Market Efficiency in the Emerging
Securitized Real Estate Markets
Felix Schindler
Centre for European Economic Research (ZEW)
Milan, 26th of June 2010
1
Motivation
• Does the hypothesis of market efficiency hold for
emerging securitized real estate markets?
• While focus has largely been placed on analyzing market
efficiency with respect to international stock markets and
other asset markets, there is comparably little research
conducted on securitized real estate markets.
• It is well documented in financial literature that emerging
markets are less efficient than more developed / matured
markets.
• Existing research on this topic in real estate mainly
focuses on the U.S. real estate stock market and is often
based on the analysis of individual stocks.
• To our knowledge, no study explicitly analyzes market
efficiency in emerging securitized real estate markets.
2
Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Outline
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Motivation
Relevant Literature
Theoretical Background and Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Relevant Literature
• Research is predominantly conducted on the U.S. market
and for individual REITs or direct real estate; see e.g.
Graff and Young (1997), Jirasakuldech and Knight (2005),
Kuhle and Alvayay (2000), Mei and Gao (1995), Nelling
and Gyourko (1998), Seck (1996).
• Research on international real estate markets: Kleiman et
al. (2002), Schindler et al. (2009), Serrano and Hoesli
(2009), Stevenson (2002).
• Conclusion of previous research results: mixed results,
which might depend on the analyzed market, time period,
and applied methodology (autocorrelation, variance ratios,
runs, momentum, ARMA-GARCH-models, etc.).
4
Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Theoretical Background
Weak-Form
Market Efficiency
Semistrong-Form
Market Efficiency
Strong-Form
Market Efficiency
5
Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Methodology
• Market efficiency is analyzed by focusing on the
information contained in historical time series and
the random walk model (joint hypothesis test).
• The following statistical tests are applied:
– Autocorrelation test
– Variance ratio test (heteroscedasticity-robust
estimators)
– Multiple variance ratio test (heteroscedasticity-robust
estimators)
– Runs test (direct test and less restrictive in its
assumptions than tests above)
• Lead and lag structures of other time series and
determinants are not considered.
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Null and Alternative Hypotheses of WeakForm Market Efficiency Tests
Autocorrelation
Coefficient
Variance Ratio
Runs
Random Walk
 (h)  0 for h  0
VR (h)  1 for h  0
Z 0
Mean Aversion
 (h)  0 for h  0
VR (h)  1 for h  0
Z 0
Mean Reversion
 (h)  0 for h  0
VR (h)  1 for h  0
Z 0
Significance Test
7
Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Data Description I
• 12 national emerging securitized real estate
markets and 4 national matured securitized real
estate markets for comparison only.
• Data on Global Property Research (GPR) indices.
• Period: January 1992 – December 2009.
• Frequency: monthly data.
• The presented statistical results are based on
monthly data in local currency.
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Country Indices & Data Availability
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Data Description
10
Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Summary of Statistical Tests
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Trading Strategy Requirements
• Clear ex-ante declaration of the position in the
market and the trading guideline.
• Applying the same information set as for the
statistical tests.
• Objective and restrictive decision criteria.
• Keep it simple!
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Further Requirements Related to
the Market Structure
• Feasible investment opportunity into the national
securitized real estate indices.
• No market impact by individual investors.
• Sufficient liquidity in the markets.
• Tax effects, bid-ask spreads, and transaction
costs are not considered.
• Two different trading strategies are applied:
• Without short selling
• With short selling
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Moving Averages as a Suitable
Instrument
• The imposed restrictions are mainly carried out by
a technical analysis based on moving averages
(criticism: choice of moving average).
• Announced trading strategy:
Invest into the national securitized real estate
market (long position), if index level is above the
moving average, otherwise do not invest or short
the index.
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Results from the Trading Strategy I
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Results from the Trading Strategy II
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Conclusion
• The hypothesis of weak-form market efficiency cannot be
rejected for most emerging securitized real estate markets.
• The statistical test results are supported from technical
analysis. Excess returns compared to a buy-and-hold
strategy seem to be limited compared to matured markets
and are weakly significant only.
• The results are in contrast to the findings by Schindler et
al. (2009) and Serrano and Hoesli (2009) for mainly
matured markets.
• Thus, the often stated hypothesis in financial literature that
emerging markets are less efficient than matured markets
is of limited validity for securitized real estate markets!
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Thank you for your attention!
18
Literature (I)
• Campbell, J.Y.; Lo, A.W.; MacKinlay, A.C. (1997): The Econometrics of Financial
Markets, Princeton/New Jersey.
• Fama, E.F. (1965): Random Walks in Stock Market Prices, Financial Analysts
Journal 21(5), 55-59.
• Fama, E.F. (1970): Efficient Capital Markets: A Review of Theory and Empirical
Work, The Journal of Finance 25(2), 383-417.
• Fama, E.F. (1991): Efficient Capital Markets: II, The Journal of Finance 46(5),
1575-1617.
• Fama, E.F. (1998): Market Efficiency, Long-Term Returns, and Behavioral Finance,
Journal of Financial Economics 49(3),283-306.
• Graff, R.A.; Young, M.S. (1997): Serial Persistence in Equity REIT Returns, Journal
of Real Estate Research 14(3), 183-214.
• Jirasakuldech, B.; Knight, J.R. (2005): Efficiency in the Market for REITs: Further
Evidence, Journal of Real Estate Portfolio Management 11(2), 123-132.
• Kleiman, R.T.; Payne, J.E.; Sahu, A.P. (2002): Random Walk and Market
Efficiency: Evidence from International Real Estate Markets, The Journal of Real
Estate Research 24(3), 279-297.
• Kuhle, J.L.; Alvayay, J.R. (2000): The Efficiency of Equity REIT Prices, Journal of
Real Estate Portfolio Management 6(4), 349-354.
19
Literature (II)
• Lo, A.W.; MacKinlay, A.C. (1988): Stock Market Prices Do Not Follow Random
Walks: Evidence from a Simple Specification Test, The Review of Financial Studies
1(1), 41-66.
• Lo, A.W.; MacKinlay, A.C. (1989): The Size and Power of the Variance Ratio Test
in Finite Samples, Journal of Econometrics 40(2), 203-238.
• Mei, J.; Gao, B. (1995): Price Reversal, Transaction Costs, and Arbitrage Profits in
the Real Estate Securities Market, Journal of Real Estate Finance and
Economics 11(2), 153-165.
• Nelling, E.; Gyourko, J. (1998): The Predictability of Equity REIT Returns, Journal
of Real Estate Research 16(3) 251-268.
• Schindler, F.; Rottke, N.; Fuess, R. (2009): Testing the Predictability and Efficiency
of Securitized Real Estate Markets, ZEW Discussion Paper 09-054.
• Seck, D. (1996): The Substitutability of Real Estate Assets, Real Estate Economics
24(1), 75-95.
• Serrano, C.; Hoesli, M. (2009): Are Securitized Real Estate Returns More
Predictable than Stock Returns?, Journal of Real Estate Finance and Economics
(forthcoming).
• Stevenson, S. (2002): Momentum Effects and Mean Reversion in Real Estate
Securities, Journal of Real Estate Research, 23(1/2), 47-64.
20
Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Appendix
• Statistical test description
• Statistical tests on the results from the technical
trading rule
• Results from autocorrelation tests
• Results from variance ratio tests
• Results from runs tests
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Autocorrelation Test
The examination of the random walk hypothesis in its weakest form is
often conducted by analyzing autocorrelation, whereas the assumption of
independence between lagged returns is reduced to uncorrelated lagged
returns:
ρk  
 rt ; rt  k
 2r   2r
t
t k
k 

.
0
Test statistic:
ρ 2 k  a 2
Q K  T  T  2  
~χ
k 1 T  k
with:
k
= lag / degree of freedom,
(k) = autocorrelation coefficient of order k.
K
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Variance Ratio Test
The approach suggested by Lo and MacKinlay (1988) tests the linearity of
the variance of the return series related to the lag structure:

2
lnP   lnP   q   lnP   lnP    r (q)
t
t q
2
t
t 1
2
t
with: q = lag.
Given the validity of the random walk hypothesis, the variance ratio of the
unbiased estimator of the variance is one:
 2 rt (q) 
VR (q) 
 1.
2
q   rt 
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Runs Test
In the Bernoulli-case, the expected value of the runs is defined by:
EN runs   2n(1  )  2  (1  ) 2 ,
with:
n
Nruns

= number of observation,
= number of runs,
= probability.
Considering the adjustment suggested by Wallis and Roberts (1957), the Zstatistic is calculated as follows:
1
N runs   2nπ (1 - π) a
2
Z
~ N (0,1).
2 nπ (1  π)[1 3π (1 - π)]
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Statistical Tests on the Results I
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Statistical Tests on the Results II
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Statistical Tests on the Results III
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Statistical Tests on the Results IV
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Results from Autocorrelation Tests
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Results from Variance Ratio Tests I
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Results from Variance Ratio Tests II
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Results from Variance Ratio Tests III
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Results from Variance Ratio Tests IV
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Outline
Literature
Methodology
Data Description
Empirical Results
Trading Strategy
Conclusion
Appendix
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Results from Runs Tests
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