ACADEMY OF ECONOMIC STUDIES

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ACADEMY OF ECONOMIC STUDIES DOCTORAL SCHOOL OF
FINANCE AND BANKING
DISSERTATION PAPER The day of the week effect
on stock market return and volatility
International evidence
Student Sorin Stoica
Supervisor Professor Moisa Altar
BUCHAREST, JULY 2008
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Contents

• Introduction
• 2. Literature review
• Data and Model description
• Empirical results
• Conclusions
• Bibliography

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1. Introduction
The day of the week effect refers to the
existence of a pattern of stock returns during
the week, a seasonal anomaly, which contradicts
the Efficient Market Hypothesis
A market is efficient if prices fully and
instantaneously reflect all available information
and no profit opportunities are left unexploited.
In an efficient situation, new information is
unpredictable, so stock market returns cannot be
predicted and there is therefore no trading
pattern, which an investor can follow in order to
make unexpected profits.
(The efficient-market hypothesis was developed
by Professor Eugene Fama at the University of
Chicago Graduate School of Business as an
academic concept of study through his published
Ph.D. thesis in the early 1960s at the same
school)
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2. Literature review

• Cross (1973) and French (1980) were the first to
  observe a specific
• seasonality in stock returns during the week,
  that was named
• Day of the Week Effect. According to this
  phenomenon, the average stock
• market return on the last trading day of the week
  (Friday) is positive and is
• the highest across all days of the week and the
  return on the first trading
• day of the week (Monday) is negative and is the
  lowest across the same period.
• French (1987) examine the relationship between
  stock prices and volatility and
• report that unexpected stock market returns are
  negatively related to the
• unexpected changes in volatility.
• Campbell and Hentschel (1992) report similar
  results and argue that an increase
• in stock market volatility raises the required
  rate of return on common stocks
• and hence lowers stock prices.
• Glosten (1993) and Nelson (1991), on the other
  hand, report that positive
• unanticipated returns reduce conditional
  volatility whereas negative unanticipated
• returns increase conditional volatility.

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• Kiymaz and Berument (2003) investigate the day
  of the week effect on
• the volatility and return of major stock markets
  (German, Japan, US, Canada
• and United Kingdom) for the time period from 1998
  to 2002. Their findings are
• consistent with the day of the week effect both
  for returns and volatility.
• Patev (2003) examine the presence of the
  day-of-the-week effect
• anomaly in the Central European stock markets
  during the period 1997 to 2002.
• Their results indicated that the Czech and
  Romanian markets have significant
• negative Monday returns while the Slovenian
  market has significant positive
• Wednesday returns and has non-significant
  negative returns on Fridays.
• The Polish and Slovak markets have no day-of-the
  week effect anomaly.
• Cabello and Ortiz (2004) investigate the day of
  the week and month of the year
• effect for Latin America stock markets. The paper
  supports the existence of
• calendar anomalies. They find the lowest and
  negative returns on Mondays
• and high returns on Fridays.
• Hui (2005) examines the day of the week effect at
  Asian-Pacific markets
• during the period of Asian financial crisis and
  also tests the presence of

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3. Data and Model description 3.1 Data
The data set used in this study consists of six
European Index values obtained from
Bloomberg. For econometric reasons, for working
days that the stock markets did not open and of
course the indices did not change, the value of
the previous day has been used.
Period ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
Downtrend 1/10/2001- 28/3/2003 1/10/2001- 28/3/2003 1/10/2001- 28/3/2003 1/10/2001- 28/3/2003 1/10/2001- 28/3/2003 1/10/2001- 28/3/2003
(390) (390) (390) (390) (390) (390)
Uptrend 31/3/2003- 20/6/2008 31/3/2003- 20/6/2008 31/3/2003- 20/6/2008 31/3/2003- 20/6/2008 31/3/2003- 20/6/2008 31/3/2003- 20/6/2008
(1365) (1365) (1365) (1365) (1365) (1365)
Notes Numbers in parentheses depict observations
used in each period
The returns used in each of the time series are
computed as follows
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3.3 Model description
The first GARCH-M (1, 1) model investigate the
day of the week effect in stock return and it
consists of the following two equations
are the dummy variables for Monday, Tuesday,
Thursday, and Friday at time t
are the dummy variables for Monday, Tuesday,
Thursday, and Friday at time t
the GARCH term
the GARCH term
the ARCH term
the ARCH term
The mean equation allows for an autoregression of
order 1 in the mean of returns since most of the
returns data exhibit a small but significant
first order autocorrelation
In both models the Wednesday dummy variable is
excluded to avoid the dummy variable trap
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The second GARCH-M (1, 1) model investigate the
day of the week effect in both stock return and
volatility and it consists of the following two
equations
are the dummy variables for Monday, Tuesday,
Thursday, and Friday at time t
are the dummy variables for Monday, Tuesday,
Thursday, and Friday at time t
the mean
the GARCH term
the GARCH term
the ARCH term
the ARCH term
The mean equation allows for an autoregression of
order 1 in the mean of returns since most of the
returns data exhibit a small but significant
first order autocorrelation
The quasi-maximum likelihood estimation (QMLE)
method introduced by Bollerslev and Wooldridge
(1992) is used to estimate parameters
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4. Empirical results
4.1 Testing the series
Whole period (Returns) ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
Mean 0.001142 6.77E-05 0.000250 -4.66E-05 0.000311 3.15E-05
Median 0.000115 0.000102 0.000576 0.000000 0.000481 0.000309
Maximum 0.145016 0.070023 0.075527 0.068219 0.067222 0.064038
Minimum -0.119056 -0.070774 -0.074335 -0.059332 -0.078393 -0.053131
Std. Dev. 0.016653 0.013626 0.015120 0.011948 0.012338 0.011510
Skewness 0.144307 -0.008740 -0.036558 -0.102100 -0.038203 -0.082341
Kurtosis 10.33795 6.783804 6.536587 6.345886 6.627896 5.730291
Jarque-Bera 3941.297 1046.369 914.4765 821.2117 962.3224 546.7811
Observations 1754 1754 1754 1754 1754 1754
ADF (returns) -39.11451 0 -43.93095 0 -44.38366 0 -27.51158 0 -44.40952 0 -44.00585 0
Notes p values are reported in brackets
denotes significance at the 1 level of
significance

• The return series are nonsymmetric and
  leptokurtic compared to the normal distribution
• According to Augmented Dickey - Fuller test all
  return series are stationary

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Down trend (Returns) ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
Mean 0.001547 -0.000982 -0.001337 -0.000911 -0.000454 -0.000608
Median 0.000000 -0.001053 -0.001204 -0.001179 0.000000 -0.000648
Maximum 0.145016 0.070023 0.075527 0.068219 0.056942 0.064038
Minimum -0.044481 -0.060448 -0.063360 -0.059332 -0.052006 -0.050102
Std. Dev. 0.016518 0.021481 0.024335 0.017495 0.018810 0.017979
Skewness 1.901538 0.250631 0.196448 0.144311 0.300625 0.217018
Kurtosis 17.59871 3.769944 3.393660 4.263171 3.185388 3.180879
Jarque-Bera 3688.783 13.68108 5.013823 27.21225 6.416413 3.583733
Observations 389 389 389 389 389 389
ADF Test -19.18971 0 -19.84382 0 -20.90961 0 -21.38023 0 -20.41756 0 -20.14965 0
Notes p values are reported in brackets
denotes significance at the 1 level of
significance

• The return series are nonsymmetric and
  leptokurtic compared to the normal distribution
• According to Augmented Dickey - Fuller test all
  return series are stationary

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Up trend (Returns) ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
Mean 0.001027 0.000367 0.000703 0.000200 0.000529 0.000214
Median 0.000182 0.000449 0.000924 0.000253 0.000765 0.000786
Maximum 0.089371 0.058335 0.057610 0.044623 0.067222 0.038619
Minimum -0.119056 -0.070774 -0.074335 -0.056277 -0.078393 -0.053131
Std. Dev. 0.016695 0.010342 0.011155 0.009805 0.009735 0.008841
Skewness -0.338816 -0.376683 -0.239517 -0.306060 -0.532929 -0.558735
Kurtosis 8.304512 6.575000 6.731557 5.784750 9.571692 5.869344
Jarque-Bera 1626.456 759.1779 805.0084 462.3666 2520.881 539.2817
Observations 1365 1365 1365 1365 1365 1365
ADF (returns) -34.09442 0 -40.82585 0 -39.29837 0 -42.64936 0 -40.17416 0 -40.08223 0
Notes p values are reported in brackets
denotes significance at the 1 level of
significance

• The return series are nonsymmetric and
  leptokurtic compared to the normal distribution
• According to Augmented Dickey - Fuller test all
  return series are stationary

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The descriptive statistics for each day of the
week
Whole period Whole period Whole period Whole period Whole period Whole period Whole period Whole period
Mean MO TU WE TH FR F-stat Prob
BET 10 0.005918 0.005890 0.005843 0.005785 0.005734 0.001340 1.0000
CAC 40 0.000432 0.000421 0.000394 0.000257 0.000227 0.004023 1.0000
DAX 30 0.001320 0.001305 0.001190 0.001116 0.001093 0.003717 1.0000
FTSE 100 -0.000137 -0.000128 -0.000228 -0.000308 -0.000385 0.007723 0.9999
MADRID 0.001653 0.001620 0.001588 0.001492 0.001568 0.001945 1.0000
MIBTEL 0.000248 0.000228 0.000150 5.13E-05 7.60E-05 0.004465 1.0000
The F-Stat refers to the F-Statistic of the
Equality of means test. If p-value lt 0.050, then
the hypothesis of equal means is rejected
Whole period Whole period Whole period Whole period Whole period Whole period Whole period Whole period
Std. Dev. MO TU WE TH FR Levene Prob
BET 10 0.041494 0.039676 0.038668 0.035554 0.037045 1.063576 0.3730
CAC 40 0.030611 0.029600 0.030619 0.025393 0.025475 1.640912 0.1614
DAX 30 0.034507 0.033402 0.033373 0.029319 0.030010 1.478357 0.2062
FTSE 100 0.026093 0.023406 0.024967 0.021326 0.021358 1.860181 0.1149
MADRID 0.028230 0.025554 0.027220 0.023941 0.023496 0.974811 0.4201
MIBTEL 0.026436 0.025032 0.025754 0.022853 0.022933 0.725194 0.5747
The L-Value refers to the Levene Value of the
Equality of variance test. If p-value lt 0.050,
then the hypothesis of equal variances is rejected
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Down Trend Down Trend Down Trend Down Trend Down Trend Down Trend Down Trend Down Trend
Mean MO TU WE TH FR F-stat Prob
BET 10 0.007724 0.007595 0.007658 0.007856 0.007857 0.000832 1.0000
CAC 40 -0.004991 -0.004796 -0.004768 -0.005616 -0.005471 0.005675 0.9999
DAX 30 -0.006612 -0.006367 -0.007044 -0.007342 -0.007490 0.000461 1.0000
FTSE 100 -0.004284 -0.004305 -0.004432 -0.005108 -0.005291 0.014669 0.9996
MADRID -0.002345 -0.002299 -0.002143 -0.002791 -0.002249 0.003187 1.0000
MIBTEL -0.003127 -0.003062 -0.003210 -0.003838 -0.003443 0.005131 0.9999
The F-Stat refers to the F-Statistic of the
Equality of means test. If p-value lt 0.050, then
the hypothesis of equal means is rejected
Down trend Down trend Down trend Down trend Down trend Down trend Down trend Down trend
Std. Dev. MO TU WE TH FR Levene Prob
BET 10 0.034672 0.036623 0.038090 0.033666 0.035559 0.105995 0.9804
CAC 40 0.047271 0.049090 0.051749 0.039945 0.038637 0.730156 0.5718
DAX 30 0.053515 0.053612 0.053847 0.045270 0.045831 0.934238 0.4431
FTSE 100 0.036625 0.036621 0.039259 0.030501 0.029112 0.615906 0.6514
MADRID 0.041747 0.038969 0.042352 0.036434 0.033663 1.010731 0.4017
MIBTEL 0.041197 0.040986 0.041212 0.034844 0.034272 0.668828 0.6140
The L-Value refers to the Levene Value of the
Equality of variance test. If p-value lt 0.050,
then the hypothesis of equal variances is rejected
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Up trend Up trend Up trend Up trend Up trend Up trend Up trend Up trend
Mean MO TU WE TH FR F-stat Prob
BET 10 0.005409 0.005409 0.005332 0.005201 0.005135 0.002722 1.0000
CAC 40 0.001961 0.001892 0.001850 0.001914 0.001834 0.001591 1.0000
DAX 30 0.003557 0.003469 0.003512 0.003501 0.003514 0.006821 0.9999
FTSE 100 0.001032 0.001050 0.000958 0.001046 0.000999 0.001116 1.0000
MADRID 0.002780 0.002725 0.002641 0.002700 0.002645 0.002172 1.0000
MIBTEL 0.001201 0.001156 0.001098 0.001148 0.001068 0.002043 1.0000
The F-Stat refers to the F-Statistic of the
Equality of means test. If p-value lt 0.050, then
the hypothesis of equal means is rejected
Up trend Up trend Up trend Up trend Up trend Up trend Up trend Up trend
Mean MO TU WE TH FR Levene Prob
BET 10 0.043267 0.040546 0.038883 0.036107 0.037495 1.114507 0.3480
CAC 40 0.023817 0.021000 0.021095 0.019209 0.020094 1.912600 0.1059
DAX 30 0.026548 0.024640 0.024378 0.022458 0.023280 0.930642 0.4461
FTSE 100 0.022193 0.017942 0.019046 0.017755 0.018433 2.442196 0.0450
MADRID 0.023016 0.020199 0.021081 0.018918 0.019658 0.532459 0.7119
MIBTEL 0.020454 0.018185 0.019297 0.018037 0.018497 0.532061 0.7122
The L-Value refers to the Levene Value of the
Equality of variance test. If p-value lt 0.050,
then the hypothesis of equal variances is rejected
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4.2 The Results of the regressions
The day of the week effects in returns for whole
period
Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period
Return ecuation ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
Constant -0,0003 0,000706 0,000878 0,000173 0,001168 0,001476
(0.001708) (0.000869) (0.000926) (0.000765) (0.000821) (0.000725)
Monday -0,00031 -0,000594 -0,000242 0,000356 -0,00114 -0,001503
(0.001108) (0.000724) (0.000823) (0.000633) (0.000729) (0.000676)
Tuesday 0,001601 -0,00078 -0,000862 0,000148 -0,00106 -0,001336
(0.001138) (0.000708) (0.000767) (0.000668) (0.000694) (0.000613)
Thursday 3,06E-05 1,58E-04 -3,39E-05 7,46E-04 -1,83E-04 -8,49E-04
(0.001089) (0.00073) (0.000787) (0.000669) (0.000677) (0.000649)
Friday 6,61E-05 1,05E-04 -2,41E-04 9,46E-04 -2,99E-04 -6,52E-04
(0.001057) (0.000709) (0.000767) (0.000639) (0.000724) (0.000625)
Return(t-1) 5,53E-02 -6,60E-02 -4,93E-02 -8,99E-02 -3,58E-02 -5,85E-02
(0.034143) (0.023936) (0.024818) (0.024974) (0.025588) (0.02407)
Risk 0,092859 0,015239 0,028418 -0,020148 0,023416 -0,016238
(0.113662) (0.076608) (0.071814) (0.073613) (0.074867) (0.074664)
Notes Standard errors are reported in
parentheses denotes significance at the 1
level of significance
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Volatility ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
Mean 3,01E-05 1,93E-06 2,07E-06 1,46E-06 2,14E-06 1,15E-06
(0.0000111) (0.000000745) (0.000000964) (0.000000524) (0.000000831) (0.000000508)
ARCH 0,177732 0,090911 0,089462 0,089707 0,097743 0,073798
(0.057288) (0.019176) (0.021683) (0.014662) (0.024015) (0.016404)
GARCH 0,721278 0,897015 0,899845 0,899368 0,887776 0,916383
(0.068387) (0.018995) (0.022146) (0.014838) (0.023285) (0.017282)
Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period
LjungBox Q statistics ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
5 2,5467 8,3985 8,2389 6,1078 3,7531 5,7284
0.769 0.136 0.144 0.296 0.585 0.334
10 7,2557 12,559 11,504 6,9764 6,6237 9,4085
0.509 0.128 0.175 0.539 0.578 0.309
15 24,409 17,954 17,336 12,63 19,498 12,492
0.058 0.265 0.299 0.631 0.192 0.642
20 31,865 24,681 22,088 20,86 23,096 17,725
0.045 0.214 0.336 0.405 0.284 0.606
25 37,99 25,995 24,727 28,881 25,632 18,442
0.046 0.408 0.478 0.269 0.427 0.823
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Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period
ARCH-LM test ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
5 0,382733 1,727216 1,129006 0,69928 4,075016 0,933572
0.860877 0.125118 0.342759 0.624008 0.00111 0.458033
10 0,381393 0,927862 0,649215 0,850661 2,106105 0,714608
0.955162 0.5062 0.772107 0.579599 0.021217 0.711419
15 0,319659 1,106179 0,835782 1,612083 1,900103 1,063579
0.993643 0.344869 0.637904 0.063357 0.019338 0.386045
20 0,280678 0,937869 0,794883 1,348491 1,953253 0,978515
0.999309 0.537914 0.722357 0.138103 0.007002 0.48565
25 0,764475 1,090896 0,796243 1,160234 1,746724 1,119203
0.790675 0.344074 0.750802 0.265791 0.012622 0.310641
The conditional variances are always positive and
are not explosive in our samples. According to
the LjungBox Q statistics we can not reject the
null hypothesis that the residuals are not
autocorrelated. The ARCH-LM test does not
indicate the presence of a significant ARCH
effect in any of the sampled markets except
MADRID.
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The day of the week effects in returns and
volatilities for whole period
Whole period Whole period Whole period Whole period Whole period Whole period Whole period
Return ecuation ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
Constant -0,00078 0,000767 0,000794 0,000224 0,001116 0,001341
(0.001663) (0.000862) (0.000962) (0.000761) (0.00084) (0.000714)
Monday -0,00034 -0,000613 -0,00025 0,00036 -0,00119 -0,00151
(0.001088) (0.000721) (0.000843) (0.000632) (0.000745) (0.000683)
Tuesday 0,00139 -0,000804 -0,0009 0,000141 -0,00109 -0,00131
(0.001079) (0.000709) (0.000786) (0.000665) (0.000712) (0.000617)
Thursday 2,38E-05 2,15E-04 -3,07E-05 7,93E-04 -2,94E-04 -8,24E-04
(0.00109) (0.00073) (0.000795) (0.000667) (0.000681) (0.000647)
Friday 2,48E-04 1,85E-04 -1,75E-04 9,84E-04 -2,73E-04 -6,65E-04
(0.001025) (0.000708) (0.000776) (0.000638) (0.000721) (0.000623)
Return(t-1) 6,06E-02 -6,63E-02 -5,00E-02 -8,89E-02 -3,62E-02 -6,06E-02
(0.034595) (0.023934) (0.024656) (0.024993) (0.025303) (0.023909)
Risk 0,122603 0,009604 0,034378 -0,025356 0,031732 -0,00411
(0.116125) (0.075484) (0.073363) (0.072933) (0.074814) (0.076502)
Statistically significant at the 5 level.
Statistically significant at the 1 level.
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Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period
Volatility ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
Mean -9,87E-06 4,92E-06 1,32E-05 -2,95E-07 1,13E-05 1,42E-06
(0.0000562) (0.0000109) (0.0000141) (0.00000802) (0.000011) (0.0000076)
ARCH 0,210745 0,093075 0,087229 0,089355 0,094191 0,072936
(0.059474) (0.019896) (0.021338) (0.014525) (0.023343) (0.01512)
GARCH 0,662341 0,896094 0,901471 0,900508 0,892052 0,915054
(0.076557) (0.01932) (0.021912) (0.014675) (0.022591) (0.016479)
Monday 7,72E-05 -1,42E-05 -1,48E-05 -4,13E-06 -1,35E-05 1,25E-05
(0.000058) (0.0000147) (0.0000198) (0.0000111) (0.0000157) (0.0000125)
Tuesday 1,00E-04 -9,59E-08 -1,69E-05 8,89E-06 -1,42E-05 -1,51E-05
(0.0000969) (0.0000215) (0.0000284) (0.0000153) (0.0000217) (0.0000153)
Thursday 3,89E-05 9,30E-07 -1,73E-05 3,18E-06 -2,06E-05 5,68E-06
(0.0000778) (0.0000159) (0.0000201) (0.0000127) (0.0000159) (0.0000123)
Friday 2,48E-05 -2,07E-06 -6,38E-06 5,01E-07 2,03E-06 -3,61E-06
(0.0000577) (0.0000153) (0.0000182) (0.0000114) (0.0000158) (0.0000124)
The conditional variances are always positive and
are not explosive in our samples.
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The LjungBox Q statistics for the normalized
residuals at 5-, 10-, 15-, 20-, and 25-day lags
Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period
Q stat ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
5 3,0236 8,5064 8,7964 6,0607 4,0458 5,5976
0.696 0.13 0.117 0.3 0.543 0.347
10 8,2793 12,759 12,084 7,024 6,8198 9,1098
0.407 0.12 0.148 0.534 0.556 0.333
15 25,043 18,238 18,178 12,551 20,135 12,019
0.049 0.25 0.253 0.637 0.167 0.678
20 31,952 25,255 22,881 20,821 23,846 17,078
0.044 0.192 0.295 0.408 0.249 0.648
25 38,21 26,578 25,594 28,619 26,714 17,848
0.044 0.377 0.429 0.28 0.37 0.849
None of these coefficients are statistically
significant. Therefore, we cannot reject the null
hypothesis that the residuals are not
autocorrelated.
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Engles ARCH-LM for whole period
Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period Whole Period
ARCH-LM test ROMANIA BET 10 FRANCE CAC 40 GERMANY DAX 30 UK FTSE 100 SPAIN MADRID ITALY MIBTEL
5 0,420936 1,680777 1,201455 0,692022 4,505728 0,980701
0.834402 0.135968 0.306014 0.629501 0.000439 0.428102
10 0,601501 0,88257 0,691385 0,911325 2,343972 0,759711
0.813712 0.548923 0.73335 0.521666 0.009571 0.668039
15 0,505872 1,074607 0,877044 1,590531 2,057816 1,222953
0.938819 0.375135 0.590322 0.068863 0.009606 0.246415
20 0,474225 0,920121 0,822288 1,341716 2,094818 1,113194
0.976242 0.561059 0.688144 0.141982 0.003109 0.327823
25 0,799504 1,062295 0,804766 1,148274 1,863541 1,209985
0.746558 0.379769 0.739655 0.278409 0.005968 0.217401
Engles ARCH-LM test does not indicate the
presence of a significant ARCH effect in any of
the sampled markets except MADRID. This finding
indicates that the standardized residual terms
have constant variances and do not exhibit
autocorrelation except MADRID.
23
The results for downtrend period
The day of the week effects in returns for
downtrend period
There is no coefficient of dummys variables
statistically significant. Thus, we dont find
the evidence for the existence of the classical
day of the week effect.
The estimated coefficients for BET 10, MADRID and
MIBTEL are lowest on Mondays but they are
statistically insignificant. The coefficient of
the conditional standard deviation of the return
equation (risk) is positive for BET10 (0,347303),
CAC 40 (0,115031), DAX 30 (0,058048), FTSE 100
(0,178102), MADRID (0,224529) and MIBTEL
(0,218751). However, the estimated coefficients
are not statistically significant. The
conditional variances are always positive and are
not explosive in our samples. According to the
LjungBox Q statistics we cannot reject the null
hypothesis that the residuals are not
autocorrelated. The ARCH-LM test does not
indicate the presence of a significant ARCH
effect in any of the sampled markets. This
finding indicates that the standardized residual
terms have constant variances and do not exhibit
autocorrelation.
24
The day of the week effects in returns and
volatilities for downtrend period
The estimated coefficients for dummys variables
in volatility equation are not statistically
significant except the ones from Monday and
Tuesday for BET10, the one from Tuesday for DAX
40 and the one from Friday for FTSE 100 who are
statistically significant. Not only we dont
find strong evidence for the existence of the
classical day of the week effect, but there is no
any obvious pattern in coefficients
significances. The coefficients of the
conditional standard deviation of the return
equation (risk) are positive for all markets.
However, the estimated coefficients are not
statistically significant except BET10. The
conditional variances are always positive and are
not explosive in our samples According to the
LjungBox Q statistics we cannot reject the null
hypothesis that the residuals are not
autocorrelated. The ARCH-LM test does not
indicate the presence of a significant ARCH
effect in any of the sampled markets
25
The results for uptrend period
The day of the week effects in returns for
uptrend period
The estimated coefficient of the Mondays dummy
variable for MIBTEL (-0,001503) is negative and
statistically significant at the 1 level,
suggesting that Mondays returns are smaller than
those of Wednesdays. Also the estimated
coefficient of the Tuesdays dummy variables for
MIBTEL (-0,001316) is negative and statistically
significant at the 1 level, suggesting that
Tuesdays returns are smaller than those of
Wednesdays. All the rest of dummys coefficients
are not statistically significant. The
coefficient of the conditional standard deviation
of the return equation (risk) is positive for CAC
40 (0,09187), DAX 30 (0,158252), MADRID
(0,108172), MIBTEL (0,012795) and it is negative
for BET10 (-0,08354), FTSE 100 (-0,005897),
However, the estimated coefficients are not
statistically significant. There is no
classical version of the day of the week effect
and no substantial day effect for the developed
stock markets. The conditional variances are
always positive and are not explosive in our
samples. According to the LjungBox Q statistics
we cannot reject the null hypothesis that the
residuals are not autocorrelated. ARCH-LM test
does not indicate the presence of a significant
ARCH effect in any of the sampled markets except
MADRID.
26
The day of the week effects in returns and
volatilities for uptrend period
The estimated coefficients for dummys variables
in volatility equation are not statistically
significant. Thus, there is no evidence of a day
of the week in volatility. The coefficients of
the conditional standard deviation of the return
equation (risk) are positive for all markets
except BET10 (-0,071027) and FTSE100 (-0,008442)
who are negative. However, the estimated
coefficients are not statistically significant.
The estimated coefficient of the Mondays dummy
variable in the return equation for MIBTEL
(-0,00143) is negative and statistically
significant at the 1 level, suggesting that
Mondays returns are smaller than those of
Wednesdays. Also the estimated coefficient of the
Tuesdays dummy variables in the return equation
for MIBTEL (-0,00129) is negative and
statistically significant at the 1 level,
suggesting that Tuesdays returns are smaller
than those of Wednesdays. The conditional
variances are always positive and are not
explosive in our samples. According to the
LjungBox Q statistics we cannot reject the null
hypothesis that the residuals are not
autocorrelated. ARCH-LM test does not indicate
the presence of a significant ARCH effect in any
of the sampled markets except MADRID.
27
5. The Conclusions
The phenomenon of the Day of the Week Effect
seems to disappears from the developed stock
markets and not to have a specific pattern in
general. Nowadays, the stock markets are more
liquid than ever and seem to be more efficient
that the previous decades because of the easiest
capital transmission, the technological changes
and the changes in the stock market
microstructure. So, it is logical for investors
to react more mature, something that induces less
inefficient results.
Finally, the conclusion of this study is that the
phenomenon of the Day of the Week Effect seems
to be weaker than it was in previous decades as a
result of investors behavior. Investors are more
mature, well educated, with more professional
attitude, characteristics that help stock markets
to become more efficient.
28
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