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Anomalies in the European REITs Market. Evidence
from Calendar effects
Gianluca Mattarocci, University of Rome “Tor Vergata”
Roma – January 21th, 2014
• Introduction
• Literature review
• Empirical analysis:
• Sample
• Methodology
• Main Results
• Conclusions
Index
Introduction (1/3)
The relevance of a calendar anomaly is affected by the
characteristics of the market in which the financial
instrument is traded. Greater liquidity normally implies lower
relevance of the calendar anomaly due to higher numbers of
traders who can adopt an arbitrage strategy (Lauterbach and
Ungar, 1992).
The literature focuses on more liquid markets (such as the
stock and bond markets) and demonstrates that an increase in
efficiency and liquidity leads to the disappearance of almost all
calendar anomalies in almost all of the most developed
markets (Gu, 2003).
Few studies examine markets with low trade volume (e.g.,
Real estate) to determine the relevance of calendar anomalies
in less liquid markets (Bouges, Jain, and Puri, 2009).
Introduction (2/3)
Research questions:
- Does week-end effect exist in the European REITs
Market?
- Does monthly calendar anomalies affect European REITs
returns?
- Does January and Halloween Effect will exist in European
REITs?
Focus and value added
Introduction (3/3)
Introduction
1. Real Estate Investment Trusts
2. The European REIT industry
3. The Day of the Week Effect
4. The Role of Weekly Calendar Anomalies in European
REITs
5. Monthly Calendar Anomalies
6. Monthly Calendar Anomalies for European REIT
Investors
7. Yearly Calendar Anomalies
8. The January and Halloween Effects in European
REITs
Conclusion
References
Appendix
• Introduction
• Literature review
• Empirical analysis:
• Sample
• Methodology
• Main Results
• Conclusions
Index
Literature review (1/6)
The standard trend in the weekend period is characterized by a positive
performance on Friday and a negative performance on Monday,
with a Monday return that is the lowest performance achieved that week.
Given intra-day patterns, abnormal performance on a particular day of
the week is always explained only in the first hour(s) of the day, in which
there is an abnormal volume of trade in reaction to information disclosed
during the closure of stock exchange market (Chatrath, Christie-David,
and Ramchander, 2012).
From examination of the negative return on Monday, the anomaly is
clear for almost all types of REITs, but its magnitude is significantly
affected by overall market momentum. The weekend effect is more
evident in upturn markets than in downturn markets due to the higher
relevance of the information available during the closed market days
(Friday and Higgins, 2000).
Literature review (2/6)
Considering the abnormal positive performance on Fridays, there is
clear evidence of an increase in performance due to the approximation
of the end of the week (Hepsen, 2012). The maximum positive
performance can be related to both Thursday and Friday instead of only
the last trading day. Therefore, to consider the weekend effect, a longer
time horizon could be considered with respect to only the first and last
trading weekdays (Lee and Ou, 2010).
The relevance of the day of the week effect is also affected by the types
of investors trading in the REIT market, with the main differences
pertaining to the role of individual and institutional investors.
Empirical evidence demonstrates that the calendar anomaly is clearer
when the role of institutional investors is more important, REITs are not
widespread in the market, and the weekend effect is not so relevant to
the financial markets (Chan, Leung, and Wang, 2005).
Literature review (3/6)
Normally positive performance achieved in a month is focused on the
first days of the month and calendar anomalies are more relevant for
smaller REITs (Redman, Manakyan, and Liano, 1997). The differences
in returns at the turn of the month and the rest of the month are driven
more by the capital yield than the dividend yield. Even if REIT dividends
are frequently paid outside the turn of the month period, capital
appreciation is mostly related to these few days of the month (Hardin,
Liano, and Huang, 2005).
Empirical evidence about the time of the month is still mixed and the
relevance of the first half of the month is affected by the time horizon
considered and the characteristics of the sample. The main differences
in the results are related to the type of REIT (Connors, Jackman, Lamb,
and Rosenberg, 2002) and country (Hepsen, 2012).
Literature review (4/6)
Before a holiday, the returns are significantly higher than those for the
other days of the year and the result is significantly affected by REIT
type and size. Regarding the residential, diversified, office, and industrial
sectors, the return obtained the day before a holiday is at least four
times the average return on all other trading days (Connors, Jackman,
Lamb, and Rosenberg, 2002), while other types of REITs exhibit not
statistical significant differences in returns. The holiday effect is usually
stronger for small REITs than for medium and large ones and the
calendar anomalies are therefore more economically relevant for
investors focused on small REIT investments (Redman, Manakyan and
Liano, 1997).
Friday 13th and 17th are studied prevalently in the stock market but,
because there is still debate about the existence of this calendar
anomaly, there is no evidence for its role in other markets. No studies
provide evidence of the existence of such an anomaly in the REIT
market
Literature review (5/6)
The January effect is a calendar anomaly clearly identified in the
industry that affects REITs differently on the basis of their features.
Unlike for other stocks, the relevance of the calendar anomaly is not only
related to firm size but also to the type of REIT. The literature focuses on
the differences between equity, mortgage, and mixed REITs and the
empirical evidence demonstrates that the calendar anomaly is more
significant for mortgage REITs, especially smaller ones (Colwell and
Park, 1990).
The relevance of the January effect is related to the past performance of
REITs and past losers are normally those that are more affected by the
calendar anomaly (Zhou and Sah, 2010). This evidence supports the
hypothesis that one of the main motivations behind the calendar
anomaly is the tax selling hypothesis: the decrease of prices near the
end of the year is driven by an abnormal volume of sales released for
monetizing the losses before the fiscal year close and decrease the
amount of taxes to be paid (Friday and Peterson, 1997).
Literature review (6/6)
The seasonality of REITs is frequently discussed in the literature and
empirical evidence supports the hypothesis that the efficiency of that
market cannot ignore the existence of calendar anomalies (Connors,
Jackman, Lamb, and Rosenberg, 2002).
The Halloween effect is significant for almost all worldwide REIT
markets and the returns achieved in the summer period are significantly
lower than in the rest of the year. As for other financial instruments, the
main motivation behind the calendar anomaly is related to investor
behavior, market risk, and information disclosure. Consistent with
evidence provided for other financial instruments, the anomaly is more
evident for smaller REITs and there is also a reputation effect that
implies an even higher premium for younger firms (Brounen and Ben-
Hamo, 2009).
• Introduction
• Literature review
• Empirical analysis:
• Sample
• Methodology
• Main Results
• Conclusions
Index
Empirical analysis: Sample
Number of REITs
Belgium France Germany Italy Netherlands Turkey UK
2003 3 8 1 1 5 3 12
2004 3 8 1 1 5 3 12
2005 2 6 1 1 3 1 11
2006 2 7 1 2 3 2 12
2007 3 7 1 2 3 2 12
2008 3 7 2 2 3 2 13
2009 3 7 2 2 3 2 13
2010 3 7 2 2 3 2 13
2011 3 7 2 2 3 3 13
2012 3 7 2 2 3 3 13
Type of data: Daily rate of return
Dummy variables for different types of calendar effect
Empirical analysis: Methodology (1/2)
We test the existence of calendar anomaly for both the performance and the extra-
performance
Type of anomalies: Week-end effect, turn of the month, time of the month, holiday effect, Friday 13th and 17th, January effect and Halloween effect
Empirical analysis: Methodology (2/2)
The role of the calendar anomaly is analysed through a buy and hold modified
strategy
Type of anomalies: Week-end effect, turn of the month, time of the month, holiday effect, Friday 13th and 17th, January effect and Halloween effect
Empirical analysis: Main Results
Return Statistics 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2003
2012
Monday Average -0.02% 0.09% 0.06% -0.06% -0.39% -0.33% -0.04% 0.29% -0.42% -0.04% -0.08%
% Pos 41.26% 43.01% 37.87% 40.51% 33.02% 37.50% 45.49% 47.84% 36.31% 44.71% 40.75%
Tuesday Average 0.09% 0.19% 0.16% 0.00% -0.04% 0.25% -0.06% -0.05% 0.05% 0.08% 0.07%
% Pos 38.99% 46.74% 39.24% 42.50% 42.12% 46.29% 41.05% 46.50% 48.78% 46.91% 43.91%
Wednesda
y
Average -0.13% 0.07% 0.08% 0.23% 0.06% -0.21% 0.23% 0.01% -0.01% 0.02% 0.04%
% Pos 35.11% 44.41% 38.67% 51.35% 43.03% 43.51% 50.72% 44.46% 47.09% 48.25% 44.66%
Thurday Average 0.08% 0.04% -0.03% 0.21% -0.18% -0.43% 0.11% 0.09% -0.19% 0.13% -0.02%
% Pos 39.86% 40.59% 36.90% 49.81% 41.71% 36.12% 44.16% 45.98% 45.05% 50.64% 43.08%
Friday Average 0.11% 0.17% 0.27% 0.21% 0.06% -0.22% 0.19% -0.16% 0.17% 0.11% 0.09%
% Pos 40.03% 45.00% 42.10% 48.40% 44.53% 40.69% 47.60% 39.17% 52.27% 50.87% 45.07%
Empirical analysis: Main Results
Return
TOM
Statistics Belgium France
German
y Italy
Netherla
nds
Turkey UK
-9 days
+9 days
Average 0.00% 0.06% 0.07% 0.08% 0.01% 0.04% 0.05%
% Pos 45.98% 42.84% 43.25% 46.83% 48.17% 40.53% 44.06%
-5 days
+2days
Average 0.08% 0.19% 0.16% 0.27% 0.14% 0.03% 0.15%
% Pos 48.60% 45.23% 43.82% 49.47% 50.25% 40.26% 45.32%
-2 days
+4 days
Average 0.05% 0.13% 0.20% 0.21% 0.06% 0.23% 0.13%
% Pos 47.47% 44.60% 45.35% 49.39% 50.03% 43.61% 47.00%
-1 day Average 0.12% 0.30% 0.56% 0.29% 0.41% -0.12% 0.20%
% Pos 53.79% 50.11% 47.32% 50.69% 55.36% 40.21% 43.52%
-1 day +3
days
Average 0.11% 0.19% 0.20% 0.32% 0.18% 0.27% 0.17%
% Pos 49.82% 46.14% 42.99% 49.31% 51.72% 43.58% 47.90%
-1 day +4
days
Average 0.06% 0.13% 0.20% 0.22% 0.07% 0.29% 0.14%
% Pos 47.90% 44.62% 44.65% 48.79% 50.24% 44.11% 47.35%
-1 day +8
days
Average -0.01% 0.04% 0.04% 0.05% -0.02% 0.07% 0.06%
% Pos 45.97% 42.81% 43.75% 47.24% 48.72% 42.03% 45.58%
Empirical analysis: Main Results
Belgium France Germany Italy
Netherla
nds
Turkey UK
Return FHM -0.02% 0.00% -0.03% -0.02% -0.06% 0.07% 0.03%
SHM 0.02% 0.06% 0.02% 0.02% 0.04% 0.00% 0.02%
D CAPM FHM -0.02% 0.02% -0.03% -0.01% -0.05% 0.05% 0.04%
SHM 0.00% 0.03% -0.01% 0.00% 0.00% -0.06% -0.01%
D Fama
& French
FHM -0.03% 0.03% -0.05% 0.03% -0.05% 0.06% 0.05%
SHM -0.01% 0.03% -0.03% 0.00% -0.01% -0.06% -0.02%
D
Carhart
FHM -0.36% -0.48% -0.39% -0.81% -0.59% -0.23% -0.60%
SHM -0.33% -0.48% -0.37% -0.85% -0.53% -0.36% -0.65%
Empirical analysis: Main Results
Statistics Return CAPM
model
F&F
Model
Carhart
Model
Holiday Average 0.24% 0.01% 0.02% -0.52%
% Pos 34.44% 40.91% 48.40% 35.09%
International
holiday
Average 0.33% -0.01% -0.01% -0.55%
% Pos 35.69% 40.66% 48.04% 34.45%
Daily average Average 0.02% 0.00% 0.00% -0.55%
% Pos 44.25% 47.90% 48.43% 34.71%
Empirical analysis: Main Results
EW Performance
+ WE
EW Performance
+ Friday 13th
EW Performance
+ Friday 17th
Average
return % Positive
Average
return % Positive
Average
return
%
Positive
All 0.18% 60.00% 0.07% 59.81% 0.08% 60.19%
VW Performance + WE VW Performance + Friday
13th
EW Performance +
Friday 17th
Average
return % Positive
Average
return % Positive
Average
return
%
Positive
All 0.23% 60.00% 0.10% 55.38% 0.10% 55.96%
Empirical analysis: Main Results
EW EW
+ January Effect VW
VW
+ January effect
2003 4.46% 2.06% 6.10% 3.71%
2004 14.28% 3.72% 38.02% 6.05%
2005 6.06% 1.37% 23.66% 4.50%
2006 1.58% 0.46% 50.69% 4.44%
2007 -0.49% 0.16% -19.67% 4.43%
2008 -2.13% 0.25% -45.61% 4.09%
2009 1.23% -0.18% 30.77% 3.37%
2010 0.43% 0.18% 9.52% 3.40%
2011 -0.60% 0.22% -11.75% 2.93%
2012 0.61% 0.18% 21.29% 2.29%
All 2.54% 0.84% 10.30% 3.92%
Empirical analysis: Main Results
EW EW + Halloween
effect VW
VW + Halloween
effect
2003 4.46% 3.30% 6.10% 4.23%
2004 14.28% 10.31% 38.02% 11.56%
2005 6.06% 5.59% 23.66% 7.41%
2006 1.58% 1.19% 50.69% 3.19%
2007 -0.49% 0.27% -19.67% 2.39%
2008 -2.13% -0.23% -45.61% 1.64%
2009 1.23% 0.26% 30.77% 2.02%
2010 0.43% 0.31% 9.52% 1.90%
2011 -0.60% 0.15% -11.75% 1.49%
2012 0.61% 0.43% 21.29% 1.46%
All 2.54% 2.16% 10.30% 3.73%
• Introduction
• Literature review
• Empirical analysis:
• Sample
• Methodology
• Main Results
• Conclusions
Index
• In view of the aggregate market data, day-by-day
performance in the REIT market is coherent with the
weekend effect theory, with the highest average
performance registered on Fridays and the lowest
average performance on Mondays.
• The turn of the month effect for the European REITs is
stronger in the first days after the month change with
respect to the last days of the previous month and the
holiday effect is relevant the day before the holiday.
• The REIT industry is characterized by yearly calendar
anomalies such as the January and the Halloween effects
and during the last years these calendar anomalies have
not disappeared.
Conclusions
Reference
Mattarocci G. (2014), “Anomalies in the European REITs
Market. Evidence from Calendar effects”, Palgrave
MacMillan, Basingstoke
Contact Information
Gianluca Mattarocci University of Rome Tor Vergata
e-mail: [email protected]
Thanks for you attention