ling, Naranjo and Scheick (2013), previous

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REIT investor sentiment studies focus on individual investors (Lin, Rahman and Yung, 2009;
Chiang and Lee, 2009; Clayton and MacKinnon, 2003a; Barkham and Ward, 1999).
Traditionally, institutional investors have been considered to behave rationally and trade on
expectations about fundamentals (Anand, Chakravarty and Martell, 2005; Brown and Cliff,
2004; Barberis and Shleifer, 2003; De Long et al. 1990, 1989). However, previous studies on
institutional herding and momentum trading in REIT and non-REIT stocks (e.g. Ro and
Gallimore, 2013; Sias, 2004; Badrinath and Wahal, 2002; Nofsinger and Sias, 1999) suggest that
institutional investment decisions may not be entirely based on rational expectations about the
future. The focus on institutional investors is particularly relevant, as institutional ownership in
REITs has been continuously increasing since the beginning of the new “REIT era”, which
allows more investment flexibility (Devos et al., 2013; Lee, Lee and Chiang, 2008; Clayton and
MacKinnon, 2003b; Below, Stansell and Coffin, 2000; Graff and Young, 1997). Our study also
complements previous studies such as Below, Stansell and Coffin (2000), who investigate
fundamentals-based determinants of institutional demand in REIT stocks in line with traditional
capital asset pricing theory, by analyzing behavioral determinants of institutional investor
demand for REITs.
The remainder of the paper is structured as follows: the next section discusses our theoretical
foundation presenting a literature review. We then describe the data and methodology used in
our study. Finally, we present our main results for both institutional REIT trading and pricing,
followed by our conclusion.

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2. Literature Review
Alongside more traditional asset pricing theory, a growing stream of literature finds that
underlying fundamentals are not sufficient to explain the excess comovement of different assets
(Barberis, Shleifer and Wurgler, 2005; Pindyck and Rotemberg, 1993, 1990; Shiller, 1989).
Sentiment-based theories such as the category (style investing) and habitat theory offer
alternative and behavioral explanations for how investor sentiment affects the comovement of
asset returns (Barberis, Shleifer and Wurgler, 2005). Barberis and Shleifer (2003) refer to a
category or “style” to define a group of risky assets that investors treat homogeneously and
hence do not consider competing in their demand function. After combining assets into broader
classes, investors then make portfolio allocation decisions at the category level instead of the
individual asset level (“style investing”). In particular, investors categorize assets into
superordinate styles and allocate funds to these categories based on the category’s past
performance relative to other categories. If a category has a relatively superior performance to
others, switchers withdraw funds from underperforming categories and invest them in this
overperforming category. As a consequence, regardless of cash flows, which may be either
highly (e.g. utilities stocks) or weakly correlated (e.g. closed end funds), assets within the same
category tend to comove (Barberis and Shleifer, 2003). Empirical evidence for the category
theory (style investing) has been found, for example, in “Siamese twins” companies traded in
different markets (Froot and Dabora, 1999), commodities (Pindyck and Rotemberg, 1990),
stocks in the same index (Barberis, Shleifer and Wurgler, 2005; Chen and Bondt, 2004),
companies of the same size but different lines of business (Pindyck and Rotemberg, 1993),
Morningstar categories (Teo and Woo, 2004), stocks with similar prices (Green and Hwang,

8
2009), and stocks with other similar characteristics (Wahal and Yavuz, 2013; Baker and
Wurgler, 2006). Investigating the comovement of two overlapping stock market categories
(REITs and S&P index stocks), Ambrose, Lee and Peek (2007) find that after certain REITs
were added to the S&P indices, both “index” and “non-index” REITs comove with the S&P
index stocks. Furthermore, institutional investors in particular have been found to herd from and
to styles, for example, with regard to stock portfolios of particular characteristics (e.g. growth
stocks or market capitalization) and industries (Choi and Sias, 2009; Froot and Teo, 2008).
A number of studies find that unsecuritized and securitized real estate returns comove (Pagliari,
Scherer and Monopoli, 2005; Myer and Webb, 1993; Giliberto, 1990). Pagliari, Scherer and
Monopoli (2005) argue that public and private real estate are interchangeable from a portfolio
management perspective. This suggests the existence of a “real estate category”, based on the
real estate industry, in which investors style-invest in line with Choi and Sias (2009). Graff and
Young (1997) present evidence that institutional investors herd in and out of REIT stocks, based
on the performance of the underlying commercial real estate market. If institutional investors
indeed style-invest in the real estate category, we expect a positive relationship between the
sentiment of institutional investors in the private market and their trading behavior in the public
market.
The flight to liquidity theory, which has evolved from the noise-trader or habitat theory, offers an
alternative explanation for sentiment-induced REIT trading of institutional investors. According
to this theory (Lee, Shleifer and Thaler, 1991; De Long et al., 1989, 1990) noise trading by
individual investors increases the systematic risk of assets that are in the preferred habitat of

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individual investors and exposes rational investors to an additional risk delinked from
fundamentals that cannot be arbitraged away. For real estate, the noise-trader theory has been
empirically supported by a number of studies on individual investor sentiment in REITs (Lin,
Rahman and Yung, 2009; Chiang and Lee, 2009; Clayton and MacKinnon, 2003a; Barkham and
Ward, 1999).
However, Baker and Wurgler (2007) argue that noise trading also results in a flight to quality
within the stock market. For example, in times of high sentiment characterized by increased
volatility due to higher noise trading (Yu and Yuan, 2011), some investors move away from
small, high growth and more volatile stocks whose prices are often driven by irrational
sentiment, towards safe, more “bond-like” stocks, whose prices are less likely to be affected by
sentiment. Amihud, Mendelson and Wood (1990) suggest that the flight to quality should be
interpreted as a flight to liquidity. A number of studies provide empirical support for the flight to
quality/liquidity theory within and across asset markets such as the bond and stock market
(Goyenko and Ukhov, 2009; Brunnermeier and Pedersen, 2009; Beber, Brandt and Kavajecz,
2008; Acharya and Pedersen, 2005; Vayanos, 2004; Ilmanen, 2003).
With regard to the REIT market, Devos et al. (2013) find that institutional investments depend
on REIT performance and economic conditions. The financial crisis led to a flight to quality of
institutional REIT investors towards lower risk REITs, which lead to an increase in institutional
ownership in older and larger REITs in the post-crisis period. These REITs have been
traditionally the habitat of institutional investors (Below, Stansell and Coffin, 2000). During the
crisis, institutional investors exhibited a preference for REITs with higher turnover. As stocks

10
with high turnover can be considered more liquid (Baker and Stein, 2004), this finding suggests a
flight to liquidity within the REIT market.
An important characteristic of institutional real estate investors is their high sensitivity to
illiquidity risk in the unsecuritized real estate market (Dhar and Goetzmann, 2006) and hence
their preference for more liquid securitized real estate assets (Ciochetti, Craft and Shilling,
2002). Liquidity is an important distinction between these two forms of real estate investment
(Pagliari, Scherer and Monopoli, 2005). Clayton and MacKinnon (2003a) find that the liquidity
premium in REIT prices relative to net asset values is related to the liquidity of the underlying
commercial real estate market. Additionally, institutional investors have also been found to
consider unsecuritized and securitized real estate as substitutes and switch their investments
(capital) between these two markets (Lee, Lee and Chiang, 2008). As a consequence, if
institutional investors switch capital from the illiquid unsecuritized to the more liquid securitized
real estate market (flight to liquidity), we expect a negative relationship between the sentiment of
institutional investors in the private market and their trading behavior in the public market.
3. Data Description
Institutional Investor Sentiment for Private Real Estate
In the investor sentiment literature, sentiment is measured with either the closed end fund
discount (CEFD), surveys or cash flow imbalances/trading activity. Previous studies on REIT
investor sentiment predominantly employ the CEFD or discount to net asset value approach,

11
which however, is inappropriate for our investigation for a number of reasons. The indirect
CEFD measure does not allow us to isolate institutional investor sentiment and also has been
found to proxy primarily for individual investor sentiment (De Long and Shleifer, 1992; Lee,
Shleifer and Thaler, 1991). Findings about the appropriateness of the CEFD measure as investor
sentiment proxy furthermore have been mixed in the finance literature (Gemmill and Thomas,
2002; Neal and Wheatley, 1998; Doukas and Milonas, 2004; Sias, Starks and Tinic 2001; Elton,
Gruber and Busse 1998; Chen, Kan and Miller, 1993).
To measure the sentiment of institutional investors in the unsecuritized commercial real estate
market, we follow Ling, Naranjo and Scheick (2013) and Clayton, Ling and Naranjo (2009) and
employ a survey-based measure, which is based on data from the Real Estate Research
Corporation (RERC) over the period of Q1/2002 to Q2/2012. The RERC surveys institutional
investors such as pension funds, insurance companies or investment managers involved in the
commercial real estate market on a quarterly basis. Respondents are asked to provide information
such as expectations about yields, growth rates and investment conditions in all major
commercial real estate market segments (office, industrial, retail, apartment and hotel).
In particular, we focus on the rankings of current investment conditions for office, industrial,
retail, apartment and hotel. Respondents are asked to rate the current investment conditions from
“poor” (1) to “excellent” (10). These rankings are direct measures of investor sentiment in the
unsecuritized real estate market as they represent the expectations of market participants for the
future (Clayton, Ling and Naranjo, 2009). For office, industrial and retail, current investment
conditions are reported for more than one segment (e.g. office CBD and office suburban). As a

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consequence, we use principal components analysis (oblimin rotation) to extract a common
factor or score for each property type with more than one segment. In particular, we retain the
eigenvector with the highest eigenvalue (principal component), which is able to explain the
largest variance in the respective data. For diversified REITs, we use a common factor derived
from the investment conditions for all property types as sentiment measure. Our approach
follows Ling, Naranjo and Scheick (2013). We then match the respective RERC sentiment score
to REITs based on property type, e.g. we use the RERC retail sentiment score for REITs
specializing in retail.
Institutional Investor Trading in REITs
We measure institutional investor trading behavior in the REIT market as buy-sell imbalance
(BSI) in line with Kumar and Lee (2006). This measure has also been used as a proxy for
investor sentiment. In our analysis, we focus on publicly traded US equity REITs specializing in
office, industrial, apartment, retail and hotel as well as diversified REITs. This focus stems from
the availability of RERC sentiment measures for these property types. We also only include
REITs traded on the NYSE in our sample, as institutional investors prefer firms listed at this
exchange (Below, Stansell and Coffin, 2000). We define BSI as follows:
(1)
where Bt (St) is the quarterly long (short) position of institutional investors in a particular REIT.
The BSI measure indicates whether institutional investors are net buyers (BSIt > 0) or net sellers
(BSIt < 0) of shares of a particular REIT. A BSI of 1 (-1) for a particular REIT suggests that
BSIt=(Bt-St)
(Bt+St)

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institutional investors only purchased (sold) this REIT’s shares in a particular quarter. A BSI of
less that 1 or more than -1 indicates that institutional investors varied in their investment and
divestment in shares of a particular REIT, i.e. some investors purchased stocks while others sold
them in the same quarter.
To calculate the institutional investor BSI, we obtain information about institutional trading of
individual REITs from the Institutional (13f) Holdings database (s34) in Thomson Reuters for
the period of Q1/2002 to Q2/2012. Institutional investors covered by this dataset are pension
funds, banks, insurance companies, parent companies of mutual funds and other institutions such
as endowment funds. For each quarter, we derive the aggregated net change in the holdings of a
particular REIT by institutional investors (Bt-St) and aggregated total institutional investor
trading volume of that REIT (aggregated absolute net change, Bt+St).
One shortcoming of the Thomson Reuters 13f data for our investigation is that it combines
institutions invested in the unsecuritized and securitized market (pension funds, banks, insurance
companies) with institutions that do not directly invest in real estate (mutual funds), but heavily
invest in REITs (Devos et al., 2013). To control for the REIT trading of mutual funds, we derive
a mutual fund BSI based on equation 1 and data from the Mutual Fund Holdings database (s12)
in Thomson Reuters. While the Institutional (13f) Holdings database includes aggregated mutual
fund trading at the parent company level, the Mutual Fund Holdings database includes
disaggregated trading by individual mutual funds. As the BSI measures are based on aggregated
trading activity, these differences are irrelevant to our empirical analysis.

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Liquidity Control Measures
Institutional investors are highly sensitive to the liquidity risk of commercial real estate (Dhar
and Goetzmann, 2006). Clayton and MacKinnon (2003a) find that investor sentiment is
important to REIT pricing even after accounting for REIT and private market liquidity.
Additionally, an extensive body of literature provides evidence for the importance of liquidity to
asset pricing in the stock market (Liu, 2006; Acharya and Pedersen, 2005; Pastor and
Stambaugh, 2003; Amihud, 2002; Amihud and Mendelson, 1986). In our empirical analysis, we
control for the liquidity of individual REIT stocks and REIT market by using the Amihud (2002)
illiquidity measure as shown in equation 2. We also employ a modified Amihud (2002) measure
to control for private market illiquidity. This modified measure allows the computation of the
Amihud (2002) measure for private real estate, where information on daily pricing at index level
is not available:
(2)
where ILLIQ is the illiquidity of a REIT stock or property type i in period y, R is the absolute
return and VOL the trading volume. To calculate the illiquidity measure for different commercial
property markets from Q1/2002 to Q2/2012, we obtain the quarterly property type-specific
NCREIF transaction based index (NTBI) total return (in absolute terms) and divide it by the
dollar-denominated trading volume, defined as quarterly property type-specific aggregate sale
price. We calculate individual stock and market illiquidity measures for REITs traded by
institutional investors over the period of Q1/2002 to Q2/2012 based on the Institutional (13f)
Holdings database (s34) in Thomson Reuters. We obtain information about quarterly REIT
ILLIQiy =|Riy |
VOLiy

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returns and total trading volume from CRSP and derive the REIT-level illiquidity measure based
on equation 2. The REIT market illiquidity measure represents a value-weighted (by market
capitalization) quarterly aggregate of the REIT-level illiquidity values. In our analysis of the
impact of institutional real estate investor sentiment on REIT pricing, we control for REIT-level
illiquidity by using the mean-adjusted Amihud (2002) measure. The mean adjustment addresses
variation in average market illiquidity over time and is derived by dividing the illiquidity
measure for an individual stock by the respective market illiquidity measure (Amihud, 2002).
Other Control Variables
Finally, to control for the impact of other fundamentals on institutional REIT trading behavior
and to isolate the effect of irrational institutional investor sentiment in the unsecuritized real
estate market, we include economic and capital market fundamentals in our model. At the macro-
economic level, we control for unemployment (UNP) by including the average quarterly
unemployment rate from the Bureau of Labor Statistics (BLS). This variable, which is negatively
related to gross domestic product (GDP; Knotek, 2007), proxies for demand for space which in
turn affects real estate prices (Brooks and Tsolacos, 1999) and has been used as a proxy for the
general state of the economy in previous studies (Bianchi and Guidolin, 2014; Fei et al., 2010).
However, we also estimated our models substituting unemployment with gross domestic product
(GDP) but results do not change. At capital market level, we control for debt capital market
conditions by including the term structure (Clayton, Ling and Naranjo, 2009) and the default risk
premium/credit spread. The term structure (TRM) is defined as the difference between the yields
of the 10-year treasury bond and 3-month treasury bill (Clayton, Ling and Naranjo, 2009). The
default risk premium (SPR) is defined as difference between yield of BAA rated corporate bond

16
and 1yr treasury bond. To control for the general stock market, we also include the return on the
S&P500 composite index from CRSP (SNP).
As the REIT industry matured and market capitalization increased, a number of REITs have been
added to Standard & Poor stock market indices such as the S&P400, 500 or 600. These stocks
represent the preferred habitat of institutional investors, as they are larger, older and less volatile.
To control for systematic differences between REITs included in S&P indices and those that are
not, we introduce a binary variable coded 1 for quarters in which a REIT was included in an
index (SPINDEX).
Lastly, we control for the level of institutional ownership in a REIT. The effect of institutional
real estate investor sentiment on trading behavior may be systematically different for stocks with
different levels of institutional and individual investor ownership. As a consequence, we obtain
the total institutional ownership as a percentage of shares outstanding from Thomson Reuters
and include INSTOWN in our analysis. In our sample 241 observations have an institutional
ownership greater than 100%, which is a well-documented issue of this database (Glushkov,
Moussawi and Palacios, 2009). We drop these observations from our sample.
An overview of our variables, their definitions, computations and data sources is provided in
Table A1 in the Appendix. Our panel dataset covers 2,357 REIT quarters for 68 REITs over the
period of Q1/2002 to Q2/2012. Summary statistics for all variables are presented in Table 1 for
the full sample and Table A2 in Appendix by period (2002-06, 2007-09 and 2010-12). The
measures for REIT and mutual fund trading behavior, BSIINST and BSIMF respectively, suggest, on
average, a net buying behavior for both type of investors over our sample period, with mutual

17
funds showing a more pronounced net buyer attitude than institutions also invested in the
unsecuritized market. The different average illiquidity measures (AMILLIQMARKET and
AMILLIQCOM) are similar if we exclude the one referring to individual REITs (AMILLIQREIT),
where a higher value can be expected. On average 40% of the REITs in our sample are included
in S&P indexes, while the average institutional ownership is around 71%. If we then turn to the
risk/return factors of the asset pricing model, we find that REITs and the equity market have
respectively performed on average 3.90% and 1.27% per quarter, while the three other factors of
the Cahart (1997) model show positive factor loadings on average.
[Insert Table 1 here]
Panel A in Table 2 presents pairwise correlations between the sentiment, liquidity and return
variables. Institutional investor sentiment in the commercial real estate market (RERCSENT) and
their trading behavior in the REIT market (BSIINST) are significantly negatively correlated. To
further assess the relationship between these two variables over time, we determine the pairwise
correlations between RERCSENT and BSIINST for the pre-crisis, crisis and post-crisis period, which
are presented in Panel B in Table 2. While the correlation coefficients are negative yet
insignificant during the pre- and post-crisis, the two variables have a significantly negative
correlation during the financial crisis (2007-2009). Thus, the more pessimistic institutional
investors were about the private real estate market, the more did they behave like net buyers in
the REIT market. Panel B suggests that the significantly negative correlation between the two
variables in Panel A is primarily driven by the crisis period. Overall, the significantly negative

18
correlation of RERCSENT and BSIINST in Table 2 provides initial evidence for the flight to liquidity
theory, at least during the financial crisis.
The relationship of BSIINST and RERCSENT over time is also graphically depicted in Figure 1,
which clearly shows the significantly negative correlation between the two variables during the
crisis years, particularly from the second quarter of 2007 to the fourth quarter of 2009.
Interestingly, Figure 1 shows a noticeable drop in the BSIINST measure, i.e. a net selling behavior
of institutional investors, between the second quarter of 2006 and the first quarter of 2007. This
may be related to a number of factors such as the end of the housing boom, stock market
conditions at this particular time or a preference of institutional investors for certain types of
unsecuritized real estate such as multi-family housing over REIT stocks, as the institutional
investor sentiment in the commercial real estate market (RERCSENT) was relatively high in this
period.
[Insert Figure 1 here]
As shown in Panel A in Table 2, the trading behavior of institutional investors in the REIT
market (BSIINST) is significantly positively correlated with the trading behavior of mutual funds
(BSIMF), the illiquidity of a particular REIT (AMILLIQREIT), the REIT market (AMILLIQMARKET)
and the commercial real estate market (AMILLIQCOM). An increase in commercial real estate
illiquidity increases the net buying behavior in the REIT market, which provides evidence for a
fundamentals-driven flight to liquidity. Additionally, the increase in institutional trading if REIT
market and individual REIT illiquidity are high appears to be in line with the findings of Devos

19
et al. (2013) that institutional investors move towards REITs with higher turnover (liquidity)
during times of economic crisis.
[Insert Table 2 here]
4. Methodology
To investigate whether the flight to liquidity or style investing theory has the highest explanatory
power for the effect of institutional real estate investor sentiment in the unsecuritized real estate
market on their REIT trading behavior, we first conduct diagnostic tests to identify unit roots and
transform non-stationary variables to remove them. We then employ a linear regression model to
our unbalanced panel dataset and regress BSIINST on RERC sentiment, illiquidity and control
variables as shown in equation 3. In our linear regression, we control for firm-fixed effects.
(3)
where BSIINST is the buy sell index for institutional investors in REITs in line with Kumar and
Lee (2006), i indexes firms and t indexes time (in quarters),  is the intercept, which controls for
firm fixed effects, and  is the error term. RERCSENT is the institutional investor sentiment in the
commercial real estate market. AMILLIQREIT, AMILLIQMARKET and AMILLIQCOM are the Amihud
(2002) illiquidity measures for individual REITs, the REIT market and the commercial real
BSIINSTi,t=
a
i+
b
1RERCSENT +
b
2AMILLIQREITi,t+
b
3AMILLIQMARKETi,t+
b
4AMILLIQCOMt+
b
5BSIMF
i,t+
b
6INSTOWNi,t+
b
7SPINDEXi,t+
b
8X+
e
i,t

20
estate market respectively. BSIMF is the buy sell index for mutual funds investing in REITs.
INSTOWN is the percentage of institutional ownership in a REIT. SPINDEX is a binary variable
coded 1 for quarters in which a REIT was included in an S&P index. X is a vector of economic
and capital market control variables (SPR, TRM, UNP and SNP).
Furthermore, to assess the impact of institutional real estate investor sentiment on REIT returns,
we regress the quarterly REIT returns on RERCSENT, the four systematic risk factors, the mean
adjusted Amihud (2002) illiquidity measure and the lags of REIT returns and RERCSENT as
shown in equation 4.
RETREITi,t=
a
+
b
1RERCSENT +
b
2MKT +
b
3SMB +
b
4HML +
b
5MOM +
b
6AMILLIQMA +
b
7lagRETREIT +
b
8lagRERCSENT +
e
i,t
(4)
where RETREIT are quarterly REIT returns, i indexes firms and t indexes time (in quarters),
RERCSENT is the institutional investor sentiment in the commercial real estate market, MKT,
SMB, HML and MOM are systematic risk factors in line with Fama and French (1993) and
Carhart (1997). AMILLIQMA is the mean adjusted Amihud (2002) illiquidity measure.
LagRETREIT and lagRERCSENT are lags of the respective variables.
5. Results for Institutional Investor Sentiment and Trading Behavior in Securitized
Markets
Table 3 presents the results for our analysis of the relationship of institutional real estate investor
sentiment (RERCSENT) and REIT trading behavior (BSIINST). In our estimation using the full

21
sample (Overall Sample column), the coefficient on RERCSENT is positive, yet insignificant.
However, this initial aggregated analysis fails to distinguish between different investor habitats
and time periods, which may explain the insignificant coefficient. To assess sentiment-induced
institutional trading in the securitized real estate market further, we conduct the following
disaggregated analyses.
[Insert Table 3 here]
Previous studies have shown that institutional investors prefer larger and older stocks (Devos et
al., 2013; Below, Stansell and Coffin, 2000; Graff and Young, 1997), which can be considered
the habitat of institutional investors. Clayton and MacKinnon (2003b) provide further support for
an institutional REIT investor habitat characterized by large cap REITs. Consequently, we
investigate the relationship of RERCSENT and BSIINST for stocks that form the institutional and
individual investor habitat. We define the institutional investor habitat as securities (i.e. REITs)
included in S&P indices (i.e. larger and older REITs) and REITs with high (above median)
institutional ownership. On the other hand, securities in the individual investor habitat are
characterized as stocks not included in S&P indices (i.e. small and medium cap REITs) and with
low (below median) institutional ownership. We then estimate our model as shown in equation 3
for each of the different investor habitats.
The results of our analysis disaggregated by investor habitat are presented in Table 3. Except for
securities with low institutional ownership, the coefficients on RERCSENT are insignificant for
S&P Index, non-S&P index and high institutional ownership REITs. These initial results suggest
that the irrational sentiment of institutional investors in the unsecuritized market has no effect on

22
their trading behavior in the securitized market within the institutional habitat. The positive
coefficient for stocks with low institutional ownership provides initial support for style investing.
An increase in optimism (pessimism) about the commercial real estate market increased the
buying (selling) behavior of institutional investors in low institutional ownership stocks. In other
words institutional investors may have decided to increase the exposure to securitized assets with
low institutional ownership to obtain more investment opportunities and pre-empt the action of
individual investors to gain profits. However, we further disaggregate our analysis by time
period and property type to assess the robustness of these results, and discuss them in the
remainder of this paper.
The coefficients on the Amihud (2002) illiquidity measures of individual REITs (AMILLIQREIT),
overall public market (AMILLIQMARKET) and private market (AMILLIQCOM) are insignificant
across all samples in Table 3. The trading behavior of mutual funds (BSIMF) has a positive
relationship with that of institutional real estate investors (BSIINST). It is beyond the scope of this
study to investigate how the trading behaviors of different types of institutional investors are
related. However, one explanation for this consistently positive and significant relationship is
herding among different institutional investors. The coefficients on the macro-economic
variables such as credit risk spread (SPR), term structure (TRM), unemployment (UNP) and
S&P500 returns (SNP) are consistent with expectations about their direction, but vary in
significance.
Devos et al. (2013) show that the preferences of institutional REIT investors have changed over
time, particularly around the most recent financial crisis. As a consequence, we estimate our

23
model for the pre-crisis (2002-2006), financial crisis (2007-2009) and post-crisis (2010-2012)
period. To identify the financial crisis period (2007 to 2009), we follow Devos et al. (2013).
[Insert Table 4 here]
Table 4 presents the results for the overall sample separated by time periods. In the pre-crisis
years, the coefficient on RERCSENT is significantly positive at the 1% level, and this provides
evidence for a style investing of institutional investors in the real estate category. If institutional
investors were irrationally optimistic (pessimistic) about the underlying private market, they
behaved like net buyers (sellers) in the securitized market. However, during the crisis period, the
relationship between RERCSENT and BSIINST changes from positive to negative, as shown by the
significantly negative coefficient on RERCSENT. Thus, the more pessimistic institutional investors
were about the unsecuritized market, the higher was the amount of securitized real estate assets
they purchased, with this result supporting the flight to liquidity theory. In the post-crisis period
from 2010 to 2012, institutional investor sentiment in the private market has a significantly
negative effect on the institutional trading behavior in securitized markets (i.e. REITs). This
result suggests a fundamental change in institutional preferences from the pre- to the post-crisis
period due to the financial crisis, in line with Devos et al. (2013).
[Insert Table 5 here]
Next we contrast stocks forming the institutional investor habitat (included in the S&P index)
with those in the individual investor habitat (not included in the S&P index) over different time

24
periods. Results are presented in Table 5. The significantly positive coefficients on RERCSENT for
the period of 2002 to 2006 provide further support for a style investing of institutional investors
in the real estate category, when markets were booming. Interestingly, the coefficient on
RERCSENT is positive and significant at the 5% and 1% level respectively for S&P and non-S&P
REITs. These findings for the pre-crisis period are in line with our previous findings for the
overall sample in Table 4, suggesting that the style investing theory has the highest explanatory
power for the sentiment-induced institutional trading behavior in the securitized market,
irrespective of whether securities belong to the individual or institutional investor habitat.
For the financial crisis period of 2007 to 2009, instead, the coefficient on RERCSENT again
changes direction and becomes significantly negative at the 1% for S&P and non-S&P REITs,
which supports our previous findings for the full sample (Table 4). The more pessimistic
institutional investors were about the unsecuritized real estate market, the more they behaved as
net buyers in the securitized real estate market. These results suggest a sentiment-induced capital
switching between the illiquid private and more liquid public real estate market, irrespective of
habitat, in line with the flight to liquidity theory. Our results mirror the ones of Devos et al.
(2013), who show that some institutional investors such as banks significantly increased their
REIT ownership during the financial crisis.
For the post-crisis period of 2010 to 2012, the coefficient on RERCSENT is negative yet
insignificant for stocks included in the S&P500 index and significantly negative at the 5% level
for non-S&P500 stocks. The financial crisis has hence changed the relationship of RERCSENT and
BSIINST from positive (category theory) to negative (flight to liquidity), probably due to a higher

25
risk perception of investors with regard to unsecuritized real estate markets despite the mild
recovery subsequent to the financial crisis. Our results are in line with previous findings of
Devos et al. (2013) that the investment behavior and preferences of institutional REIT investors
change with economic conditions. Devos et al. (2013) find that institutional investors placed a
greater emphasis on managing risk following the crisis. In particular, the authors show that
insurance companies and banks have become more conservative after the crisis. Our findings
suggest that this emphasis on lower risk exposure also holds for the relationship of unsecuritized
and securitized market investments, and leads institutional investors to switch capital between
these two markets based on perceived risk levels.
The results of our time-period specific analysis for the full sample in Table 4 as well as S&P and
non-S&P REITs in Table 5 indicate that the initial aggregated analysis in Table 3 masks
differences in the relationship of RERCSENT and BSIINST over time. The insignificant coefficients
on RERCSENT for S&P, non-S&P and high institutional ownership REITs in Table 3 are likely the
result of directional changes in the investigated relationship over time, due to style investing in
positive economic conditions (2002 to 2006) and a flight to liquidity in difficult economic
environments (2007 to 2009).
To assess the robustness of our findings, we conduct two robustness checks. Firstly, we estimate
our model as shown in equation 3 for portfolios of REITs with above median (high) and below
median (low) institutional ownership, which represents an alternative proxy for the habitat of
institutional and individual investors. Our results are presented in Table 6. The coefficients on
RERCSENT for both types of REITs are significantly positive in the pre-crisis period (2002 to

26
2006), significantly negative in the crisis period (2007 to 2009) and negative, but insignificant in
the post-crisis period (2010 to 2012). These results suggest that our main findings are robust to
different definitions of individual and institutional investor habitat. Institutional investors style
invested in the pre-crisis period and showed a flight to liquidity in the crisis period and to a lesser
extent in the post-crisis period.
[Insert Table 6 here]
As a second robustness check, we estimate our model for different property types in all three
periods. As shown in Table 7, the coefficients on RERCSENT are consistent across asset types,
although varying in significance. In particular, coefficients are significantly positive in the pre-
crisis period for industrial, retail and hotel REITs, but insignificant for office REITs.
Interestingly, the coefficient on RERCSENT for multi-family REITs is significantly negative in the
pre-crisis period. During the crisis period, institutional investor sentiment in the private market is
significantly negatively related to institutional trading of REITs of all property type
specializations, except hotel. While the coefficient for hotel REITs is in the expected direction,
the insignificance may stem from low statistical power due to a relatively small sample size.
Lastly, while the coefficients on RERCSENT for all property type specializations in the post-crisis
period are negative, only the one for hotel REITs is significant. Overall, the results for different
property types support our previous findings. The applicability of style investing and flight to
liquidity theory depends on economic conditions: in pre-crisis conditions style investing best
explains sentiment-induced institutional trading behavior in the securitized real market, while in

27
crisis and to some extent in the post-crisis conditions the flight to liquidity theory is more
suitable.
[Insert Table 7 here]
6. Results for Institutional Investor Sentiment and Securitized Asset Pricing
Table 8 presents the results of the effect of institutional investor sentiment in the unsecuritized
market on asset pricing in the securitized market. For the overall sample, institutional investor
sentiment in the commercial real estate market has a significantly positive effect on REIT
returns. For the pre-crisis period of 2002 to 2006, RERCSENT also has a significantly positive
effect on the returns of REITs in the individual and institutional investor habitat. This is in line
with the significantly positive correlation between institutional investor sentiment in the private
real estate market and REIT returns identified by Ling, Naranjo and Scheick (2013). The
sentiment-induced trading behavior of institutional investors in the securitized real estate market
identified previously introduces additional systematic risk into asset pricing in line with previous
studies (Barberis, Shleifer and Wurgler, 2005; Barberis and Shleifer, 2003). While the effect of
institutional investor sentiment on the returns of large cap REITs (institutional investor habitat)
is in line with earlier studies (Clayton and MacKinnon, 2003b; Graff and Young, 1997), we also
find an impact on the returns of REITs in the individual investor habitat. This effect can be
explained with the presence of fewer fundamental traders and greater limits to arbitrage in this
habitat. An additional explanation for the impact of institutional sentiment on the return of

28
REITs in the individual investor habitat is that institutional trading signals information to less
informed individual investors. Lee, Lee and Chiang (2008) argue that individual investors use
institutional investors as a source of information and follow them in and out of small cap REITs
based on private market performance. As individual investors are less likely to be able to
determine whether institutional trading is based on private market fundamentals (e.g.
performance) or irrational sentiment, they likely follow institutional investors in and out of
REITs in their habitat based on sentiment.
[Insert Table 8 here]
In the crisis (2007 to 2009), RERCSENT has a positive yet insignificant coefficient for the S&P
REIT sample and a significantly positive coefficient for non-S&P REITs. The insignificant
coefficient for the crisis period is puzzling. One explanation for the non-existing effect of
commercial investor sentiment on the pricing of S&P REITs between 2007 and 2009 may be that
factors such as the flight to quality (Devos et al., 2013) have increased the presence of
fundamentals traders in these larger, older and relatively more liquid stocks. These investors in
turn may face lower limits to arbitrage in these REITs and be able to arbitrage away the
additional sentiment-induced risk. On the other hand, arbitrage may be too costly in REITs
forming the habitat of individual investors (Kumar and Lee, 2006), and this explains the
persistent effect of private market sentiment on securitized returns.
The significantly positive coefficient on RERCSENT for non-S&P REITs is also somewhat
counter-intuitive. With regards to our previous findings for BSIINST, if institutional investors as a

29
group are pessimistic about the private market during the financial crisis and switch their
investments from private to public real estate, we expect a negative coefficient. This aggregated
trading behavior (flight to liquidity) should increase the systematic risk in REITs, when
institutional investors are pessimistic, and consequently increase returns to compensate for this
additional risk.
Lastly, commercial real estate sentiment has a significantly positive effect on institutional trading
behavior for S&P REITs, but no effect for non-S&P REITs in the post-crisis period. Analogously
to the crisis period, these effects are somewhat counter-intuitive, particularly with regard to our
findings for BSIINST in Table 5. Overall, our results for the crisis and post-crisis period suggest
that further investigations into the relationship of commercial real estate sentiment and REIT
returns, particularly across different types of investor habitats, are needed.
7. Conclusion
Our study yields a number of interesting results. Firstly, we show that the sentiment of
institutional investors in the underlying unsecuritized real estate market affects their trading
behavior in the securitized market, suggesting a spillover effect of irrational sentiment between
private and public market. Moreover, our findings suggest that the direction of sentiment-
induced trading behavior of institutional investors in the securitized market depends on economic
conditions, particularly with regard to the most recent financial crisis (2007 to 2009).

30
During times of favorable economic and property market conditions such as 2002 to 2006 (pre-
crisis), institutions style invested in the real estate category based on their sentiment about the
underlying private market. If institutional investors as a group felt irrationally optimistic about
commercial real estate, they would have increased their investment in the real estate category,
including both securitized and unsecuritized assets. Our study complements the extensive
literature on style (category) investing theory (Choi and Sias, 2009; Froot and Teo, 2008;
Barberis, Shleifer and Wurgler, 2005; Barberis and Shleifer, 2003) by providing empirical
evidence that institutional investors not only style-invest within the stock market, but also across
asset markets (e.g. the unsecuritized and securitized real estate market). Our findings also
contribute to the institutional herding literature (Sias 2004; Nofsinger and Sias, 1999) by
showing that institutional investors as a group herd in and out of asset categories, increasing
volatility and introducing a non-fundamental component into asset pricing. This is in line with
the institutional herding effects found in Clayton and MacKinnon (2003b) and Graff and Young
(1997).
Our finding that institutions style-invest in the real estate category based on sentiment represents
a behavioral explanation for the comovement of securitized and unsecuritized real estate returns
(Pagliari et al., 2005; Myer and Webb, 1993; Giliberto, 1990). Lee, Lee and Chiang (2008) find
that sentiment linked to private markets has a high explanatory power for large cap securities
(i.e. REITs) for the period of 1993 to 2003. The authors explain this finding with an increased
involvement of institutions invested in both markets that strengthen the link between private
market fundamentals and public asset returns. Our findings for the pre-crisis period support Lee,
Lee and Chiang (2008).

31
For the crisis period, we find evidence of sentiment-induced capital switching between the
illiquid unsecuritized real estate market and the more liquid securitized one. As institutional
investors are highly sensitive to the illiquidity risk in commercial real estate (Dhar and
Goetzmann, 2006) and have a preference for more liquid real estate investments such as REITs
(Ciochetti, Craft and Shilling, 2002), we control for private and public market illiquidity to
ensure that our results are not driven by fundamental illiquidity risk. Thus, our sentiment
measure (RERCSENT) captures perceived (sentiment-based) risk in the private real estate market,
as opposed to fundamentals-based liquidity risk.
Our findings for the crisis period complement previous findings by Devos et al. (2013). While
the earlier study showed a flight to quality of institutional investors within the REIT market, our
study finds a flight to liquidity of institutional investors between the unsecuritized and
securitized real estate market. Furthermore, we provide a behavioral explanation for the capital
switching between real estate markets as discussed by Lee, Lee and Chiang (2008). In addition,
for a better understanding of the behavior of institutional investors in securitized asset markets,
our study also contributes to the flight to liquidity / quality literature (e.g. Baker and Wurgler,
2012; Brunnermeier and Pederson, 2009; Goyenko and Ukhov, 2009; Connolly, Stivers and Sun,
2007; Archarya and Pederson, 2005) by showing that a flight to liquidity not only occurs within
the stock market or between bond & stock market, but also between unsecuritized and
securitized markets of the same asset (e.g. direct investment in real estate and REITs).
Overall, our findings suggest that the style investing and flight to liquidity theory are
complementary rather than substitute theories for the sentiment-induced trading behavior of
institutional investors in securitized markets. Our results hold across different groups of

32
securities (e.g. REITs with high and low institutional ownership, included or not in the S&P
index) and property types.
Our study provides additional evidence that the financial crisis has changed the preferences of
institutional investors towards financial assets that imply a lower risk exposure (Devos et al.
2013). Future studies with larger post-crisis datasets may investigate whether this effect is
temporary or persistent, as well as implications for institutional portfolio performance. Lastly,
our investigation into the effect of institutional investor sentiment on securitized real estate
pricing suggests that not only the sentiment of individual investors positively affects REIT
returns (Lin et al., 2009; Chiang and Lee, 2009; Clayton and MacKinnon, 2003a; Barkham and
Ward, 1999), but also institutional investor sentiment in the underlying private market.
Our results have implications for future studies on investor sentiment in general and institutional
investors in particular. Firstly, institutional investors cannot be assumed to be rational and future
studies on investor sentiment in securitized or unsecuritized real estate markets need to account
for both institutional and individual investor sentiment. Additionally, our findings suggest that
investor sentiment studies should be time variant and distinguish between different time periods
as risk perception and investment behavior change over time. We consider our study a starting
point for future investigations into institutional investor sentiment, the sentiment-driven trading
behavior of institutional investors between private and public market as well as the effect of
liquidity on investor sentiment.

33
Acknowledgements
The authors would like to thank Seow Eng Ong, David Geltner, Piet Eichholtz, Andy Naranjo,
David Downs, the participants of the 2013 Maastricht University-National University of
Singapore-MIT (MNM) symposium and 2013 National AREUEA conference for their valuable
comments. We also thank the Real Estate Research Corporation (RERC) for providing us with
their data.

34
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39
Exhibits
Table 1: Descriptive Statistics
Panel A: Sentiment measures
Mean
Median
Std. Dev
Minimum
Maximum
RERCSENT
1.19
0.62
3.15
-6.57
7.5
BSIINST
0.16
0.23
0.46
-1.00
1
BSIMF
0.49
0.53
0.32
-0.93
1
Panel B: Illiquidity and Liquidity Measures
AMILLIQREIT
0.10
0.03
0.29
0.00
5.05
AMILLIQMARKET
0.02
0.01
0.01
0.00
0.07
AMILLIQCOM
0.01
0.00
0.01
0.00
0.10
Panel C: Fundamentals
SPR
4.52
5.08
1.81
1.29
7.85
TRM
2.02
2.41
1.19
-0.41
3.44
UNP
6.65
5.83
1.92
4.43
9.93
SNP
0.30
0.55
2.94
-7.88
4.91
SPINDEX
0.40
0.00
0.49
0.00
1.00
INSTOWN
71.22
77.71
22.38
0.09
100
Panel D: REIT Returns and Systematic Risk Factors
RETREIT
3.90
4.95
18.46
-145.84
203.17
MKT
1.27
1.55
9.02
-22.28
16.55
SMB
1.21
0.74
4.04
-6.03
12.01
HML
0.87
0.80
6.62
-13.63
23.85
MOM
0.08
0.45
3.32
-13.97
5.75
Note: This table presents the descriptive statistics for a sample of 2,357 REIT quarters (68 REITs) over the
period of Q1/2002 to Q2/2012. RERCSENT measures institutional investor sentiment in different typological
commercial real estate markets and is based on the “investment conditions” item in the RERC survey over the
period of Q1/2002 to Q2/2012. BSIINST is the buy sell index for institutional investors in individual REITs in line
with Kumar and Lee (2006). BSIMF is the buy sell index for mutual funds investing in individual REITs.
AMILLIQREIT, AMILLIQMARKET and AMILLIQCOM are the Amihud (2002) illiquidity measures for individual
REITs, the REIT market and the commercial real estate market respectively. SPR is the default risk premium
(spread) defined as difference between yield of BAA rated corporate bond and 1yr treasury bond. TRM is the
term structure defined as difference between the yields of the 10-year treasury bond and 3-month treasury bill.
UNP is the unemployment rate. SNP is the return on the S&P500 index. SPINDEX is coded 1 for quarters in
which a REIT is included in the S&P 400, 500 or 600 index. INSTOWN is the percentage of institutional
ownership in a REIT. RETREIT is the quarterly return for a particular REIT. MKT, SMB, HML and MOM are
systematic risk factors.

40
Table 2: Correlations
Panel A: Correlations of Sentiment Measures, Liquidity Measures and REIT Returns
RERCSENT
BSIINST
BSIMF
AMILLIQREIT
AMILLIQMARKET
AMILLIQCOM
RETREIT
RERCSENT
1
BSIINST
-0.06***
1
BSIMF
0.01
0.15***
1
AMILLIQREIT
-0.05**
0.10***
0.02
1
AMILLIQMARKET
-0.12***
0.21***
0.08***
0.22***
1
AMILLIQCOM
-0.21***
0.09***
-0.07***
0.04*
-0.03
1
RETREIT
0.08***
0.08***
0.05**
-0.01
-0.08***
0.19***
1
Panel B: Correlations of Commercial Real Estate Investor Sentiment and REIT Trading Behavior Over Time
BSIINST
2002 - 2006
RERCSENT
-0.03
2007 - 2009
RERCSENT
-0.24***
2010 - 2012
RERCSENT
-0.04
Note: RERCSENT measures institutional investor sentiment in different typological commercial real estate markets and is based on the
“investment conditions” item in the RERC survey over the period of Q1/2002 to Q2/2012. BSIINST is the buy sell index for institutional
investors in individual REITs in line with Kumar and Lee (2006). BSIMF is the buy sell index for mutual funds investing in individual REITs.
AMILLIQREIT, AMILLIQMARKET and AMILLIQCOM are the Amihud (2002) illiquidity measures for individual REITs, the REIT market and the
commercial real estate market respectively. RETREIT is the quarterly return for a particular REIT.
‘***’, ‘**’ and ‘*’ indicate significance at the 1%, 5% and 10% level respectively.

41
Table 3: Results for Institutional Investor Trading Behavior in REITs (BSIINST)
Overall
Sample
S&P
Index
Non-S&P
Index
Institutional Ownership
High
Low
RERCSENT
0.01
0.00
0.00
-0.01
0.02*
AMILLIQREIT
0.01
-0.09
0.01
-0.07
0.01
AMILLIQMARKET
-0.20
1.96
-0.53
0.48
0.04
AMILLIQCOM
0.68
1.20
0.67
1.29
0.06
BSIMF
0.14***
0.12***
0.13***
0.13***
0.12***
INSTOWN
0.00*
0.01***
0.00
0.00***
0.00**
SPINDEX
0.02
0.03
0.01
SPR
-0.03
-0.04*
-0.04
-0.03
-0.03
TRM
0.28***
0.28***
0.30***
0.29***
0.28***
UNP
-0.03***
-0.02*
-0.03**
-0.03**
-0.03
SNP
0.01***
0.00
0.01***
0.01*
0.01**
Constant
-0.29***
-0.62***
-0.21**
-0.56***
-0.26**
Firm-fixed effects
Yes
Yes
Yes
Yes
Yes
R2
0.31
0.29
0.31
0.33
0.23
N (n)
2357 (68)
933 (44)
1424 (64)
1562 (60)
795 (51)
Note: This table presents the results for the regression of BSIINST on the following variables using
firm-fixed effects linear regression (unbalanced panels). Results are reported for the overall sample,
REITs that are included in a S&P index (S&P) and those that are not (Non-S&P), REITs with above
median and below median institutional ownership. RERCSENT measures institutional investor
sentiment in different typological commercial real estate markets and is based on the “investment
conditions” item in the RERC survey over the period of Q1/2002 to Q2/2012. BSIINST is the buy sell
index for institutional investors in individual REITs in line with Kumar and Lee (2006). BSIMF is the
buy sell index for mutual funds investing in individual REITs. AMILLIQREIT, AMILLIQMARKET and
AMILLIQCOM are the Amihud (2002) illiquidity measures for individual REITs, the REIT market and
the commercial real estate market respectively. SPR is the default risk premium (spread) defined as
difference between yield of BAA rated corporate bond and 1yr treasury bond. TRM is the term
structure defined as difference between the yields of the 10-year treasury bond and 3-month treasury
bill. UNP is the unemployment rate. SNP is the return on the S&P500 index. INSTOWN is the
percentage of institutional ownership in a REIT. SPINDEX is a binary variable coded 1 for quarters
in which a REIT was included in an S&P index. The reported R2 is the overall R2 resulting from the
respective within and between R2s.
‘***’, ‘**’ and ‘*’ denote significance at the 1%, 5% and 10% level respectively.

42
Table 4: Results for Institutional Investor Trading Behavior in REITs (BSIINST) for
the Overall Sample Separated by Time
2002-2006
2007-2009
2010-2012
RERCSENT
0.08***
-0.10***
-0.03*
AMILLIQREIT
-0.01
-0.06
0.08
AMILLIQMARKET
3.51**
4.40**
12.50**
AMILLIQCOM
13.86***
0.05
-1.17
BSIMF
0.10***
0.19***
0.13***
INSTOWN
-0.00
0.01***
0.00
SPINDEX
-0.04
0.08
0.04
SPR
-0.42***
-0.01
0.01
TRM
0.22***
0.29***
0.11
UNP
1.44***
-0.18***
0.07
SNP
-0.03***
0.06***
0.00
Constant
-6.60***
-0.09
-0.99
Firm-fixed effects
Yes
Yes
Yes
R2
0.43
0.15
0.06
N (n)
1112 (63)
638 (63)
607 (68)
Note: This table presents the results for the regression of BSIINST on the following variables using
firm-fixed effects linear regression (unbalanced panels). Results are reported for the overall
sample for pre-crisis (2002-2006), crisis (2007-2009) and post-crisis (2010-2012) period.
RERCSENT measures institutional investor sentiment in different typological commercial real
estate markets and is based on the “investment conditions” item in the RERC survey over the
period of Q1/2002 to Q2/2012. BSIINST is the buy sell index for institutional investors in individual
REITs in line with Kumar and Lee (2006). BSIMF is the buy sell index for mutual funds investing in
individual REITs. AMILLIQREIT, AMILLIQMARKET and AMILLIQCOM are the Amihud (2002)
illiquidity measures for individual REITs, the REIT market and the commercial real estate market
respectively. SPR is the default risk premium (spread) defined as difference between yield of BAA
rated corporate bond and 1yr treasury bond. TRM is the term structure defined as difference
between the yields of the 10-year treasury bond and 3-month treasury bill. UNP is the
unemployment rate. SNP is the return on the S&P500 index. INSTOWN is the percentage of
institutional ownership in a REIT. SPINDEX is a binary variable coded 1 for quarters in which a
REIT was included in an S&P index. The reported R2 is the overall R2 resulting from the
respective within and between R2s.
‘***’, ‘**’ and ‘*’ denote significance at the 1%, 5% and 10% level respectively.

43
Table 5: Results for BSIINST Separated for S&P and Non-S&P REITs and Time Period
2002-2006
2007-2009
2010-2012
S&P
Non-S&P
S&P
Non-S&P
S&P
Non-S&P
RERCSENT
0.09**
0.08***
-0.08***
-0.13***
-0.03
-0.06**
AMILLIQREIT
0.32
-0.00
0.03
-0.02
0.32
0.00
AMILLIQMARKET
2.54
3.69**
2.68
5.37
19.11***
-1.35
AMILLIQCOM
12.12*
14.59***
0.89
-0.52
-1.81*
-0.74
BSIMF
0.12
0.10**
0.10
0.24***
0.14***
0.16***
INSTOWN
-0.01*
-0.00
0.02***
0.00
0.01***
-0.00
SPR
-0.48***
-0.39***
0.02
-0.06
-0.04
-0.06
TRM
0.26***
0.21***
0.20***
0.37***
0.13
0.16
UNP
1.47***
1.41***
-0.13***
-0.22***
0.14*
-0.03
SNP
-0.01
-0.03***
0.04***
0.07***
-0.00
0.00
Constant
-6.27***
-6.56***
-0.89**
0.53
-1.87*
0.58
Firm-fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
R2
0.43
0.40
0.13
0.18
0.07
0.03
N (n)
243 (21)
869 (59)
328 (35)
310 (41)
362 (44)
245 (30)
Note: This table presents the results for the regression of BSIINST on the following variables using fixed effects
linear regression (unbalanced panels). Results are reported for REITs that are in an S&P index and those that
are not for the pre-crisis (2002-2006), crisis (2007-2009) and post-crisis (2010-2012) period. RERCSENT
measures institutional investor sentiment in different typological commercial real estate markets and is based
on the “investment conditions” item in the RERC survey over the period of Q1/2002 to Q2/2012. BSIINST is the
buy sell index for institutional investors in individual REITs in line with Kumar and Lee (2006). BSIMF is the
buy sell index for mutual funds investing in individual REITs. AMILLIQREIT, AMILLIQMARKET and AMILLIQCOM
are the Amihud (2002) illiquidity measures for individual REITs, the REIT market and the commercial real
estate market respectively. INSTOWN is the percentage of institutional ownership in a REIT. SPR is the default
risk premium (spread) defined as difference between yield of BAA rated corporate bond and 1yr treasury bond.
TRM is the term structure defined as difference between the yields of the 10-year treasury bond and 3-month
treasury bill. UNP is the unemployment rate. SNP is the return on the S&P500 index. The reported R2 is the
overall R2 resulting from the respective within and between R2s.
‘***’, ‘**’ and ‘*’ denote significance at the 1%, 5% and 10% level respectively.

44
Table 6: Results for BSIINST Separated for High and Low Institutional Ownership REITs and
Time Period
2002-2006
2007-2009
2010-2012
High
Low
High
Low
High
Low
RERCSENT
0.08***
0.08***
-0.10***
-0.13***
-0.03
-0.02
AMILLIQREIT
0.48
-0.06
-0.11
0.01
-0.17
0.21
AMILLIQMARKET
2.59
4.80**
3.61
7.35*
12.75**
-10.70
AMILLIQCOM
17.70***
10.13**
0.23
0.76
-0.17
-0.41
BSIMF
0.08
0.11**
0.16**
0.21*
0.13***
0.14*
INSTOWN
0.00
0.00
0.01***
0.03***
0.01***
0.00
SPINDEX
-0.02
-0.07
0.10
0.16
0.06
0.17
SPR
-0.48***
-0.31***
0.02
-0.11
-0.01
-1.09
TRM
0.23***
0.21***
0.25***
0.33***
0.11
0.83*
UNP
1.66***
1.10***
-0.17***
-0.19***
0.11
0.01
SNP
-0.03***
-0.02**
0.06***
0.06***
-0.00
0.03**
Constant
-7.81***
-5.38***
-0.34
-0.58***
-1.92
4.03
Firm-fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
R2
0.47
0.28
0.19
0.05
0.03
0.18
N (n)
620 (49)
492 (45)
463 (54)
175 (24)
479 (60)
128 (29)
Note: This table presents the results for the regression of BSIINST on the following variables using fixed effects
linear regression (unbalanced panels). Results are reported for REITs with above median and below median
institutional ownership for the pre-crisis (2002-2006), crisis (2007-2009) and post-crisis (2010-2012) period.
RERCSENT measures institutional investor sentiment in different typological commercial real estate markets and
is based on the “investment conditions” item in the RERC survey over the period of Q1/2002 to Q2/2012. BSIINST
is the buy sell index for institutional investors in individual REITs in line with Kumar and Lee (2006). BSIMF is
the buy sell index for mutual funds investing in individual REITs. AMILLIQREIT, AMILLIQMARKET and
AMILLIQCOM are the Amihud (2002) illiquidity measures for individual REITs, the REIT market and the
commercial real estate market respectively. SPR is the default risk premium (spread) defined as difference
between yield of BAA rated corporate bond and 1yr treasury bond. TRM is the term structure defined as
difference between the yields of the 10-year treasury bond and 3-month treasury bill. UNP is the unemployment
rate. SNP is the return on the S&P500 index. SPINDEX is a binary variable coded 1 for quarters in which a
REIT was included in an S&P index. INSTOWN is the percentage of institutional ownership in a REIT The
reported R2 is the overall R2 resulting from the respective within and between R2s.
‘***’, ‘**’ and ‘*’ denote significance at the 1%, 5% and 10% level respectively.

45
Table 7: Results for BSIINST by Property Type and Time Period
Office
Industrial
Retail
Residential
Hotel
2002-
2006
2007-
2009
2010-
2012
2002-
2006
2007-
2009
2010-
2012
2002-
2006
2007-
2009
2010-
2012
2002-
2006
2007-
2009
2010-
2012
2002-
2006
2007-
2009
2010-
2012
RERCSENT
0.07
-0.42**
-0.03
0.43**
-0.54**
-0.10
0.14***
-0.35***
-0.11
-0.10**
-0.66***
-0.00
0.40**
-0.05
-0.22**
AMILLIQREIT
0.97
-0.02
0.50
1.86
-0.67
-0.41
0.00
-0.01
0.19
-0.17
-0.41
3.81**
-0.06
0.10
-0.69
AMILLIQMARKET
2.69
12.36*
11.68
-4.76
10.15
6.05
6.50**
3.36
20.69*
5.85*
7.96
-2.24
15.07
5.72
51.83**
AMILLIQCOM
23.99**
0.07
2.73
6.92
-6.94
1.21
16.65***
1.17
0.63
15.68*
-11.47**
16.75
116.70
16.94
-46.20
BSIMF
0.04
0.16
0.15*
0.15
0.16
0.08
0.11*
0.18**
0.14***
0.10
0.30**
0.13**
0.02
0.24
0.01
INSTOWN
-0.01
0.00
0.00
-0.00
0.00
0.01
-0.00
0.01***
0.00
-0.00
0.03***
0.01**
-0.01
0.01
0.01
SPINDEX
0.06
0.11
-0.44*
-0.19
-0.07
0.09
0.11
-0.22
-0.10
0.02
SPR
-0.42***
-0.08
0.40
-0.27
0.08
0.57
-0.38***
-0.16
0.10
-0.57***
0.07
-2.16**
-0.40*
-0.14
3.35*
TRM
0.23***
0.26
-0.06
0.31
0.02
-0.10
0.11*
0.35**
0.18
0.37***
0.25
1.06**
0.29
0.46
-1.34
UNP
1.43***
-0.24***
-0.05
1.31**
-0.34**
-0.16
1.51***
-0.25***
-0.14
1.28***
-0.21***
0.41***
1.24**
-0.11
-0.61*
SNP
-0.02
0.08**
-0.00
-0.00
0.13**
0.00
-0.05***
0.08**
0.01
-0.03**
0.07***
0.01
-0.08**
0.04
-0.03
Constant
-6.02***
0.47
-1.27
-6.25**
0.68
-1.91
-7.15***
-0.04
0.03
-4.79***
2.15*
4.39
-7.44**
-0.38
-8.48
Firm-fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
R2
0.53
0.46
0.12
0.15
0.47
0.22
0.54
0.24
0.13
0.49
0.08
0.23
0.63
0.33
0.11
N (n)
188 (11)
84 (10)
84(11)
41 (3)
33 (3)
34(4)
441 (24)
247(24)
221(25)
216 (11)
106(11)
102(11)
54 (4)
49(5)
68(7)
Note: This table presents the results for the regression of BSIINST on the following variables using fixed effects linear regression (unbalanced panels). Results are
reported for different property types and three distinct time periods. RERCSENT measures institutional investor sentiment in different typological commercial real
estate markets and is based on the “investment conditions” item in the RERC survey over the period of Q1/2002 to Q2/2012. BSIINST is the buy sell index for
institutional investors in individual REITs in line with Kumar and Lee (2006). BSIMF is the buy sell index for mutual funds investing in individual REITs.
AMILLIQREIT, AMILLIQMARKET and AMILLIQCOM are the Amihud (2002) illiquidity measures for individual REITs, the REIT market and the commercial real estate
market respectively. SPINDEX is a binary variable coded 1 for quarters in which a REIT was included in an S&P index. SPR is the default risk premium (spread)
defined as difference between yield of BAA rated corporate bond and 1yr treasury bond. TRM is the term structure defined as difference between the yields of the
10-year treasury bond and 3-month treasury bill. UNP is the unemployment rate. SNP is the return on the S&P500 index. INSTOWN is the percentage of
institutional ownership in a REIT. The reported R2 is the overall R2 resulting from the respective within and between R2s.
‘***’, ‘**’ and ‘*’ denote significance at the 1%, 5% and 10% level respectively.

46
Table 8: Results for REIT Return Separated by S&P and Non-S&P REITs and Time Period
2002-2006
2007-2009
2010-2012
Full
Sample
S&P
Non-S&P
S&P
Non-S&P
S&P
Non-S&P
RERCSENT
3.62***
2.65***
3.22***
2.27
9.66**
3.28*
0.03
MKT
0.60***
0.28*
0.21***
0.97***
1.00***
0.62***
0.70***
SMB
0.50***
0.71***
0.83***
0.69
1.93**
3.17***
2.94*
HML
1.11***
0.08
0.26**
1.45***
0.95
-2.67***
-1.52
MOM
0.83***
0.54
0.60***
2.21**
1.13
-0.22
0.62
AMILLIQMA
0.05
2.14***
0.11***
0.54**
0.06
-0.15
0.02
lagRETREIT
-0.06***
-0.30***
-0.27***
-0.13**
-0.05
-0.22***
-0.12*
lagRERCSENT
-4.06***
-1.35
-1.97***
-4.53*
-7.42**
-0.45
1.88
Constant
2.40***
-1.02
1.79**
3.97**
5.32
-7.83**
-4.37
Fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
R2
0.47
0.16
0.30
0.56
0.51
0.48
0.50
N (n)
1677 (68)
183 (21)
625 (57)
237 (34)
218 (37)
248 (42)
166 (30)
Note: This table presents the results for the regression of REIT returns (RETREIT) on the following variables using
firm-fixed effects linear regression (unbalanced panels). Results are reported for the full sample, REITs that are in an
S&P index and those that are not for three distinct time periods. RERCSENT measures institutional investor sentiment
in different typological commercial real estate markets and is based on the “investment conditions” item in the RERC
survey over the period of Q1/2002 to Q2/2012. MKT, SMB, HML and MOM are the four systematic risk factors.
AMILLIQMA is the mean-adjusted Amihud (2002) illiquidity measure.
‘***’, ‘**’ and ‘*’ denote significance at the 1%, 5% and 10% level respectively.

47
Figure 1: Correlation of Institutional Investor Sentiment in the Private Market (RERCSENT)
and REIT Trading Behavior (BSIINST) Over Time
Note: This figure graphically presents the correlation between institutional investor sentiment in the commercial
real estate market (RERCSENT) and institutional trading behavior in REITs (BSIINST) over the period of Q1/2002 to
Q2/2012. The X-axis measures time in year and quarter. The left Y-axis measures RERCSENT while the right Y-axis
measures BSIINST.
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
-3
-2
-1
0
1
2
3
RERCSENT
BSIINST

48
Appendix
Table A1: Data Description and Sources
Variable
Definition
Derivation
Source
RERCSENT
Commercial real estate market
sentiment of institutional
investors
“Investment conditions” in RERC survey; principal
common analysis used for property types with more
than one segment (office, industrial, retail, diversified)
to derive a score
Quarterly survey of institutional
investors by Real Estate
Research Corporation (RERC)
BSIINST
Buy sell index of institutional
investors; BSIINST>0 (net
buyers); BSIINST<0 (net
sellers)
Where Bt (St) is the quarterly long (short) position of
institutional investors in a particular REIT.
Institutional (13f) Holdings
database (s34) in Thomson
Reuters
BSIMF
Buy sell index of mutual
funds; BSIMF>0 (net buyers);
BSIMF<0 (net sellers)
Where Bt (St) is the quarterly long (short) position of
mutual funds in a particular REIT.
Mutual Fund Holdings database
(s12) in Thomson Reuters
AMILLIQREIT
Amihud (2002) illiquidity
measure for an individual
REIT
Where R is the absolute return and VOL the total
trading volume for a particular REIT.
CRSP
AMILLIQMARKET
Amihud (2002) illiquidity
measure for the REIT market
Quarterly value-weighted (by market capitalization)
aggregate of the REIT-level illiquidity values.
CRSP
AMILLIQCOM
Amihud (2002) illiquidity
measure for the commercial
real estate market
Where R is the absolute quarterly property-type
specific NCREIF transaction based index (NTBI) total
return and VOL is the dollar-denominated trading
volume for a particular property type.
NCREIF
SPR
Default risk premium
Difference between yields of BAA rated corporate
bond and 1 year treasury bond
Federal reserve, COMPUSTAT
TRM
Term structure
Difference between yields of 10 year T-bond and 3
Federal Reserve
BSIt=(Bt-St)
(Bt+St)
BSIt=(Bt-St)
(Bt+St)
ILLIQiy =|Riy |
VOLiy
ILLIQiy =|Riy |
VOLiy

49
month T-bill
UNP
Control for overall economy
Unemployment rate (national)
Bureau of Labor Statistics
SNP
Control for general stock
market
Return on S&P 500 composite index
CRSP
SPINDEX
Inclusion in S&P index
Binary variable coded 1 for quarters in which an
individual REIT was included in the S&P400, 500 or
600 index
NAREIT
INSTOWN
Institutional ownership in an
individual REIT
Total institutional ownership as a percentage of shares
outstanding
Thomson Reuters
RETREIT
Individual REIT returns
Quarterly returns for individual REITs
CRSP
MKT
Market Risk Premium
See Fama French (1993)
Fama French Factors (WRDS)
SMB
Small Minus Big factor
See Fama French (1993)
Fama French Factors (WRDS)
HML
High Minus Low factor
See Fama French (1993)
Fama French Factors (WRDS)
MOM
Momentum Factor
See Carhart (1997)
Fama French Factors (WRDS)

50
Table A2: Descriptive Statistics by Period
Period
Mean
Median
Std. Dev
Minimum
Maximum
RERCSENT
2002-2006
1.79
1.04
2.50
-1.89
6.8
2007-2009
-0.43
-1.26
3.58
-6.57
6.4
2010-2012
1.79
0.62
3.13
-3.00
7.5
BSIINST
2002-2006
0.12
0.24
0.54
-1.00
1.00
2007-2009
0.10
0.16
0.42
-1.00
0.93
2010-2012
0.29
0.28
0.25
-0.38
1.00
BSIMF
2002-2006
0.56
0.61
0.32
-0.93
1.00
2007-2009
0.45
0.49
0.27
-0.61
1.00
2010-2012
0.40
0.42
0.34
-0.73
1.00
AMILLIQREIT
2002-2006
0.12
0.03
0.37
0.00
5.05
2007-2009
0.11
0.02
0.26
0.00
2.56
2010-2012
0.06
0.01
0.11
0.00
0.94
AMILLIQMARKET
2002-2006
0.02
0.02
0.02
0.01
0.07
2007-2009
0.02
0.02
0.01
0.00
0.05
2010-2012
0.01
0.01
0.00
0.01
0.02
AMILLIQCOM
2002-2006
0.00
0.00
0.01
0.00
0.03
2007-2009
0.01
0.00
0.02
0.00
0.10
2010-2012
0.01
0.00
0.02
0.00
0.08
SPINDEX
2002-2006
0.22
0
0.41
0
1
2007-2009
0.51
1
0.50
0
1
2010-2012
0.60
1
0.49
0
1
INSTOWN
2002-2006
64.79
71.27
24.53
0.09
100
2007-2009
76.43
81.25
18.17
20.51
100
2010-2012
77.50
82.47
18.79
8.39
100
RETREIT
2002-2006
5.71
6.16
9.13
-40.84
30.56
2007-2009
-0.15
-0.41
29.92
-145.84
203.17
2010-2012
4.85
5.73
14.37
-60.39
98.46
Note: This table presents the descriptive statistics for our dataset for a sample of 2,357 REIT quarters (68 REITs)
over the period of Q1/2002 to Q2/2012, separated by period. The period of 2002 to 2006 covers 1112 REIT
quarters, 2007 to 2009 covers 638 REIT quarters and 2010 to 2012 covers 607 REIT quarters. RERCSENT measures
institutional investor sentiment in the commercial real estate market and is based on the “investment conditions”
item in the RERC survey over the period of Q1/2002 to Q2/2012. BSIINST is the buy sell index for institutional
investors in individual REITs in line with Kumar and Lee (2006). BSIMF is the buy sell index for mutual funds
investing in individual REITs. AMILLIQREIT, AMILLIQMARKET and AMILLIQCOM are the Amihud (2002) illiquidity
measures for individual REITs, the REIT market and the commercial real estate market respectively. SPINDEX is
coded 1 for quarters in which a REIT is included in the S&P 400, 500 or 600 index. INSTOWN is the percentage of
institutional ownership in a REIT. RETREIT is the quarterly return for a particular REIT.