Anomalies in the European REITs Market. Evidence from ...€¦ · market cannot ignore the...

Anomalies in the European REITs Market. Evidence

from Calendar effects

Gianluca Mattarocci, University of Rome “Tor Vergata”

[email protected]

Roma – January 21th, 2014

mailto:[email protected]

• 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



• 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).


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).


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).


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


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).


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



• 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%


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%


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%


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%


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%


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%


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



• 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







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