RISK-ADJUSTED PERFORMANCE OF REAL ESTATE STOCKS:
EVIDENCE FROM EMERGING MARKETS IN ASIA
Joseph T.L. Ooi# & Kim-Hiang Liow
Department of Real Estate
National University of Singapore
4 Architecture Drive, Singapore 117566
Tel: 65 6874 3564 Fax: 65 6774 8684
E-mail: rstooitl@nus.edu.sg
December 9, 2002
Research paper to be presented at the American Real Estate and Urban Economics Association,
2003 Annual Conference and Meetings, Jan 3-5, 2003, Washington D.C.
Abstract
We investigate the performance of real estate stocks listed in seven emerging markets in
Asia, namely Hong Kong, Indonesia, Malaysia, Singapore, South Korea, Taiwan and
Thailand. Whilst the risk-adjusted returns of real estate stocks vary across the markets and
over time, we did not find any evidence of superior return. Using panel regressions, we
examine the determinants of the risk-adjusted returns at the firm level. The empirical
evidence suggests that market-to-book value, dividend yield and market diversification
have significant influence on the risk-adjusted returns of real estate stocks in Asia. Firm
size, leverage, and development exposure, however, do not appear to have any significant
impact on the risk-adjusted returns. As expected, interest rates and market condition have
significant impact on the risk-adjusted performance of real estate stocks.
Keywords: real estate stocks, risk-adjusted returns, Sharpe ratio, Asian markets.
#
Corresponding author.
RISK-ADJUSTED PERFORMANCE OF REAL ESTATE STOCKS:
EVIDENCE FROM EMERGING MARKETS IN ASIA
1
Introduction
This study examines the risk-adjusted performance of real estate stocks traded publicly in seven
emerging economies in East Asia, namely Hong Kong, Indonesia, Malaysia, Singapore, South Korea,
Taiwan and Thailand. The dominant story in Asia has been a strong economic growth accompanied
with high asset inflation in the 1980s to the mid 1990s. This was followed by a severe economic and
currency crisis, which hit the region starting with devaluation of the Thai bath in from July 1997.
Entering into the new millennium, we are seeing transformations in these markets with real estate
securitization becoming more popular. The performance of real estate stocks in Asia is a compelling
topic for research to help investors understand the returns opportunities offered by securitized real
estate in the international arena. In an attempt to increase returns and reduce risks, US pension funds
and corporations have increased their commitments to foreign equities since the 1990s (Carman,
1997). Ling and Naranjo (2002) further observed that a global real estate securities market has slowly
developed over the last two decades to provide a vehicle for investors to construct international
commercial real estate portfolios without the burden of acquiring, managing, and disposing of direct
real estate investments in far-away countries with unfamiliar legal, political, and market structures.
The findings of this study provide useful comparison with the performance of real estate securities in
US and other mature economies. In particular, a study on Asian real estate stocks provides an
opportunity to examine the performance of real estate investment in a market structure that is
different from the US or other more developed markets. Unlike REIT stocks that are defensive in
nature (see Howe and Shilling, 1990; Chan, Hendershott and Sanders, 1990), real estate stocks in Asia
are generally aggressive with high idiosyncratic and systematic risks. As highlighted by Glascock, So
and Lu (2002), Asia is characterized by land scarcity, high population density, and thus, relatively high
real estate values. Consequently, the Asian economies is an interesting setting to examine the returns
of real estate in developing economies that experienced both remarkable growth and extreme
volatility. The focus on the Asian economies also allows us to examine the impact of a financial
meltdown in the capital market on the risk-return characteristics of real estate stocks.
1
Our empirical investigation is carried out in two stages - in the first stage, the time-varying riskadjusted returns of the individual real estate stocks are estimated. Consistent with the findings of
Kallberg, Liu and Pasquariello (2002), our data shows that the risk-return profile of the real estate
stocks in our sample markets in Asia have changed significantly after the Asian Financial Crisis. We
also observed significant variations in the nominal and risk-adjusted returns of the individual real
estate stocks. Overall, the observations point to the existence of cross-sectional and time-varying
factors that determine the risk-return performance of real estate stocks. This is similar to the findings
of Ling and Naranjo (2002) who also observed significant firm-specific risk in international real estate
securities markets, even after controlling for world and country specific effects.
In the second part of our investigation, we employ panel regressions to identify the determinants of
risk-adjusted returns of real estate stocks. Our panel specification facilitates the identification of
effects that are simply not detectable in previous pure cross-sections or pure time-series studies. For
example, whilst the debt ratio of a firm has significant explanatory power in our cross-sectional
regressions on individual single-market portfolios, it ceased to have any significant explanatory power
in panel regressions that control for macroeconomic conditions. This suggests that the leverage may
simply be proxying for omitted macroeconomic factors in pure cross-sectional regressions. The
empirical evidence suggests that market-to-book value ratio and dividend yield of the individual real
estate stocks have a significant impact on their risk-adjusted returns after controlling for time effects.
However, firm size, property asset intensity, and gearing did not have any significant influence on the
real estate stock performance. As expected and consistent with findings of previous studies, we also
find that interest rate and economic market conditions have significant impact on the risk-adjusted
returns of real estate stocks.
The remainder of the paper is organized as follows. A brief review of literature on the performance
of securitized real estate is presented in the next section. In Section 3, we examine the nominal and
risk-adjusted performance of selected real estate stocks listed in seven emerging markets in Asia. In
Section 4, we carry out panel regressions to identify the determinants of risk-adjusted returns. Section
5 concludes with a discussion on the implications of our research findings.
2
2.
Review of Literature
The performance of real estate related stocks is a widely researched topic in the real estate literature.
Focusing primarily on REITs in the US, previous studies have employed various performance
metrics to investigate the historical performance of real estate-related stocks. In addition to nominal
return measures of performance, the two most common measures used to evaluate and rank the riskadjusted returns of real estate stocks are the Treynor ratio and the Sharpe ratio. Both ratios are quite
similar in that they both measure excess return earned per unit of risk. The different lies in the
denominator – Sharpe (1966) uses the standard deviation of returns (total risk) as a measure of risk,
whereas Treynor (1965) uses beta (systematic risk). The Sharpe ratio is, therefore, an appropriate
measure of reward-to-variability for investors who have a non-diversified portfolio. The Treynor
ratio, on the other hand, is a measure of reward-to-systematic risk for evaluating well-diversified
portfolios (Glascock and Davidson, 1995).
Numerous researchers have also sought to examine whether real estate investment offers superior
return using the Jensen’s index. First employed by Jensen in 1968, the index is essentially the alpha of
a regression equation with the individual stock’s excess return (stock return minus the risk-free rate)
as the dependent variable and the market risk premium (market return minus the risk-free rate) as the
independent variable.1 Earlier studies, such as Kuhle, Walther and Wurtzebach (1986), Firstenberg,
Ross and Zisler (1988), and Sagalyn (1990), concluded that REITs earned positive risk adjusted
returns especially from the late 1970s to the mid-1980s. As pointed out by Titman and Warga
(1986), these findings are often interpreted as evidence that real estate is a particularly good
investment that investors should add to their portfolios.
However, recent studies have questioned the reported abnormal returns. In particular, Liu, Grissom
and Hartzell (1995), in a critical review of the literature on real estate performance, suggest that
superior real estate performance is an illusion arising from an omission of certain fundamental
In earlier studies, the alpha and beta of the regression model are assumed to be constant over the
study period. However, in more recent studies, this assumption has been relaxed to allow for the time-varying
parameters in the regression models. A good example would be the study by Devaney (2001), who employs a
generalized autoregressive conditionally heteroskedastic in the mean (GARCH-M) methodology to estimate the
time varying risk premia for REITs. However, the disadvantage of this time-varying approach is that the return
regression must be estimated with greater frequency. This considerably reduces the number of observations in
each return regression, which, in turn, make it more difficult to uncover statistically significant parameters (Ling
and Naranjo, 1998).
1
3
factors in the estimates of risk.2 They argue that any evidence that real estate continues to possess
superior performance in the long run is likely to suffer from an inadequate or deficient pricing model.
Several studies have also illustrated the importance of using multiple index models instead of single
index models to determine the returns of real estate related stocks. In particular, Chan, Hendershott
and Sanders (1990) found evidence of excess real estate returns, especially in the 1980s, when a
simple CAPM framework was employed. However, when the multifactor model was employed, the
excess return evaporated.
The results of previous studies on the risk-adjusted returns of real estate stocks are summarized in
Table 1. Consistent with the theoretical prediction, most of the recent studies have not been able to
detect any superior return associated with real estate-related stocks. With the exception of Matysiak
and Brown (1997), all the previous empirical studies are based on US evidence. Two recent studies
have also examined the performance of real estate stocks using international data. Glascock et al.
(2002) use a modified version of Jensen’s alpha to measure the excess returns of publicly listed real
estate firms in six Asian market economies, namely, Japan, Taiwan, Hong Kong, South Korea,
Singapore and Thailand. Their results show that, except for Taiwan, real estate stocks across the
other five Asian markets do not exhibit excess returns behavior. They also noted that the risk
characteristics of the real estate stocks change with market conditions although the effects are not the
same across different countries. In another study, Ling and Naranjo (2002) examined the return
performance of 600 publicly traded real estate companies in 28 countries over the 1984 to 1999 time
period. Based on single and multifactor specifications, they found substantial variations in mean real
estate returns and standard deviations across countries. Using the standard Treynor ratio, they
observed substantial variation across countries in excess real estate returns per unit of systematic risk.
However, they detected little evidence of abnormal risk-adjusted returns at the country level. Their
overall results indicate the existence of a strong worldwide factor in international real estate returns
as well as a highly significant country-specific factor.
The fundamental factors identified by Liu et al. (1995) are: (1) inadequate theory and deficient
valuation models, (2) omitted asset markets and misspecification of risk, (3) market imperfection such as thin
trading, information/transaction costs, and divisibility, (4) markets segmentation arising from clientele effects,
and (5) inflation risk.
2
4
Table 1. Previous Studies on Performance of Real Estate Stocks
Authors
Sample (Period)
Measures
Results
Titman & Warga (1986)
36 REITs (1973)
Jensen alpha
No abnormal returns.
Chan, Hendershott &
Sanders (1990)
30 EREITs
(1973-1987)
Jensen alpha
EREITs do not offer superior
risk-adjusted return in the
multifactor model.
Howe & Shilling (1990)
105 REITs (1973-1987)
Sharpe ratio,
Treynor ratio
& Jensen alpha
No superior return with evidence
of significant poor performance
within several advisor categories.
Glascock (1991)
109 real estate firms
(1965-1986)
Jensen alpha
Real estate firms did not
outperform the market portfolio
for either the entire test period or
any subperiod of market
conditions.
Kapplin & Schwartz
(1995)
26 REITs, 15 master
limited partnerships
(MLPs) & 13 finite life
REITs (1987-1989).
Coefficient of
variation
MLPs provide superior returns,
but REITs underperform the
S&P 500 Index.
Glascock & Davidson
(1995)
31 real estate related
companies (1977-86).
Sharpe &
Treynor ratios
Real estate firms underperform
the market on a nominal and on a
risk-adjusted basis.
Redman & Manakyan
(1995)
48 REITs (1986-90)
Sharpe ratio
REITs underperform the market
on a risk-adjusted basis.
Wang & Erickson (1997)
144 MLPs (1981-91)
Sharpe ratio &
Jensen alpha
MLP stocks underperform the
market.
Matysiak & Brown
(1997)
18 property companies
in UK (1980-1995)
Jensen alpha
Insignificant negative abnormal
returns.
What determines the performance of an asset? According to the CAPM, the systematic risk should
be the only relevant factor in asset pricing. However, the Fama and French (1992) study on the
cross-sectional expected returns of common stocks show that the influence of beta is diminishing
and there are other firm-specific attributes that influence expected returns. Hence, an interesting area
of research is the search for factors determining the risk-return characteristics of real estate stocks. In
the real estate context, several studies have investigated the influencing factors behind the expected
returns or systematic risk (beta) of real estate-related stocks. However, only a few studies have sought
to examine the determinants of the returns on a risk-adjusted basis.
5
Two previous studies that have done so and which bear close resemblance to our current study are
Howe and Shilling (1990), who examined the abnormal performance (Jensen alpha) of 105 REITs in
the US over the period 1973 to 1987, and Redman and Manakyan (1995), who examined the riskadjusted performance (Sharpe ratio) of 48 REITs from 1986 through 1990. In the Redman and
Manakyan (1990) study, none of the individual financial variables (including firm size, gearing,
dividend yield, price-earnings ratio and return on assets and others) have any significant influence on
the REIT risk-adjusted returns. Results of their stepwise regressions, however, indicate that the most
significant variables positively affecting the risk-adjusted returns were three real asset characteristics:
equity investments in health care properties, investments in securitized mortgages, and equity
investments located in western United States. Howe and Shilling (1990) also observed that property
location is correlated to the abnormal returns of REITs. In addition, they observed that firm size and
advisor type may partially explain REIT performance. These findings are consistent with Mueller and
Laposa’s (1996) point that “even REITs of the same property type will nevertheless tend to have investments in
different geographic markets or property-type and size submarkets, and also that individual REITs have different
management skills and financial structures, all or which would lead to idiosyncratic return differences across REITs,
even within the same general property-type grouping.”
Our current research can be differentiated from the two earlier pure cross-sectional studies. Firstly,
we employ an international set of property returns data. Secondly, both Howe and Shilling (1990)
and Redman and Manakyan (1995) employed pure cross-sectional analysis to examine the influence
of firm-specific variables on the risk-adjusted returns of the firm. In our regression models, we also
control for time-varying factors in our panel regression models to control for macroeconomic factors
that may significantly affect the risk-adjusted returns. Accordingly, the panel regression allows us to
double-check whether any firm-specific attributes that have significant explanatory power are not
merely picking up the impact of omitted macroeconomic factors. This is in line with Ling and
Naranjo’s (1998) precautionary statement that prior findings of significant abnormal real estate
returns (either positive or negative) that ignored changes in macroeconomic factors may be
potentially biased.
6
3. Performance of Real Estate Stocks in Asia
3.1
Data & Sample Period
In this section, we examine the performance of real estate corporations listed on seven stock markets
in East Asia: Hong Kong (61 companies), Indonesia (23 companies), Malaysia (42 companies),
Singapore (20 companies), South Korea (27 companies), Taiwan (15 companies) and Thailand (24
companies). Information on the financial characteristics and stock returns of the individual firms
over the sample period was extracted from Datastream. For each company, the weekly returns were
compounded to derive its annual holding period returns for each year of the sample period. To
avoid any potential time bias, our sample covers an eleven-year period from January 1992 to June
2002. This period covers the complete boom and bust phases of the most recent real estate market
cycle in Asia. The study period is divided further into two sub-periods: The first sub-period, 1992 to
1997, is generally characterized by strong growth and high asset inflation in most of the Asian
economies. The second sub-period, 1998-2002, reflects the recession stage of the market cycles in
these economies.
3.2
Description of Sample
The financial characteristics of the securitized real estate sector in the various Asian markets over the
sample period are presented in Table 2. Consistent with the recent observations by Kallberg et al
(2002), it is evident that the real estate sectors have undergone major changes post-1997. Firstly, the
median size of the real estate firms has shrunk by 61.5% over the two sub-periods (from USD 220.99
million in the first sample period to only USD 84.99 million in the second sample period). Over the
same period, debt ratios of the real estate corporations also increased from 0.495 to 1.123. In the
expansionary phase of the Asian economies, more than half of the real estate stocks traded at a
premium to their net asset value, as indicated by the median market-to-book value ratio that
exceeded one. Conversely, in the following market recession, the median market-to-book value of
the aggregate real estate sector dropped to 0.53, indicating that real estate stocks were traded at a
median discount of 47% below their net asset values. The median capitalization rate of the real estate
stocks also declined over the sample periods - from 16.0% to 11.2%.
7
Table 2. Financial Characteristics of Real Estate Companies
Market Value Debt-Equity Property Asset Market to Book Earnings(USD million)
Ratio
Intensity Ratio Value Ratio Price Ratio
Dividend
Yield (%)
Sample Period: 1992-2002
Hong Kong
Indonesia
Malaysia
Singapore
South Korea
Taiwan
Thailand
All
229.13
82.06
128.44
360.18
78.12
275.50
35.58
141.16
0.687
1.434
0.332
0.612
2.379
0.740
1.004
0.778
0.676
0.720
0.648
0.793
0.293
0.071
0.230
0.587
0.510
0.950
1.110
0.780
0.830
0.940
0.825
0.750
10.60
11.90
18.40
22.80
13.80
17.30
13.20
13.80
3.55
1.14
1.88
1.65
1.83
1.81
0.00
2.00
0.410
0.874
0.212
0.488
2.173
0.371
0.770
0.495
0.689
0.690
0.587
0.793
0.277
0.072
0.199
0.568
0.600
1.220
1.905
0.935
1.180
2.070
1.425
1.080
10.40
12.15
21.90
31.20
17.30
24.90
16.35
16.00
3.95
1.79
1.79
1.39
2.26
1.24
1.81
2.33
Sub-Period 1: 1992-1997
Hong Kong
Indonesia
Malaysia
Singapore
South Korea
Taiwan
Thailand
All
413.49
176.75
231.62
490.65
105.72
503.52
81.30
220.99
Sub-Period 2: 1998-2002
Hong Kong
177.27
0.971
0.666
0.390
10.75
2.79
Indonesia
22.19
2.133
0.765
0.600
7.60
0.00
Malaysia
73.43
0.799
0.717
0.600
15.00
2.00
Singapore
222.14
1.010
0.789
0.600
13.60
1.92
South Korea
36.47
2.739
0.343
0.400
5.80
0.80
Taiwan
165.02
1.338
0.067
0.590
11.80
3.37
Thailand
18.04
1.383
0.248
0.640
11.20
0.00
All
84.98
1.123
0.616
0.530
11.20
1.66
The reported figures are median values based on 1,424 firm-year observations for the whole period sample. The number of firm-year
observations for sample period 1 (1992-1997) and sample period 2 (1998-2002) are 727 and 804 respectively.
On the whole, real estate stocks in Asia pay out low dividend yield with a median of 2.0% per
annum. This substantiates the fact that in Asia, real estate investment focuses more on capital
movements rather than dividend income. Hong Kong real estate related stocks paid the highest yields
amongst the seven Asian nations – with a median dividend yield of 3.55% per annum. In Thailand,
more than half of the real estate companies did not pay any dividend over the study period. The
property asset intensity ratio also indicates that the median real estate firm listed in the Asian stock
markets held 59% of its total assets in real estate.
8
3.3
Measuring Risk-Adjusted Returns
In our study, we employed weekly stock returns to calculate the annual standard deviations and
compounded return of the real estate firms listed in each of the Asian economies. All the returns
were measured in their respective local currencies. Excess returns are measured by the difference
between the individual firm’s nominal rate of return and the risk free rate, which is represented by
the yield on three-month treasury bills.3 To measure the risk-adjusted returns of the individual real
estate stocks, we adjust the excess returns against the standard deviation (total risks) because the
idiosyncratic risks of individual real estate stocks are more significant in less developed markets.4
Furthermore, this risk measure does not directly depend on the market portfolio.
Hence, we employ the Sharpe index to measure excess return per unit of total risk. The Sharpe index
adjusts returns by both the risk free rate of return and the standard deviation of the returns, with the
numerator measuring the firm’s risk premium and the denominator measuring the total variability of
the returns. Designated Sit, the Sharpe ratio is computed for each company for each year using
weekly returns data as follows:
S it =
Rit − R ft
σ it
(1)
where σ it is the standard deviation of the rate of return for security i during period t, Rft is the riskfree rate of return, and Rit is the compounded annual return for company i in the corresponding
period.
The mean nominal rates of return, standard deviation, excess return, and Sharpe ratio of each market
portfolio are presented in Panel A of Table 3. To compare the performance of the real estate stocks
against the performance of the general stock market, the corresponding return statistics for the
market portfolios in each of the seven Asian economies are reported in Panel B.
Where the yield on treasury bills is not available (such as in Hong Kong, Malaysia, Taiwan and
Thailand), we use the 3-month savings deposit rate as a proxy for the risk free rate. Admittedly, there creates a
slight downward bias in the reported excess return.
3
Bekaert, Erb, Harvey and Viskanta (1997) also argued that for emerging economies, many of their
markets are not fully integrated into the world capital markets. As a result, the beta suggested by CAPM may
not be useful in explaining cross section of average returns. They pointed out that in completely segmented
capital markets, the volatility is the correct measure of risk. Furthermore, Glascock et al (2002) observed that
market-specific information dominates the risk/return behavior of individual real estate markets in Asia largely
because real estate is not a mobile asset and perfect substitutes are not readily available.
4
9
Table 3. Risk-Adjusted Returns of Real Estate Stocks
Panel A:
Mean
Return
Property Stocks
Total
Excess
Risk
Return
Sharpe
Ratio
0.1068
0.1876
0.1425
0.0826
0.2256
-0.0726
0.2306
0.1268
0.5447
0.8649
0.5941
0.4473
0.6718
0.4785
0.8968
0.6186
0.0496
0.0027
0.0890
0.0658
0.1112
-0.1199
0.1611
0.0568
0.1313
-0.0925
0.0948
0.1360
0.0910
-0.1890
-0.1079
0.0493
0.3854
0.2854
0.4532
0.3044
0.1242
0.2681
-0.2602
0.2777
0.3955
0.5154
0.4980
0.3279
0.4786
0.3655
0.4906
0.4386
0.3352
0.1507
0.3901
0.2908
-0.0135
0.2127
-0.3587
0.2039
0.8427
0.3022
0.5974
0.6883
-0.0961
0.5958
-0.7682
0.4221
Panel B:
Mean
Return
General Stocks
Total
Excess
Risk
Return
Sharpe
Ratio
0.1131
0.1045
0.0911
0.0312
0.1003
0.0510
0.0135
0.0721
0.2452
0.2455
0.2718
0.1866
0.3365
0.2701
0.3037
0.2656
0.0607
-0.0672
0.0369
0.0150
-0.0138
0.0024
-0.0542
-0.0029
0.4478
-0.0665
0.4189
0.2274
-0.1807
0.0348
-0.1258
0.1080
0.2206
0.1686
0.1450
0.0359
-0.0446
0.1494
-0.0034
0.0959
0.2239
0.1922
0.2463
0.1356
0.2544
0.2495
0.2719
0.2248
0.1635
0.0274
0.0776
0.0186
-0.2013
0.0907
-0.0963
0.0115
0.9904
0.5307
0.8557
0.4311
-0.6826
0.3460
-0.2225
0.3212
-0.0160
0.2708
-0.0627
Hong Kong
-0.0641
0.636
-0.1256
-0.3051
0.0275
0.3095
-0.1807
Indonesia
0.1281
1.0776
-0.0873
-0.3328
0.0263
0.3025
-0.0121
Malaysia
-0.0463
0.6525
-0.0940
-0.2107
0.0255
0.2479
0.0105
Singapore
-0.0968
0.5437
-0.1160
-0.3106
0.2743
0.4351
0.2112
South Korea
0.3769
0.9602
0.2973
0.3704
-0.0672
0.2947
-0.1035
Taiwan
-0.2113
0.5245
-0.2554
-0.5088
0.0337
0.3418
-0.0038
Thailand
0.5008
1.1205
0.4472
0.2557
0.0435
0.3146
-0.0202
All
0.0275
0.7370
-0.0400
-0.1961
* The mean value for the single-market portfolio is computed based on an equally weighted portfolio comprising all the real estate stocks in each market.
Total risk of the single-market portfolios is represented by standard deviation of the returns.
-0.2034
-0.7831
-0.1052
-0.0169
0.4216
-0.3387
-0.0097
-0.1479
Sample Period: 1992-2002
Hong Kong
Indonesia
Malaysia
Singapore
South Korea
Taiwan
Thailand
All
Sample Period: 1992-1996
Hong Kong
Indonesia
Malaysia
Singapore
South Korea
Taiwan
Thailand
All
Sample Period: 1997-2002
10
Over the 1992-2002 period, Thailand was the best performing market for real estate stocks with a
23.06% annual return but it also had the highest level of volatility. South Korea ranked a close
second with 22.56%, Indonesia ranked third with 18.76%, whilst Taiwan recorded disappointing
negative returns. Singapore registered low annual returns of 8.26% per annum over the sample
period but it was the safest market amongst the seven economies, as reflected by its low standard
deviation. Hong Kong and Malaysia registered modest risk and return levels. Table 3 also shows a
clear shift in the risk-return characteristics of the real estate stocks over the two sub-periods. With
the exception of Thailand, real estate stocks in the other economies performed significantly better
prior to the financial crisis in 1997. On the whole, nominal returns of the real estate stocks were
squeezed in the second sub-periods but at the same time, they recorded higher volatility.
A comparison of the statistics in Panel A and Panel B of Table 3 also shows that the returns of real
estate stocks in Asia are clearly more volatile than the general stocks. This is unlike REIT stocks in
the US, which have betas below 1.0 and as a result, tend to under-perform the market (see Howe and
Shilling, 1990; Chan, Hendershott and Sanders, 1990; and Glascock, 1991). Asian real estate stocks,
on the other hand, are more volatile than the general stock market. Hence, one key distinguishing
behavior of the returns from real state stocks in the US and those in the Asian economies is that US
REIT stocks are generally “defensive”, whilst real estate stocks in Asia are “aggressive” in nature.
Although Thailand’s real estate stocks had the highest nominal returns, they ranked poorly on a riskadjusted basis. Based on the derived Sharpe ratios, real estate stocks in Singapore and Hong Kong
are the best performers over the sample period, followed by real estate stocks in Malaysia and South
Korea. Real estate stocks in Thailand, Indonesia and Taiwan registered negative risk-adjusted returns.
The composite portfolio consisting of all real estate stocks in the seven markets has a Sharpe ratio of
0.049 over the whole sample period. In contrast, the Sharpe ratio for the general stocks was 0.108.
Comparing the Sharpe ratios of the real estate market with the general market in each of the
economies, the risk-adjusted returns of real estate stocks in Hong Kong, Indonesia, Malaysia,
Singapore and Taiwan fared worst than the general stocks. For example, the Sharpe ratio of the
general stock market in Singapore over the sample period 1992-2002 was 0.281, which is significantly
higher than the 0.136 by the equally weighted portfolio of Singapore real estate stocks. Only the real
estate stocks in Thailand and South Korea performed better than the general stock markets. This
may be due to the fact that in these two countries, the general stock market was the worst hit by the
11
Asian Financial Crisis. Nevertheless, the Jensen’s alpha derived from a single index model is
insignificant for most of the individual firms, indicating that there is no superior return to be gained
from investing in Asian real estate stocks.5
Overall, we observe a substantial amount of variation in the risk-adjusted real estate returns across
the different markets as well as over time. This suggests the presence of macroeconomic and market
specific factors that may influence the returns of real stocks. In addition, there is a wide variation in
the risk-adjusted performance of individual companies within the same economy, which indicate
another dimension of firm-specific variables that may be able to explain stock returns. In the next
section, we seek to investigate how the risk-adjusted returns are related to country-specific
macroeconomic variables and firm-specific attributes.
4.
Determinants of Risk-Adjusted Returns
4.1
Panel Regression Models
The second part of our empirical investigation involves examining the extent to which the riskadjusted returns of real estate stocks in Asia can be explained by the attributes of the individual firms.
This is carried out by regressing the Sharpe ratios of the individual firms against a set of firm specific
variables. The effects of time-variant factors is controlled in our multivariate analysis using panel
regression, which can be specified as follows:
S it = α + β X it + u it
(2)
The dependent variable in our model, Sit , is the Sharpe index of the individual firm, which varies
each year, with the subscript i denoting the cross-sectional dimension and t representing the timeseries dimension. Xit is the predetermined vector of variables, α is a scalar, and β is a column matrix
of the partial regression coefficients for the set of explanatory variables in the estimation model.
The error term, uit, for a one-way error component model may be specified as: u it = µ i +ν it ;
The percentage of alphas that was significant at the 0.05 level for each of the market economies in our
study sample is as follows: Hong Kong (3.5%), Indonesia (6.3%), Singapore (3.0%), South Korea (3.2%),
Taiwan (5.2%) and Thailand (7.5%).
5
12
where µ i accounts for any unobservable firm-specific effects that is not included in the regression
model, and ν it represents the remaining disturbances in the regression which varies with individual
firm and time.
In our estimation model, we specify µ i to be fixed for each company over the analysis period. This
represents the effects of omitted variables unique to each company that stay constant over time. An
obvious way to estimate the model is to introduce dummy variables into the regression model.
Hence, the fixed-effects model is also referred to as the least squares dummy variable (LSDV) model. 6
The fixed effects model, which provides a common set of partial regression coefficients whilst
allowing a different intercept for each of the cross-sectional units, model may be specified as:
S it = α i + β X it +ν it
(3)
where α i is the unique intercept for the individual ith firm in our study sample.
4.2 Firm-specific Attributes
We examine the cross-sectional relationship between the risk-adjusted returns and several firm
attributes, namely size, leverage, book-to-market equity, dividend yield, and property asset intensity.
The proxies used to measure the firm characteristics are summarized in Table 4.
Table 4. Summary of Cross-Sectional Variables
Firm Attributes
Measurement
Firm size
Debt-equity ratio
Market-to-book value ratio
Dividend yield
Property asset intensity
Natural Log (Market value equity expressed in USD)
Book value of debt/Market value of equity
Book value of equity/market value of equity
Dividend income/market value of equity
Book value of property assets/Book value of total assets
An alternative specification prescribed in the econometric texts is to assume that the joint-effects of
the omitted (unobserved) variables can be appropriately summarized by a random variable. Panel data model
with such error structure specification is called the random effects model (see Balestra, 1992; 26-27).
6
13
The first four variables have been found to be significant in explaining the cross-section of risk and
returns of general stocks (Fama and French, 1992). Banz (1981) observed that stocks of small firms,
on average, yield higher returns than stocks of large firms. The small-firm effect was also significant
for REITs during the 1974 to 1988 sample period (McIntosh, Liang and Tompkins, 1991; Howe and
Shilling, 1990). Leverage can also explain the cross-section of average stock returns (Bhandari, 1988).
Although nominal return tends to be positively related to debt-equity ratio, the relationship is less
clear on a risk-adjusted basis since leverage also increases the financial risk of the firm.
Several studies have also observed that average returns on US and Japanese stocks were positively
related to the ratio of a firm’s book value of common equity to its market value (see Rosenberg, Reid
and Lanstein, 1985; Chan, Hamao, and Lakonishok, 1991). Cross-sectional studies have shown that
property type specialization have a positive impact on individual REIT returns (Redman and
Manakyan, 1995; Chen and Peiser, 1999). Gyourko and Nelling (1996) also found that the systematic
risk of equity REITs vary by the type of real estate in which they invest, with beta being significantly
higher for retail-oriented REITs than for REITs owning industrial and warehouse properties during
the 1988-1992 sample period. In addition, equity REITs have been observed to outperform mortgage
REITs during 1973-87 (Howe and Shilling, 1990). The impact of geographic concentration is less
conclusive.7 Limitations in our data source did not allow us to retrieve detailed firm-level information
on property type and location of the real estate firms in our sample. As a substitute, we include the
property asset intensity (PAI) ratio as a measure of the dominance of real estate asset over the total
assets of individual firm. A high property asset intensity ratio implies that the company is highly
focused in real estate business. Given the aggressive nature of real estate assets in Asia, this variable
may have a positive impact of the risk-adjusted returns depending on the underlying market
performance.
To evaluate how the firm attributes are correlated to risk-adjusted returns, we first sub-divide the
observations in our sample into five portfolios based on their Sharpe ratio. The properties of the
equal-weighted portfolios are presented in Table 5. The median values, which are less affected by
extreme observations, show some patterns of relationship between risk-adjusted returns and the
7
Whilst Gyourko and Nelling (1996) and Ambrose, Ehrlich, Hughes and Wachter (2000) found that
diversification strategy by geographical regions has no significant benefit on REIT value, Chen and Peiser
(1999) observed that geographical concentration has a positive impact on individual REIT returns. With
respect to specific locality, Redman and Manakyan (1995) noted investments in western United States increase
REIT returns, which they attributed to the expanding economies of California, Washington, and Oregon in the
late 1980s. Howe and Shilling (1990), on the other hand, found that properties located in the Northeast were
positively associated with Jensen alpha (vis-à-vis the West) primarily in the 1979-87 period, coinciding with a
period during which house values rose at extraordinary rates.
14
various attributes of the firm. In particular, firm size and market-to-book value ratio appear to be
associated positively with risk-adjusted returns. Leverage and dividend yield, on the other hand, are
negatively related to the Sharpe ratio. Property asset intensity, however, has little association with the
risk-adjusted returns. These observations are further substantiated in Table 6, which reports the pairwise relationship between each of the variables in our regression models.
Table 5. Properties of portfolios formed on Sharpe ratios
Portfolio
No. of Observations
Sharpe Ratio
1
272
-1.227
2
286
-0.679
3
296
-0.282
4
284
0.337
5
286
1.739
All
1424
-0.277
Firm size (USD million)
Debt-equity ratio
Property asset intensity ratio
Market-to-book value ratio
Dividend yield (%)
105.4
0.893
0.563
0.665
3.10
119.9
0.873
0.595
0.610
2.45
146.7
0.799
0.575
0.670
1.81
117.0
0.825
0.580
0.775
1.79
239.4
0.438
0.614
1.005
1.72
141.2
0.778
0.587
0.750
2.00
* The reported figures are median values for each of the five portfolios, which are firmed based on the firms’ ranking according the
Sharpe ratio.
Table 6. Correlations Matrix for Firm-Specific Attributes
Firm size (SIZE)
Debt-equity ratio (D-E)
Property asset intensity (PAI)
Market-to-book value ratio (MTBV)
Dividend yield (DY)
SIZE
1.000
D-E
-0.386
1.000
PAI
0.110
-0.127
1.000
Sharpe Ratio (SR)
0.182
-0.161
-0.000
Pair-wise correlation matrix for listed variables based on pooled 1,424 firm-year observations.
MTBV
0.290
-0.336
-0.172
1.000
DY
0.041
0.040
0.025
-0.147
1.000
0.223
-0.140
4.3 Estimation Results
To determine the combined effects of the firm attributes, we pooled our cross-sectional observations
over the sample period. The estimation results of the panel regression on each of the markets in our
study sample are presented in Table 7. The Lagrange multiplier and Hausman tests confirm that the
fixed effects model is the most appropriate specification for our regression models. The R2 values
indicate that the explanatory variables together with the firm dummies were able to explain between
19.5% and 43.7% of the variations in the risk-adjusted returns of real estate-related stocks in the
seven equally weighted country portfolios. With the exception of Thailand, the F-ratios for the joint
significance of the explanatory variables are significant in all the regressions.
15
Table 7. Determinants of Risk-Adjusted returns
Firm Attributes
Firm size
Debt-equity ratio
Property asset intensity
Market-to-book value
Dividend yield
Hong Kong
0.7721
(5.23)***
0.0683
(1.00)
0.2939
(0.46)
0.6442
(2.58)**
-0.0906
(4.99)***
Indonesia
-0.0847
(0.51)
0.0313
(0.46)
-0.8401
(1.09)
0.7838
(4.44)***
-0.0712
(2.35)**
Malaysia
0.2925
(1.71)*
-0.0636
(0.78)
-0.9934
(0.79)
-0.0203
(0.18)
-0.1159
(3.99)***
Singapore
-0.4059
(1.44)
-0.2046
(1.78)*
-1.5756
(1.30)
1.0206
(3.36)***
-0.1206
(2.43)**
S. Korea
-0.2630
(1.44)
-0.2802
(4.40)***
-0.5802
(0.47)
0.1906
(0.71)
-0.0218
(0.73)
Taiwan
-0.5620
(1.44)
-0.1166
(0.92)
0.3717
(0.25)
1.0804
(3.19)***
0.0220
(0.79)
Thailand
-0.6018
(3.12)***
-0.1284
(1.81)*
-0.1244
(0.15)
0.5725
(2.38)**
-0.0904
(3.26)***
Composite
0.0403
(0.55)
-0.0613
(2.11)**
-0.2175
(0.52)
0.3337
(4.26)
-0.0805
(7.00)***
No. of Observation
445
111
336
170
167
76
138
1424
R-squared
0.252
0.354
0.195
0.254
0.256
0.437
0.234
0.176
F-value
1.97***
1.77**
1.48**
2.05***
1.56**
2.28***
1.25
1.23**
This Table reports the results of regressing the Sharpe ratio on selected firm-specific attributes. The firms in each country is pooled and estimated using a one-way fixed effects model with firm
dummies. The results are from unbalanced panels because the market economies have different sample sizes. Absolute value of the t-statistic is in parentheses. *, **, and *** represent significance at
the 10%, 5%, and 1% level respectively.
16
Rather than examining each market separately, we outline some observable broad patterns across the
economies. Consistent with our earlier observations, the relationships of risk-adjusted returns with
firm size, leverage and property asset intensity are ambiguous. The estimation results, nevertheless,
show that the risk-adjusted return of real estate stocks is inversely related to dividend yield and
positively to its market to book value ratio. The partial coefficients for these two variables were
statistically significant in five out of the seven country portfolios. The evidence appears to suggest
that firms trading at a premium to their net asset value yield positive risk-adjusted returns.
Conversely, dividend yield is negatively related to the Sharpe ratio measure in all markets except for
Taiwan where it is insignificant. This suggests that real estate stocks with high dividends tend to
under-perform on a risk-adjusted return perspective. The combined results seems to imply that
aggressive real estate stocks sold on the growth story tend to perform better than defensive stocks
sold on the income story. This has implication on the risk-return profile of REITs, which is starting
to gain favor in some of the Asian economies with its high dividend payout.
4.4 Controlling for Time-Variant Effects
To test the robustness of our results, we combine all the observations in our panel regressions with
firm dummies to control for firm-specific effects not captured by the cross-sectional variables. As in
the previous section, the derived Sharpe ratios of the individual firms are regressed against the five
firm attributes with two additional time-varying parameters.
First, we control for the impact of interest rate movements over the sample period by using the first
difference in the risk-free rate of each market economy. We expect real estate stocks to be adversely
affected by interest rate risk (Chen and Tzang, 1988; Ling and Naranjo, 1998; and Devaney, 2001).
Second, we control for regime shifts in the Asian markets following the financial meltdown in 1997.
Kallberg, Liu and Pasqquariello (2002) observed regime shifts in returns and volatility occurred
around 1997-1998 periods. One effect of the crisis was the reduction of real estate returns and an
increase in real estate volatility and correlation with other assets. Our dummy variable takes a value of
zero prior to 1997 and one thereafter. It is expected to have a negative impact on the risk-adjusted
returns of Asian real estate stocks.8
Sagalyn (1990) observed that real estate related stocks are sensitive to the general economic cycle,
whilst Glascock et al. (2002) noted that real estate stocks also exhibit significant positive excess returns in up
markets. Hence, the year-on-year percentage change in the GNP of the respective market economies could also
be measured to represent the general economic cycle. However, this variable is highly correlated with the
interest rate factor. Another alternative adopted by Glascock et al (2002) is to use a dummy variable to define
an up market as one in which the market return exceeds the risk-free rate.
8
17
The estimation results on our composite portfolio comprising the real estate stocks in all the seven
market economies are reported in Table 8.
Due to missing observations, the regressions are
unbalanced panel where different firms have different time-series observations. Regression (1)
reports the estimation results of pooling together all the real estate stocks across the seven Asian
economies on an equal weighted basis with firm dummies. Consistent with our earlier observations
for the country portfolios reported earlier in Table 7, the panel regression shows that the Sharpe ratio
is inversely related to the debt-equity ratio and dividend yield of the individual real estate firms. Debtequity ratio of the firms also has a negative impact on the risk-adjusted returns of real estate stocks.
Table 8. Determinants of Risk-Adjusted Returns (Composite Portfolio)
Regression Model
Firm size
Debt-equity ratio
Property asset intensity
Market-to-book value
Dividend yield
(1)
0.0403
(0.55)
-0.0613
(2.11)**
-0.2175
(0.52)
0.3337
(4.26)***
-0.0805
(7.00)***
(2)
0.1016
(1.58)
-0.0275
(1.03)
-0.1121
(0.43)
0.2524
(4.60)***
-0.0501
(4.80)***
(3)
0.0921
(0.41)
-0.0398
(0.66)
-0.1380
(0.15)
0.3362
(2.44)**
-0.0668
(3.40)***
-0.0352
(4.28)***
(4)
-0.0579
(0.21)
-0.0393
(0.64)
-0.0882
(0.10)
0.2794
(2.09)**
-0.0686
(3.20)***
-0.0393
(4.77)***
-0.4766
(2.43)**
0.176
1.23**
0.472
4.86***
0.188
1.26**
0.202
1.38***
Interest Rate Change
Asian Financial Crisis
Development exposure
Market diversification
R-squared
F-value
(5)
0.0337
(0.12)
-0.0513
(0.76)
0.5169
(0.37)
0.2611
(1.94)*
-0.0695
(2.99)***
-0.0403
(4.68)***
-0.4393
(2.05)**
-1.4109
(0.86)
-1.5725
(3.54)***
0.231
1.61***
This Table reports the results of regressing estimated Sharpe ratio on selected firm-specific attributes using a panel data of 1,424
firm-year observations - where the firms in each country is pooled and estimated using the fixed effects model with firm dummies.
The white-corrected absolute value of the t-statistic is in parentheses. *, **, and *** represent significance at the 10%, 5%, and
1% level respectively.
Regression (2) is a two-way panel regression that includes firm and time dummies that represent the
unspecified time-varying effects over the sample period. The results of this regression again confirm
that dividend yield and market-to-book value ratio of the individual firms have a strong influence on
the risk-adjusted returns of real estate stocks. However, gearing ratio ceased to be significant after the
inclusion of the time-varying factors. This suggests that the gearing ratio variable may simply be
picking up the impact of omitted macroeconomic factors in Regression (1).
18
Regression (3) is a one-way fixed effects panel regression model with change in interest rates
specified as the time-varying factor, whilst Regression (4) is also a one one-way fixed effects panel
regression with the annual change in interest rates and a dummy variable for the impact of Asian
Financial Crisis specified as time-varying factors. As expected, the results of both regressions show
that changes in interest rates and the Asian Financial Crisis have significant negative impact on the
risk-adjusted returns of real estate stocks. The earlier conclusions regarding the significance of
dividend yield and market-to-book value ratio are robust to the addition of macro-economic factors.
Firm size, however, was not statistically significant in all the regressions in Table 8. To test if the lack
of results is due to our selection of the proxy for firm size, we also employed an alternative measure
for firm size – namely, a dummy variable with USD 100 million capitalization as the critical hurdle.
Graff and Young (1997) noted that most institutions regard REITs with lower capitalizations as
inappropriate for their investment portfolios, while REITs with capitalizations of USD 100 million
and above are generally include in their universe of potential investment opportunities. Our reestimation produced an insignificant coefficient for firm size, whilst the other explanatory variables
have the same sign and statistical significance as before.
The firm’s asset characteristic, as represented by its property asset intensity ratio, also does not have
any significant impact on the risk-adjusted return of real estate companies. Besides property asset
intensity, we also examined the significance of the firm’s exposure to real estate development - as
measured by the percentage of total assets represented by vacant land and projects under
constructions. This variable also does not appear to have any impact on the risk-adjusted returns.
However, firm diversification, as measured by the R2 value of the market model using weekly returns,
has a significant negative impact on the Sharpe ratio (Regression 5).9 This suggests that, from the risk
adjusted perspective, focused firms tend to fare better than diversified firms.
For a single security, the R2 of a market model represents the market estimate of the intrinsic
diversification within the firm. In so far as the market index reflects the entire economy, this measure reflects
the degree to which a firm is related to the economy in the aggregate (see Barnea and Logue, 1973; Chung,
1993).
9
19
Conclusion
In this paper, we investigate the risk-adjusted returns of seven emerging Asian economies, namely
Hong Kong, Indonesia, Malaysia, Singapore, South Korea, Taiwan and Thailand. First, we use weekly
stock returns to compute the Sharpe ratio of individual real estate firms in our sample over the study
period from 1992-2002. We then attempt to explain these performances using several firm-specific
attributes including firm size, leverage, property asset intensity, development exposure, dividend
yield, market to book value ratio, and market diversification. In addition, we included two timevarying macroeconomic factors, namely interest rate and economic condition in the panel regression
models.
The findings of our study are relevant to investors who seek to understand the returns
opportunities offered by securitized real estate in the international arena. The empirical results
provide interesting comparison with the performance of real estate securities in US and other mature
economies.
On a risk-adjusted basis, real estate stocks in Singapore and Hong Kong are the best performers over
the sample period, followed by real estate stocks in Malaysia. On the other hand, Taiwan, Thailand
and Indonesia fared badly with negative Sharpe ratios. We also observe that real estate stocks
underperformed the general stocks market in five of the Asian economies, namely Hong Kong,
Indonesia, Malaysia, Singapore and Thailand. However, we did not find any evidence of abnormal
returns from investing in real estate stocks in these economies, which is consistent with the literature.
Using panel data regressions, we find that risk-adjusted returns of real estate stocks are influenced by
their market-to-book value, dividend yield, and market diversification. Firm size, leverage, property
asset intensity and development exposure do not appear to have any significant impact on returns of
real estate stocks. As expected, interest rate movements and the Asian Financial Crisis have an
adverse effect on the risk-adjusted returns of real estate stocks.
20
Acknowledgement
We thank Li Lin for providing valuable research assistance.
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