CALENDAR EFFECTS IN THE PHILIPPINE STOCK MARKET - JITBM

International Journal of Information Technology and Business Management 29

th July 2012. Vol.3 No. 1

© 2012 JITBM & ARF. All rights reserved

ISSN 2304-0777 www.jitbm.com

[64]

CALENDAR EFFECTS IN THE PHILIPPINE STOCK

MARKET

Catherine Kalayaan S. Almonte

Email: [email protected]

ABSTRACT

The returns of the Philippine stock market’s Composite Index (PSEi) were tested for conformity

with Fama’s (1970) weak form of market efficiency (Almonte, 2004) using daily values from 2001 to 2010.

Analyses were made annually and cumulatively. The results revealed the existence of a day-of-the-week

effect, the month-of-the-year effect was evidently absent, and the quarter-of-the-year effect was also absent

with the exception of the phenomenon occurring in 2002. Thus, generally, traders are advised to buy

equities on a Tuesday and sell them on a Thursday or Friday.

Keywords: weak form of market efficiency, day-of-the-week effect, month-of-the-year effect,

quarter-of-the-year effect, stock market

1. INTRODUCTION

One engages in trading equities for the

purpose of earning returns that are substantially

higher than the risk-free rate. It would be

beneficial for a trader to know if a pattern exists

in a certain stock market to time one’s buying

and selling activities in order to maximize

returns (Almonte, 2004). Financial theory

suggests that timing the market is a waste of time

(Fama, 1970). However, as discussed by

Almonte (2004), various empirical research

indicate otherwise (e.g. Poshakwale, 1996; Chia,

Liew, & Wafa, 2008; and Wyème & Olfa, 2011).

Hence, this paper aims to determine if a trend is

present in the Philippine stock market’s

Composite Index (PSEi) by studying the day-of-

the-week (Almonte, 2004), month-of-the-year,

and quarter-of-the-year effects using daily

returns. The presence of any calendar effect may

be used by traders in conjunction with technical

analysis.

1.1. Theoretical Framework

The efficient market hypothesis (EMH)

states that prices of securities reflect all available

information (Fama, 1970). It assumes a “. . .

“perfect” market in which (1) securities are

typically in equilibrium, (2) security prices fully

reflect all public information available and react

swiftly to new information, and, (3) because

stocks are fully and fairly priced, investors need

not waste time looking for mispriced securities”

(Gitman, 2009, p. 344).

There are three forms of market

efficiency: (1) weak, (2) semi-strong, and (3)

strong (Fama, 1970). The weak form asserts that

past prices is already factored into securities’

prices; the semi-strong form suggests that public

information is already incorporated into

securities’ prices; and the strong form says that

asymmetric information is already reflected into

securities’ prices (Fama, 1970).

Similar to a research done by Almonte

(2004), this paper focuses on the weak form of

market efficiency (Fama, 1970). The weak form

is related to the random walk behavior of stock

prices (Fama, 1970). In essence, if securities

prices follow a random walk, then trends (such

as calendar effects) should not be present (Fama,

1970; Aly, Mehdian, & Perry, 2004; Almonte,

2004).

1.2. Day-of-the-Week Effect

The weekend effect (also called the

Monday Effect or the day-of-the-week effect)

refers to the trend that stock returns are higher on

Fridays compared to Mondays (Weekend Effect,

n.d.; Hirt & Block, 2012). Consistent with

Almonte (2004), a day-of-the-week effect is

defined as at least one trading day in a week

wherein returns for that day are statistically

mailto:[email protected]





[65]

significantly different from at least one other

day.

1.3. Month-of-the-Year Effect

The January Effect refers to the

phenomenon that stock prices are generally

higher on January because investors sell their

stocks on December to record losses for tax

purposes and then buy back the shares on

January (Mishkin & Eakins, 2006; Fama &

French, 1980 (in Hirt & Block, 2012)). For

purposes of this paper, consistent with

Selvakumar (2011), a month-of-the-year effect is

defined as at least one month in a calendar year

wherein returns for that month are statistically

significantly different from at least one other

month.

1.4. Quarter-of-the-Year Effect

The quarter-of-the-year effect is the

occurrence where securities prices for at least

one quarter are statistically significantly different

from at least one other quarter (Davidsson,

2006).

1.5. The Association of Southeast Asian

Nations (ASEAN) Exchanges

The ASEAN Exchanges is comprised of

seven exchanges (located in six countries) that

work together to promote the ASEAN capital

market (ASEAN Exchanges website,

http://www.aseanexchanges.org/, 2011).

Selected data about the member exchanges are

given in Table 1 (ASEAN Exchanges website,

http://www.aseanexchanges.org/, 2011).

Table 1.

SELECTED DATA: ASEAN EXCHANGES MEMBERS

As of March 31, 2011 (for BM, HNX, HOSE, IDX, PSE, SET); As of December 31, 2010 (for SGX)

Country Malaysia Vietnam Vietnam Indonesia Philippines Thailand Singapore

Stock

Exchange

Bursa

Malaysia

(BM)

The

Hanoi

Stock

Exchange

(HNX)

The

Hochi-

minh

Stock

Exchange

(HOSE)

Indonesia

Stock

Exchange

(IDX)

The

Philippine

Stock

Exchange

(PSE)

The Stock

Exchange

of

Thailand

(SET)

Singapore

Exchange

(SGX)

Listed

Compa-

nies

955 379 283 422 249 541 782

Domestic

Capitali-

zation (in

USD

millions)

426,000 5,359 28,286 376,599 159,402 277,732 728,760

Turnover

Velocity

42% No

available

data

57.1% 32.21% 17.16% 83.5% 43%

Mainboard,

32% Catalist

The BM has the most number of

companies that are publicly listed, representing

26% (955 out of 3,611) of the total. The SGX

leads the group when it comes to domestic

capitalization, representing 36% (728,760

divided by 2,002,138) of the total while the SET

leads the pack in terms of turnover velocity.

The focus of the paper is on the

Philippine market. The number of firms listed in

the Philippines represents only 7% (249 out of

3,611) of the total. In terms of domestic

capitalization, it is ranked fifth (behind the

Singapore, Malaysia, Indonesia, and Thailand

exchanges). Moreover, the Philippines’

domestic capitalization is only 8% (159,402

divided by 2,002,138) of the group. With

regards to turnover velocity, save for the HNX

wherein no data was available, the PSE has the

lowest number at 17%. Clearly, the Philippine

equities market has room for improvement.

1.6. An Overview of the Philippine Stock

Market

The Philippine Stock Exchange (PSE) is

the organized securities exchange in the





[66]

Philippines. As one industry veteran better

describes the exchange, it “. . . is the organized

securities exchange for equities and equity-

linked derivatives in the

Philippines. . . ” (J.J.F. Lago, personal

communication, January 30, 2012).

Its main index, the Philippine

Composite Index (PSEi), is comprised of 30

firms (PSE Academy website,

http://www.pseacademy.com.ph/LM/glossary/Gl

ossary.html#P, 2011) belonging to different

sectors such as: financials, holding companies,

industrials, property, services, and mining and

oil (The Philippine Stock Exchange, Inc.,

2011a).

The PSE uses a five-day trading week

(from Monday to Friday) except for holidays and

when the Clearing Office of the Bangko Sentral

ng Pilipinas (BSP) is closed (The Philippine

Stock Exchange, Inc. website,

http://www.pse.com.ph/, 2007). Up until

September 2011, trading hours start from 9:30

AM and ends at 12:10 PM (The Philippine Stock

Exchange, Inc. website, http://www.pse.com.ph/,

2007). From October 2011 until December

2011, trading hours were extended until 1:00 PM

(The Philippine Stock Exchange, Inc., 2011b).

Beginning the year 2012, trading hours were

changed to last for the whole day, from 9:30 AM

to 3:30 PM (The Philippine Stock Exchange,

Inc., 2011c).

2. LITERATURE

2.1. Day-of-the-Week Effect

A paper about the Egyptian stock

market did not support the existence of the day-

of-the-week effect (Aly et al., 2004); thus, said

research supports the weak form of market

efficiency (Fama, 1970).

On the other hand, other studies

contradict said phenomenon (Almonte, 2004).

Some examples are: a study of the Bombay

Stock Exchange National Index (BSENI)

wherein it was concluded that Monday returns

were at their lowest while Friday returns were at

their highest (Poshakwale, 1996), another paper

on the Indian stock market showed that Friday

returns were highest compared to the other

trading days of the week (Selvakumar, 2011), a

research on the Philippine stock market’s

Composite Index that showed Monday and

Tuesday returns were significantly lower

compared to Friday returns (Almonte, 2004), a

paper on the “. . . Taiwan, Singapore, Hong

Kong and South Korea stock markets” (Chia,

Liew, & Wafa, 2008, p. 1) that determined

Monday returns were negative while Friday

returns were positive for all markets except

South Korea’s (Chia et al., 2008), and a study on

the Pakistani stock market that concluded

positive returns for Tuesdays (Hussain, Hamid,

Akash, & Khan, 2011).

Thus, as with Almonte (2004), various

empirical researches provide inconclusive

evidence regarding the presence of the day-of-

the-week effect in different equities markets.

2.2. Month-of-the-Year Effect

A study on the returns of the Bahrain

All Share Index revealed that a month-of-the-

year effect was non-existent, even when the time

period of the study was divided into two periods:

(1) pre-global financial crisis and (2) during the

crisis (Al-Jafari, 2011). Selvakumar’s (2011)

paper also did not support a month-of-the-year

effect.

Contrary to the results of the Al-Jafari

(2011) and Selvakumar (2011) researches, other

studies supported the existence of a month-of-

the-year effect. Examples include: a paper that

examined the returns of the Karachi Stock

Exchange where May returns were negative

compared to January returns (Zafar, Urooj, &

Farooq, 2010), a research on the returns of the

Australian stock market where “. . . April, July

and December. . . ” (Marrett & Worthington,

2011, p. 3) returns were higher compared to that

of other months (Marrett & Worthington, 2011),

and a study on the returns of the Tunis Stock

Exchange (TSE) where April returns were higher

compared to that of other months (Wyème &

Olfa, 2011).

Therefore, similar with the studies

about day-of-the-week effects (Almonte, 2004),

different studies show inconclusive evidence

regarding the existence of the month-of-the-year

effect in various stock markets.

2.3. Quarter-of-the-Year Effect

To date, very few empirical studies

have been found with regards to the quarter-of-

the-year effect. Davidsson (2006) found such an

effect in his study of the S&P 500 index using

data from 1970-2005 (the fourth quarter was the





[67]

best period). The CXO Advisory Group, LLC

(http://www.cxoadvisory.com/4080/calendar-

effects/end-of-quarter-effect/, June 14, 2012)

also studied the existence of the quarter-of-the

year effect in the S&P 500 index using data from

1950-2012 and, consistent with Davidsson

(2006), determined that the fourth quarter was

the best.

The lack of literature on this particular

calendar anomaly is primarily the reason why it

is being studied in this paper.

3. HYPOTHESES

H1 The day-of-the-week effect

exists in the Philippine stock

market (Almonte, 2004).

H2 The month-of-the-year effect


market.

H3 The quarter-of-the-year effect


market.

4. METHODOLOGY

The PSEi was used as the sample to

study the presence of calendar effects in the

Philippine stock market.

Since the trading hours of the Philippine

market were changed on October 2011 (The

Philippine Stock Exchange, Inc., 2011b), the

time frame of the study was set from the year

2001 to 2010 (the last ten years wherein the last

year reflected the end of a calendar year).

The data of the PSEi was obtained

through Technistock (used by professionals to

access data regarding securities).

Using daily returns as the main data,

analyses were conducted annually (e.g. 2001,

2002, and so on) and cumulatively (e.g. from

2001 to 2002, 2001 to 2003, and so on) to test if

any of the calendar effects exists and/or persists.

Returns were computed using the

formula (Keown, Martin, Petty, & Scott, Jr.,

2005):

11t at time Value

tat time Value Return

Similar to Almonte (2004), numeric

codes were used to signify the day in the week,

the month in the year, and the quarter in the year:

a day referring to Monday was coded as 1,

Tuesday was coded as 2, and so on; a month

referring to January was coded as 1, February

was coded as 2, and so on; a quarter referring to

the first quarter of the calendar year was coded

as 1, a quarter referring to the second quarter of

the calendar year was coded as 2, and so on.

All statistical calculations were done

using the software XLSTAT 2011.

The returns were tested for normality.

The results indicate that the returns of the PSEi

are not normally distributed (Table 2A and Table

2B). Hence, consistent with Almonte (2004), the

Kruskal-Wallis Test was used to test the

presence of calendar effects in the market.

Any existence of a calendar effect was

further explored by determining which day,

month, or quarter was statistically significantly

different from a different day, month, or quarter

by using the Steel-Dwass-Critchlow-Fligner

Procedure embedded in the software.

Summary statistics were analyzed

somewhat similar to what was done by Agathee

(2008).

This research is an updated and more

detailed version of what was done by Almonte

(2004).





[68]

Table 2. A.

TEST FOR NORMALITY

Jarque-Bera Test at = 0.05

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

JB

(Observed

Value)

20,119

.316

31.008 27.793 11.26

8

6.728 41.803 397.41

4

315.81

2

18.479 10.509

JB (Critical

Value)

5.991 5.991 5.991 5.991 5.991 5.991 5.991 5.991 5.991 5.991

DF 2 2 2 2 2 2 2 2 2 2

p-value <

0.0001

<

0.0001

<

0.0001

0.004 0.035 <

0.0001

<

0.0001

<

0.0001

<

0.0001

0.005

Table 2. B.

TEST FOR NORMALITY

Jarque-Bera Test at = 0.05

2001

to

2002

2001

to

2003

2001

to

2004

2001

to

2005

2001

to

2006

2001

to

2007

2001

to

2008

2001

to

2009

2001

to

2010

JB

(Observed Value)

39,362

.009

43,163

.114

46,151

.256

45,956

.672

39,790

.870

29,210

.826

21,293

.392

20,243

.562

22,052

.724

JB (Critical Value) 5.991 5.991 5.991 5.991 5.991 5.991 5.991 5.991 5.991

DF 2 2 2 2 2 2 2 2 2

p-value <

0.0001

<

0.0001

<

0.0001

<

0.0001

<

0.0001

<

0.0001

<

0.0001

<

0.0001

<

0.0001

5. RESULTS AND ANALYSIS

Based on the data presented in Table

3A, Tuesdays had the most number of lowest

mean returns (five out of ten years, i.e. 2001,

2002, 2005, 2006, and 2009) followed by

Mondays (four out of ten years, i.e. 2003, 2004,

2005, and 2007). On the other hand, Thursdays

had the most number of highest mean returns

(six out of ten years, i.e. 2003, 2005, 2006, 2007,

2009, and 2010). In terms of trading days,

Mondays had the least number in eight out of ten

years (i.e. 2001, 2002, 2004, 2005, 2006, 2007,

2008, and 2010) while Tuesdays had the most

number in seven out of ten years (i.e. 2002,

2003, 2004, 2005, 2008, 2009, and 2010)

followed by Wednesdays (in six out of ten years,

i.e. 2001, 2005, 2006, 2007, 2008, and 2010).

According to the results presented in

Table 3B, Tuesdays had the most number of

lowest mean returns (nine out of nine times, i.e.

2001 to 2002, 2001 to 2003 until 2001 to 2010).

Fridays had the most number of highest mean

returns (seven out of nine times, i.e. 2001 to

2002, 2001 to 2003 until 2001 to 2008) followed

by Thursdays (five out of nine times, i.e. 2001 to

2006, 2001 to 2007 until 2001 to 2010). With

regards to the number of trading days, Mondays

had the least number of trading days in eight out

of nine times (i.e. all cumulative periods with the

exception of the years 2001 to 2003) while

Tuesdays had the most number in six out of nine

times (i.e. 2001 to 2003, 2001 to 2004, 2001 to

2005, 2001 to 2006, 2001 to 2009, and 2001 to

2010) followed by Wednesdays (in four out of

nine times, i.e. 2001 to 2002, 2001 to 2003, 2001

to 2007, and 2001 to 2008).





[69]

Table 3. A.

SUMMARY STATISTICS

Day-of-the-Week Effect

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Return

1

Obs. 47 48 51 47 45 47 44 45 46 44

Mean 0.001 -0.001 0.001 -0.002 -0.001 0.002 -0.001 -0.004 0.002 0.001

Return

2

Obs. 49 50 51 52 51 50 50 51 52 51

Mean -0.005 -0.003 0.002 0.001 -0.001 -0.002 0.004 -0.003 0.000 0.000

Return

3

Obs. 52 49 49 50 51 51 52 51 50 51

Mean -0.003 -0.001 0.001 0.003 0.002 -0.002 -0.001 0.003 0.002 0.001

Return

4

Obs. 50 50 49 50 51 50 50 49 49 51

Mean 0.000 0.000 0.002 0.001 0.002 0.006 0.004 -0.005 0.004 0.004

Return

5

Obs. 49 49 47 48 48 49 48 50 45 47

Mean 0.003 0.001 0.002 0.001 0.001 0.004 -0.001 -0.003 0.003 -

0.001

Table 3. B.

SUMMARY STATISTICS

Day-of-the-Week Effect

2001

to

2002

2001

to

2003

2001

to

2004

2001

to

2005

2001

to

2006

2001

to

2007

2001

to

2008

2001

to

2009

2001

to

2010

Return 1

Obs. 95 146 193 238 285 329 374 420 464

Mean 0.000 0.000 0.000 0.000 0.000 0.000 -0.001 0.000 0.000

Return 2

Obs. 99 150 202 253 303 353 404 456 507

Mean -0.004 -0.002 -0.001 -0.001 -0.001 0.000 -0.001 -0.001 -0.001

Return 3

Obs. 101 150 200 251 302 354 405 455 506

Mean -0.002 -0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Return 4

Obs. 100 149 199 250 300 350 399 448 499

Mean 0.000 0.001 0.001 0.001 0.002 0.002 0.001 0.002 0.002

Return 5

Obs. 98 145 193 241 290 338 388 433 480

Mean 0.002 0.002 0.002 0.002 0.002 0.002 0.001 0.001 0.001

The Kruskal-Wallis Test shows that the

day-of-the-week effect is only evident during the

years 2001 and 2006 (Table 4A). However,

when the years were accumulated, the

phenomenon is present at all times (Table 4B).





[70]

Table 4. A.

TEST FOR DAY-OF-THE-WEEK EFFECT

Kruskal-Wallis Test at = 0.05

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

K

(Observed

Value)

12.893 6.718 0.878 6.636 2.432 19.555 2.243 6.419 3.190 6.668

K (Critical

Value)

9.488 9.488 9.488 9.488 9.488 9.488 9.488 9.488 9.488 9.488

DF 4 4 4 4 4 4 4 4 4 4

Asymptotic

p-value

(two-tailed)

0.012 0.152 0.928 0.156 0.657 0.001 0.691 0.170 0.527 0.155

Table 4. B.

TEST FOR DAY-OF-THE-WEEK EFFECT


2001 to

2002

2001

to

2003

2001

to

2004

2001

to

2005

2001

to

2006

2001

to

2007

2001

to

2008

2001

to

2009

2001

to

2010

K (Observed

Value)

18.867 12.347 11.073 12.818 19.167 17.063 12.129 14.516 15.347

K (Critical Value) 9.488 9.488 9.488 9.488 9.488 9.488 9.488 9.488 9.488

DF 4 4 4 4 4 4 4 4 4

Asymptotic p-

value (two-tailed)

0.001 0.015 0.026 0.012 0.001 0.002 0.016 0.006 0.004

For the year 2001 (Table 5A), there was

a significant difference between Tuesday and

Friday returns. The result suggests that one buy

on a Tuesday (since it has the lowest mean rank

of 99.306) and sell on a Friday (since it has the

highest mean rank of 149.918)

Table 5. A.

SIGNIFICANCE OF THE DAY-OF-THE-WEEK

EFFECT FOR 2001

Steel-Dwass-Critchlow-Fligner Procedure;

Bonferroni Correction

Obs. Sum of

Ranks

Mean of

Ranks

Return 1 47 5,612.0000 119.404

Return 2 49 4,866.0000 99.306

Return 3 52 6,314.0000 121.423

Return 4 50 6,490.0000 129.800

Return 5 49 7,346.0000 149.918

Significant

p-value Return 2 and Return 5 at 0.003

For the year 2006 (Table 5B), there

were several significant differences among the

trading days. Specifically, Tuesday returns were

different from Thursday returns while

Wednesday returns were different from Thursday

returns. The results indicate that one buy on

either a Tuesday or a Wednesday (although

Wednesday is preferred given that it has the

lowest mean rank of 100.843 among the five

trading days) and sell on a Thursday (since it has

the highest mean rank of 157.860).

Table 5. B.


EFFECT FOR 2006



Obs. Sum of

Ranks

Mean of

Ranks

Return 1 47 5,740.0000 122.128

Return 2 50 5,415.0000 108.300

Return 3 51 5,143.0000 100.843

Return 4 50 7,893.0000 157.860

Return 5 49 6,437.0000 131.367

Significant

p-values Return 2 and Return 4 at 0.011,

Return 3 and Return 4 at 0.000

For the years 2001 to 2002 (Table 5C),

2001 to 2003 (Table 5D), and 2001 to 2004

(Table 5E), there were consistently significant

differences between Tuesday and Friday returns.

The results suggest that one buy on a Tuesday

(the day with the lowest mean rank) and sell on a

Friday (the day with the highest mean rank).





[71]

Table 5. C.


EFFECT FOR 2001 to 2002



Obs. Sum of

Ranks

Mean of

Ranks

Return 1 95 22,725.000 239.211

Return 2 99 20,040.000 202.424

Return 3 101 24,918.000 246.713

Return 4 100 25,828.000 258.280

Return 5 98 28,260.000 288.367

Significant


Table 5. D.





Obs. Sum of

Ranks

Mean of

Ranks

Return 1 146 52,830.000 361.849

Return 2 150 49,688.000 331.253

Return 3 150 54,495.000 363.300

Return 4 149 56,890.000 381.812

Return 5 145 60,267.000 415.634

Significant


Table 5. E.





Obs. Sum of Ranks Mean of

Ranks

Return 1 193 89,588.000 464.187

Return 2 202 92,434.000 457.594

Return 3 200 100,392.000 501.960

Return 4 199 100,876.000 506.915

Return 5 193 104,288.000 540.352

Significant


For the years 2001 to 2005 (Table 5F),

there were significant differences between

Monday and Friday returns as well as Tuesday

and Friday returns. The result suggests that one

buy on either a Monday or a Tuesday (although

Tuesday is preferred given its lowest mean rank

value of 573.664) and sell on a Friday (since it

has the highest mean rank of 668.535).

Table 5. F.






Ranks

Return 1 238 137,610.000 578.193

Return 2 253 145,137.000 573.664

Return 3 251 156,800.000 624.701

Return 4 250 160,097.000 640.388

Return 5 241 161,117.000 668.535

Significant



For the years 2001 to 2006 (Table 5G),

there were several significant differences among

the different trading days. Specifically, Monday

returns were different from Thursday returns,

Monday returns were different from Friday

returns, Tuesday returns were different from

Thursday returns, and Tuesday returns were

different from Friday returns. The result

indicates that one buy either on a Monday or

Tuesday (although Tuesday is preferred given

that it has the lowest mean rank of 681.261) and

sells either on a Thursday or a Friday (although

Friday is preferred given that it has the highest

mean rank of 798.831).

Table 5. G.






Ranks

Return 1 285 199,747.000 700.867

Return 2 303 206,422.000 681.261

Return 3 302 219,186.000 725.781

Return 4 300 238,924.000 796.413

Return 5 290 231,661.000 798.831

Significant


Return 1 and Return 5 at 0.041,



For the years 2001 to 2007 (Table 5H),

there were again several significant differences

among the five trading days. Specifically,

Monday returns were different from Thursday

returns, Tuesday returns were different from

Thursday returns, and Tuesday returns were





[72]

different from Friday returns. The result

suggests that one buy either on a Monday or a

Tuesday (although Tuesday is preferred given

that has the lowest mean rank of 810.082) and

sell either on a Thursday or a Friday (although

Thursday is preferred given that it has the

highest mean rank of 927.666).

Table 5. H.






Ranks

Return 1 329 269,036.000 817.739

Return 2 353 285,959.000 810.082

Return 3 354 297,798.000 841.237

Return 4 350 324,683.000 927.666

Return 5 338 309,474.000 915.604

Significant




For the years 2001 to 2008 (Table 5I),

2001 to 2009 (Table 5J), and 2001 to 2010

(Table 5K), there were consistently significant

differences between Tuesday and Thursday

returns. The results suggest one buy on a

Tuesday (the day with the lowest mean rank) and

sell on a Thursday (the day with the highest

mean rank).

Summarizing the combinations with

significant differences, Tuesday differing from

Friday returns occurs seven times, Tuesday

differing from Thursday returns occurs six times,

Monday differing from Thursday returns occurs

two times, Monday differing from Friday returns

occurs two times, and Wednesday differing from

Thursday returns occurs one time. The

popularity of the Tuesday/Friday and the

Tuesday/Thursday combinations may be due to

holidays and/or non-trading days that fall on a

Monday and/or a Friday.

Table 5. I.






Ranks

Return 1 374 353,760.000 945.882

Return 2 404 373,821.000 925.300

Return 3 405 400,089.000 987.874

Return 4 399 414,511.000 1,038.875

Return 5 388 399,254.000 1,029.005

Significant


Table 5. J.






Ranks

Return 1 420 446,348.000 1,062.733

Return 2 456 471,602.000 1,034.215

Return 3 455 506,864.000 1,113.987

Return 4 448 524,788.000 1,171.402

Return 5 433 497,976.000 1,150.060

Significant


Table 5. K.






Ranks

Return 1 464 551,144.000 1,187.810

Return 2 507 582,224.000 1,148.371

Return 3 506 626,972.000 1,239.075

Return 4 499 653,156.000 1,308.930

Return 5 480 603,700.000 1,257.708

Significant


Based on the data on Table 6A, March,

June, September, and November had the most

number of lowest mean returns (each at two out

of ten years). For March, the years are 2004 and

2005. For June, the years are 2002 and 2006.

For September, the years are 2001 and 2009.

For November, the years are 2003 and 2010. On

the other hand, January, July, and September had

the most number of highest mean returns (each at





[73]

three out of ten years). For January, the years

are 2002, 2005, and 2007. For July, the years are

2006, 2008, and 2009. For September, the years

are 2004, 2006, and 2010. In terms of trading

days, December had the least number in seven

out of ten years (i.e. 2001 to 2004, 2006 to 2008)

while March and July had the most number (each

at five out of ten years). For March, the years

are 2004, 2006, 2007, 2009, and 2010. For July,

the years are 2002, 2003, 2007, 2008, and 2009.

As per the results shown in Table 6B,

March, August, and October had the most

number of lowest mean returns (each at five out

of nine times). For March, the following periods

were covered: 2001 to 2004, 2001 to 2005 until

2001 to 2008. For August, the following periods

were covered: 2001 to 2003, 2001 to 2006 until

2001 to 2009. For October, the following

periods were covered: 2001 to 2002, 2001 to

2003, 2001 to 2008, 2001 to 2009, and 2001 to

2010. January consistently had the highest mean

returns (i.e. from 2001 to 2002, 2001 to 2003

until 2001 to 2010). With regards to the number

of trading days, December consistently had the

least number of trading days (i.e. from 2001 to

2002, 2001 to 2003 until 2001 to 2010) while

July had the most number in five out of nine

times (i.e. 2001 to 2004, 2001 to 2005, 2001 to

2008, 2001 to 2009, and 2001 to 2010), followed

by August and October (both at four out of nine

times). For August, the following periods were

covered: 2001 to 2002, 2001 to 2005, 2001 to

2006, and 2001 to 2007. For October, the

following periods were covered: 2001 to 2002,

2001 to 2003, 2001 to 2004, and 2001 to 2005.

Table 6. A.

SUMMARY STATISTICS

Month-of-the-Year Effect

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Return

1

Obs. 22 22 22 20 21 22 22 22 20 20

Mean 0.006 0.007 0.002 0.002 0.005 0.001 0.004 -0.004 -

0.001

-

0.002

Return

2

Obs. 20 19 19 19 19 20 20 20 20 20

Mean -

0.002

0.002 -0.002 -0.001 0.002 0.000 -0.003 -0.002 0.001 0.002

Return

3

Obs. 22 19 21 23 20 23 22 19 22 23

Mean -

0.005

0.000 0.001 -0.002 -0.003 0.001 0.002 -0.002 0.003 0.002

Return

4

Obs. 18 21 19 19 21 18 18 21 19 19

Mean -

0.003

-0.002 0.002 0.005 -0.002 0.002 0.001 -0.004 0.003 0.002

Return

5

Obs. 21 22 20 20 21 22 21 21 20 19

Mean 0.001 -0.001 0.000 -0.001 0.002 0.001 0.003 0.001 0.006 0.000

Return

6

Obs. 20 19 20 22 21 21 20 20 21 20

Mean 0.000 -0.007 0.007 0.002 0.000 -0.002 0.003 -0.007 0.001 0.002

Return

7

Obs. 22 22 23 22 20 20 22 23 22 22

Mean -

0.002

-0.001 0.001 0.000 0.002 0.005 -0.002 0.002 0.006 0.001





[74]

Return

8

Obs. 23 22 20 22 22 22 21 19 18 21

Mean -

0.003

-0.001 -0.002 0.000 -0.001 -0.001 -0.001 0.002 0.002 0.002

Return

9

Obs. 20 21 22 22 22 19 20 22 20 21

Mean -

0.006

0.001 0.004 0.005 0.000 0.005 0.003 -0.002 -

0.001

0.007

Return

10

Obs. 23 22 23 21 20 21 21 22 22 20

Mean -

0.005

-0.003 0.003 0.002 0.000 0.003 0.003 -0.011 0.002 0.002

Return

11

Obs. 19 20 19 19 19 21 19 20 19 19

Mean 0.007 0.000 -0.003 0.000 0.004 0.001 -0.002 0.001 0.002 -

0.004

Return

12

Obs. 17 17 19 18 20 18 18 17 19 20

Mean 0.002 -0.002 0.005 0.000 0.000 0.004 0.001 -0.003 0.000 0.003

Table 6. B.

SUMMARY STATISTICS

Month-of-the-Year Effect

2001

to

2002

2001

to

2003

2001

to

2004

2001

to

2005

2001

to

2006

2001

to

2007

2001

to

2008

2001

to

2009

2001

to

2010

Return 1

Obs. 44 66 86 107 129 151 173 193 213

Mean 0.007 0.005 0.004 0.005 0.004 0.004 0.003 0.002 0.002

Return 2

Obs. 39 58 77 96 116 136 156 176 196

Mean 0.000 -0.001 -0.001 0.000 0.000 -0.001 -0.001 -0.001 0.000

Return 3

Obs. 41 62 85 105 128 150 169 191 214

Mean -0.003 -0.001 -0.002 -0.002 -0.001 -0.001 -0.001 0.000 0.000

Return 4

Obs. 39 58 77 98 116 134 155 174 193

Mean -0.002 -0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Return 5

Obs. 43 63 83 104 126 147 168 188 207

Mean 0.000 0.000 0.000 0.000 0.000 0.001 0.001 0.001 0.001

Return 6

Obs. 39 59 81 102 123 143 163 184 204

Mean -0.003 0.000 0.001 0.001 0.000 0.000 0.000 0.000 0.000

Return 7

Obs. 44 67 89 109 129 151 174 196 218

Mean -0.001 -0.001 0.000 0.000 0.001 0.000 0.001 0.001 0.001

Return 8

Obs. 45 65 87 109 131 152 171 189 210

Mean -0.002 -0.002 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 0.000

Return 9





[75]

Obs. 41 63 85 107 126 146 168 188 209

Mean -0.002 0.000 0.001 0.001 0.002 0.002 0.001 0.001 0.002

Return 10

Obs. 45 68 89 109 130 151 173 195 215

Mean -0.004 -0.002 -0.001 -0.001 0.000 0.000 -0.001 -0.001 -

0.001

Return 11

Obs. 39 58 77 96 117 136 156 175 194

Mean 0.003 0.001 0.001 0.002 0.001 0.001 0.001 0.001 0.001

Return 12

Obs. 34 53 71 91 109 127 144 163 183

Mean 0.000 0.002 0.001 0.001 0.002 0.001 0.001 0.001 0.001

The Kruskal-Wallis Test (Table 7A and

Table 7B) shows that the month-of-the-year

effect is non-existent in the Philippine stock

market.

It is quite surprising that the month-of-

the-year effect is non-existent in the local

equities market given that the Philippines is part

of the world’s emerging economies. Perhaps,

the result has something to do with how equity

sales are locally taxed. In the Philippines, there

is a flat tax rate based on the value of the

transaction (number of shares multiplied by the

selling price per share), regardless of the sale

being a gain or a loss (The Philippine Stock

Exchange, Inc. old website,

http://www2.pse.com.ph/, 2001). Other

countries have different tax laws such that one

may strategically sell on December (to report a

loss) and buy back the shares on January

(Mishkin & Eakins, 2006; Fama & French, 1980

(in Hirt & Block, 2012)); thus, creating a month-

of-the-year pattern.

Table 7. A.

TEST FOR MONTH-OF-THE-YEAR EFFECT


2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

K (Ob-

served

Value)

16.811 14.616 11.016 8.486 9.322 9.474 6.490 9.474 11.331 12.907

K

(Critical

Value)

19.675 19.675 19.675 19.675 19.675 19.675 19.675 19.675 19.675 19.675

DF 11 11 11 11 11 11 11 11 11 11

Asymp-

totic

p-value

(two-

tailed)

0.114 0.201 0.442 0.669 0.592 0.578 0.839 0.578 0.416 0.299

Table 7. B.

TEST FOR MONTH-OF-THE-YEAR EFFECT


2001

to

2002

2001

to

2003

2001

to

2004

2001

to

2005

2001

to

2006

2001

to

2007

2001

to

2008

2001

to

2009

2001

to

2010

K

(Observed Value)

16.153 10.361 9.582 11.943 13.687 15.484 14.095 11.173 9.618

K (Critical Value) 19.675 19.675 19.675 19.675 19.675 19.675 19.675 19.675 19.675

DF 11 11 11 11 11 11 11 11 11

Asymptotic

p-value

(two-tailed)

0.136 0.498 0.568 0.368 0.251 0.161 0.228 0.429 0.565





[76]

Based on the results presented in Table

8A, quarter 4 had the most number of lowest

mean returns (four out of ten years). These were

in 2007 until 2010. The rest of the quarters had

lowest mean returns each at three out of ten

years. For quarter 1, these were in the years

2003, 2004, and 2009. For quarter 2, there were

in 2002, 2005, and 2006. For quarter 3, these

were in 2001, 2005, and 2007. On the other

hand, quarters 2 and 3 generated the most

number of highest mean returns (each at four out

of ten years). For quarter 2, these were in years

2003, 2004, 2007, and 2009. For quarter 3, these

were in years 2004, 2006, 2008, and 2010.

Quarter 4 is not far behind, incurring highest

mean returns in three out of ten years. These

were in 2001, 2005, and 2006. In terms of

trading days, quarter 4 had the least number in

eight out of ten years (i.e. 2001, 2002, 2004 until

2009) while quarter 3 had the most number in

seven out of ten years (i.e. 2001 until 2005,

2008, and 2010).

As presented in Table 8B, quarter 2 had

the most number of lowest mean returns (seven

out of nine times). These were in 2001 to 2002,

2001 to 2004 until 2001 to 2007, 2001 to 2009,

and 2001 to 2010. Quarter 3 was next (incurring

lowest mean returns in six out of nine times;

2001 to 2002 until 2001 to 2007). On the other

hand, quarter 1 had the most number of highest

mean returns (seven out of nine times). These

were in 2001 to 2002 until 2001 to 2007, and

2001 to 2010. No lowest and no highest mean

returns were assigned to any quarter for 2001 to

2008 because all periods generated equal values.

In terms of trading days, quarter 4 and quarter 3

were consistent in having the least and most

number of trading days (for all periods),

respectively.

Table 8. A.

SUMMARY STATISTICS

Quarter-of-the-Year Effect

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Return

1

Obs. 64 60 62 62 60 65 64 61 62 63

Mean 0.000 0.003 0.000 0.000 0.001 0.001 0.001 -0.003 0.001 0.001

Return

2

Obs. 59 62 59 61 63 61 59 62 60 58

Mean 0.000 -0.003 0.003 0.002 0.000 0.000 0.002 -0.003 0.004 0.001

Return

3

Obs. 65 65 65 66 64 61 63 64 60 64

Mean -0.003 0.000 0.001 0.002 0.000 0.003 0.000 0.001 0.002 0.003

Return

4

Obs. 59 59 61 58 59 60 58 59 60 59

Mean 0.001 -0.002 0.002 0.001 0.001 0.003 0.000 -0.005 0.001 0.000





[77]

Table 8. B.

SUMMARY STATISTICS

Quarter-of-the-Year Effect

2001

to

2002

2001

to

2003

2001

to

2004

2001

to

2005

2001

to

2006

2001

to

2007

2001

to

2008

2001

to

2009

2001

to

2010

Return 1

Obs. 124 186 248 308 373 437 498 560 623

Mean 0.001 0.001 0.001 0.001 0.001 0.001 0.000 0.000 0.001

Return 2

Obs. 121 180 241 304 365 424 486 546 604

Mean -0.002 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Return 3

Obs. 130 195 261 325 386 449 513 573 637

Mean -0.002 -0.001 0.000 0.000 0.000 0.000 0.000 0.001 0.001

Return 4

Obs. 118 179 237 296 356 414 473 533 592

Mean 0.000 0.000 0.000 0.001 0.001 0.001 0.000 0.000 0.000

The Kruskal-Wallis Test shows that

there is no quarter-of-the-year effect (Table 9A

and Table 9B) except for 2002.

The non-existence of both the month-

of-the-year and quarter-of-the-year effects are

quite interesting given the common belief of

window dressing activities towards the end of

the calendar year.

Table 9. A.

TEST FOR QUARTER-OF-THE-YEAR EFFECT


2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

K (Observed

Value)

3.582 9.342 0.744 2.180 0.487 2.248 2.018 2.482 2.234 2.827

K (Critical

Value)

7.815 7.815 7.815 7.815 7.815 7.815 7.815 7.815 7.815 7.815

DF 3 3 3 3 3 3 3 3 3 3

Asymptotic

p-value

(two-tailed)

0.310 0.025 0.863 0.536 0.922 0.523 0.569 0.479 0.525 0.419

Table 9. B.

TEST FOR QUARTER-OF-THE-YEAR EFFECT


2001 to

2002

2001

to

2003

2001

to

2004

2001

to

2005

2001

to

2006

2001

to

2007

2001

to

2008

2001

to

2009

2001

to

2010

K

(Observed Value)

3.069 1.819 0.207 0.479 0.945 0.853 0.961 0.201 0.447

K (Critical Value) 7.815 7.815 7.815 7.815 7.815 7.815 7.815 7.815 7.815

DF 3 3 3 3 3 3 3 3 3

Asymptotic

p-value

(two-tailed)

0.381 0.611 0.976 0.924 0.815 0.837 0.811 0.977 0.930





[78]

For the year 2002 (Table 10A), there

was a significant difference between the return of

quarter 1 and the return of quarter 2. The results

indicate that one buy on quarter 2 (lowest mean

rank of 106.984) and sell on quarter 1 (highest

mean rank of 144.500).

Table 10.A.

SIGNIFICANCE OF THE QUARTER-OF-THE-

YEAR EFFECT FOR 2002



Obs. Sum of

Ranks

Mean of

Ranks

Return 1 60 8,670.000 144.500

Return 2 62 6,633.000 106.984

Return 3 65 8,232.000 126.646

Return 4 59 6,846.000 116.034

Significant


6. CONCLUSION

Although the annual analysis of the

existence of the day-of-the-week effect in the

PSEi indicate that only two of ten years (i.e.

2001 and 2006) are statistically significant

(Tables 4A, 5A, and 5B), the summary statistics

(Table 3A) indicate a frequency pattern of lower

mean returns on Mondays and Tuesdays higher

mean returns during Thursdays. Based on the

cumulative analysis of the existence of the day-

of-the-week effect, the summary statistics (Table

3B) are consistent with the results of the

Kruskal-Wallis Test (Tables 4B, 5C to 5K).

Since the phenomenon is present in all periods

when cumulative analysis was utilized, this

suggests a holding period of at least two years.

The top two combinations with significant

differences are (1) Tuesday versus Friday returns

and (2) Tuesday versus Thursday returns.

Generally, the results imply that one buy on a

Tuesday and sell either on a Thursday or a

Friday. The results are fundamentally in line

with the research done by Almonte (2004).

Consistent with the findings of Al-Jafari

(2011) and Selvakumar (2011), the month-of-

the-year effect is apparently non-existent in the

market (Tables 7A and 7B). For the annual

analysis, the results of the Kruskal-Wallis Test

are supported by the summary statistics in that

several months accounted for the most number of

lowest and highest mean returns (Table 6A). As

for the cumulative analysis, the summary

statistics (Table 6B) indicate that there were

several months that accounted for the most

number of lowest mean returns and that January

consistently had the highest mean returns

(although statistically insignificant). A possible

explanation for January’s highest mean returns

could be traders and/or investors trying to make-

up for their December trading (since December

had the lowest number of trading days in the

annual and cumulative analyses).

As per the annual analysis, with the

exception of 2002, there is no quarter-of-the-year

effect in the market (Table 9A). The results of

the summary statistics support the statistical test

in that no quarter was dominant in generating the

lowest or highest mean returns (Table 8A). The

significant result that occurred in 2002 may just

be due to chance. As for the cumulative

analysis, the summary statistics (Table 8B)

indicate that the lowest mean returns mostly

occur during quarter 2 while the highest mean

returns mostly occur on quarter 1 (although

results of the Kruskal-Wallis Test reveal that the

returns of one quarter are statistically the same as

the returns of any other quarter). The results of

the quarter-of-the-year effect disagree with those

of Davidsson (2006) and the CXO Advisory

Group, LLC

(http://www.cxoadvisory.com/4080/calendar-

effects/end-of-quarter-effect/, June 14, 2012).

Therefore, only the first research

hypothesis is supported by the results of this

study.

7. REFERENCES

Agathee, U.S. (2008). Calendar effects and the

months of the year: Evidence from the

Mauritian stock exchange. International

Research Journal of Finance and

Economics, (14), 254-261.

Al-Jafari, M.K. (2011). The monthly effect of stock

market returns and the global financial

crisis: Evidence and implications from

Bahrain Bourse. International Research

Journal of Finance and Economics, (78),

83-95. Retrieved January 7, 2012, from

http://www.internationalresearchjournaloffin

anceandeconomics.com/ISSUES/IRJFE_78_

07.pdf.

Almonte, C.K.S. (2004). The day-of-the-week effect

in the Philippine stock market January 3,

2000 to July 23, 2004. Retrieved January 7,





[79]

2012, from

http://www.dlsu.edu.ph/research/centers/cbe

rd/pdf/papers/Working%20Paper%20Series

%202004-10.pdf.

Aly, H., Mehdian, S., & Perry, M.J. (2004). An

analysis of the day-of-the-week effects in

the Egyptian stock market. International

Journal of Business, 9(3), 301-308.

Retrieved June 20, 2004, from

http://ssrn.com/abstract=551101.

ASEAN Exchanges website. (2011). Retrieved July

19, 2012, from

http://www.aseanexchanges.org/.

Chia, R.C., Liew, V.K., & Wafa, S.A.W.S.K. (2008).

Day-of-the-week effects in selected East

Asian stock markets. Economics Bulletin,

7(5), 1-8. Retrieved January 7, 2012, from

http://www.accessecon.com/pubs/EB/2008/

Volume7/EB-08G00001A.pdf.

CXO Advisory Group, LLC (June 14, 2012). End-of-

quarter effect. In Calendar effects.

Retrieved July 25, 2012, from

http://www.cxoadvisory.com/4080/calendar-

effects/end-of-quarter-effect/.

Davidsson, M. (2006). Stock market anomalies: A

literature review and estimation of calendar

affects on the S&P 500 index. Retrieved

July 25, 2012, from

http://scholar.google.com.ph/scholar?q=%22

quarter+of+the+year+effect%22&btnG=&hl

=en&as_sdt=0%2C5.

Fama, E.F. (1970). Efficient capital markets: A

review of theory and empirical work.

Journal of Finance, 25(2), 383-417.


http://www.jstor.org.

Hussain, F., Hamid, K., Akash, R.S.I., & Khan, M.I.

(2011). Day of the week effect and stock

returns: (Evidence from Karachi Stock

Exchange-Pakistan). Far East Journal of

Psychology and Business, 3(1), 25-31.

Retrieved January 7, 2012, from

http://www.fareastjournals.com/files/FEJPB

V3N1P3.pdf.

Gitman, L.J. (2009). Principles of managerial finance

(Twelfth Edition). USA: Pearson Addison-

Wesley.

Hirt, G.A. & Block, S.B. (2012). Fundamentals of

investment management (Tenth Edition).

USA: McGraw-Hill.

Keown, A.J., Martin, J.D., Petty, J.W. & Scott, Jr.,

D.F. (2005). Financial management:

Principles and applications (Tenth Edition).

USA: Pearson Prentice Hall.

Lago, J.J.F. (2012). Personal communication, e-mail

dated January 30, 2012.

Marrett, G. & Worthington, A. (2011). The month-of-

the-year effect in the Australian stock

market: A short technical note on the

market, industry and firm size impacts.

Australasian Accounting Business and

Finance Journal, 5(1), 117-123. Retrieved

January 7, 2012, from

http://ro.uow.edu.au/cgi/viewcontent.cgi?arti

cle=1130&context=aabfj&sei-

redir=1&referer=http%3A%2F%2Fwww.go

ogle.com.ph%2Furl%3Fsa%3Dt%26rct%3D

j%26q%3D%2522month-of-the-

year%2520effect%2522%26source%3Dweb

%26cd%3D26%26ved%3D0CD8QFjAFOB

Q%26url%3Dhttp%253A%252F%252Fro.u

ow.edu.au%252Fcgi%252Fviewcontent.cgi

%253Farticle%253D1130%2526context%2

53Daabfj%26ei%3D-

wAIT6TNLOeaiQex9L2lCQ%26usg%3DA

FQjCNGXiX28qLlslJXMRYR23SQfDelW

Bw#search=%22month-of-the-

year%20effect%22.

Mishkin, F.S. & Eakins, S.G. (2006). Financial

markets and institutions (Fifth Edition).

USA: Pearson Addison-Wesley.

Poshakwale, S. (1996). Evidence on weak form

efficiency and day of the week effect in the

Indian stock market. Finance India, X(3),


http://www.classle.org/sites/default/files/text

/41/MARKET_EFFICIENCY.pdf.

PSE Academy website. (2011). Retrieved January 23,

2012, from

http://www.pseacademy.com.ph/LM/glossar

y/Glossary.html#P.

Philippine Stock Exchange, Inc., The. (2011a).

Memorandum No. 2011-0171.

Philippine Stock Exchange, Inc., The. (2011b).

Memorandum TPA-No. 2011-0030.

Philippine Stock Exchange, Inc., The. (2011c).

Memorandum TPA-No. 2011-0108.

Philippine Stock Exchange, Inc., The old website.

(2001). Investing procedures. Retrieved on

January 29, 2012, from

http://www2.pse.com.ph/.

Phililppine Stock Exchange, Inc., The website. (2007).


http://www.pse.com.ph/.

Selvakumar, D.S. (2011). Existence of certain

anomalies in Indian stock market. 2011

International Conference on Economics and

Finance Research, IPEDR Vol. 4 (2011).

Retrieved on January 7, 2012, from

http://www.ipedr.com/vol4/99-F10141.pdf.

Weekend Effect. (n.d.). Retrieved January 25, 2012,

from http://calendar-

effects.behaviouralfinance.net/weekend-

effect/.

Wyème, B.M.D.F. & Olfa, C. (2011). Month of the

year effect: Existence and behavioral

explanation. International Research

Journal of Finance and Economics, (67),






[80]

http://www.eurojournals.com/IRJFE_67_07.

pdf.

Zafar, N., Urooj, S.F., & Farooq, S.U. (2010).

Karachi Stock Exchange: Testing month of

the year effect. European Journal of

Economics, Finance and Administrative

Sciences, (24), 20-28. Retrieved January 7,

2012, from

http://www.eurojournals.com/ejefas_24_03.

pdf.

Documents

CALENDAR EFFECTS IN THE PHILIPPINE STOCK MARKET - JITBM