pre-holiday effects: international evidence on the decline and reversal of a stock market anomaly

Journal of International Money and Finance 24 (2005) 1226e1236www.elsevier.com/locate/econbase

Pre-holiday effects: International evidence on thedecline and reversal of a stock market anomaly

Ryan Chong, Robert Hudson*, Kevin Keasey, Kevin Littler 1

The International Institute of Banking and Financial Services, Leeds University Business School,

University of Leeds, Leeds LS2 9JT, UK

Abstract

The pre-holiday effect is one of the best known of the calendar effect anomalies. This paper extendsprior work by examining whether the effect has declined for the U.S., U.K. and Hong Kong markets. Forall three markets, the effect is shown to have declined, but only significantly in the U.S. The result is notsurprising given the relative sophistication of the market. What is surprising, however, is the reversal of thepre-holiday effect during the period 1991e1997, with the mean return on pre-holiday days becoming neg-ative, and the subsequent elimination of this effect during 1997e2003.� 2005 Elsevier Ltd. All rights reserved.

JEL classification: G10

Keywords: Pre-holiday effect; Anomaly; Stock market

1. Introduction

The pre-holiday effect, where stock returns are higher on the day preceding a holiday, is oneof the best known of the calendar effect anomalies with its existence having been empiricallyconfirmed in a number of studies. The purpose of the current paper is to extend prior work byexamining whether this effect declined across the last three decades of the 20th century for thethree major international markets of the U.S., the U.K. and Hong Kong. The remainder of the

* Corresponding author. Tel.: C44 113 3431677; fax: C44 113 3434459.

E-mail address: [email protected] (R. Hudson).1 Federal Reserve Bank of Richmond, P.O. Box 30248, Charlotte, NC 28230, USA.

0261-5606/$ - see front matter � 2005 Elsevier Ltd. All rights reserved.

doi:10.1016/j.jimonfin.2005.08.015

mailto:[email protected]

http://www.elsevier.com/locate/econbase

1227R. Chong et al. / Journal of International Money and Finance 24 (2005) 1226e1236

paper is organized in four sections. Section 2 reviews the existing empirical work. Section 3discusses the methodology and data, while Section 4 presents the empirical results and Section5 offers conclusions.

2. Background

2.1. The existing evidence

The pre-holiday effect is a long standing phenomenon, being well known to both market prac-titioners and to academics for many years; this especially being the case for the U.S. markets.Merrill (1966) finds that the Dow Jones Industrial Average advances disproportionately frequent-ly on days preceding holidays in the 1897e1965 period. Fosback (1976) notes that the S&P500index displays high pre-holiday returns. Lakonishok and Smidt (1988) examine daily returns onthe Dow Jones Industrial Average over the period of 1897e1986 and find that this index producessignificantly higher returns on trading days that immediately precede holidays. Pettengill (1989)finds unusually high returns for pre-holiday trading days for both large and small U.S. firms in aninvestigation period of 25 years from 1962 to 1986. He uses the S&P500 index for a large firmindex and constructs a small firm index by deleting the returns of the 500 firms with the largestmarket values from the CRSP tapes. The mean of the pre-holiday returns is a factor of 13.6 timeslarger than the mean of the non-pre-holiday returns for large firms and a factor of 6.9 times largerfor small firms. Ariel (1990) finds that over one third of the total return accruing to the broad mar-ket in the U.S. over the 1963e1982 period was earned on the eight trading days which fall eachyear before holiday market closings. He uses data drawn from the CRSP value-weighted andequally weighted daily index return files. The mean of the pre-holiday returns is a factor of8.9 times larger than the mean of the non-pre-holiday returns for the equally weighted indexand a factor of 14.0 times larger for the value-weighted index.

Liano et al. (1992) find that for a sample period of 1973e1989 U.S. over-the-counter stocksexhibit unusually high returns on pre-holiday trading days. The study uses returns on the dailyvalue-weighted and the equally weighted return indices of over-the-counter stocks. Wilson andJones (1993) examine three major U.S. markets e the NYSE, AMEX and NASDAQ e for a pe-riod from 1973 to 1991 and find the pre-holiday effect to be strongly significant even after ac-counting for other calendar turning points and the effect of using robust estimation techniques.Fabozzi et al. (1994) test for the effect in the futures market over the period from 1969 to 1989.They investigate 28 futures contracts of which 16 are mainly traded in the U.S. and 12 are moreactively traded in world markets. They find evidence for a significantly higher pre-holiday re-turn in futures contracts compared to non-pre-holiday returns. Thus the studies that have fo-cused on U.S. markets have found significant evidence in support of the pre-holiday effect.

Turning to studies that have considered other markets, Ziemba (1991) examines the effect inJapan using daily data on the Nikkei stock average from 1949 to 1988. He finds that the typicalpre-holiday had returns of about five times the average non-pre-holiday trading day. Cadsbyand Ratner (1992) examine the pre-holiday effect in 10 different countries over a variety oftime periods between 1962 and 1989. They find a significant pre-holiday effect in the U.S.,Canada, Japan, Hong Kong and Australia with reference to their own local holidays. Theyfind no significant pre-holiday effect in several European markets. Kim and Park (1994) finda significant pre-holiday effect in the S&P500, NYSE, AMEX and NASDAQ in the U.S.,the Financial Times 30 Share Index (FT30) in the U.K. and the Japanese NikkeieDow over

1228 R. Chong et al. / Journal of International Money and Finance 24 (2005) 1226e1236

various sample periods between 1963 and 1987. The mean of the pre-holiday returns is a factorof 15.4 times larger than the mean of the non-pre-holiday returns for the S&P500, a factor of9.0 times larger for the NYSE, a factor of 27.0 times larger for the AMEX and a factor of 10.9times larger for the NASDAQ. Mills and Coutts (1995) find a pre-holiday effect in the U.K. onFinancial Times Stock Exchange 100, Mid 250 and 350 indices for the period January 1986eOctober 1992. Arsad and Coutts (1997) find a pre-holiday effect in the U.K. on the FT30 for theperiod 1935e1994. Arumugam (1999) demonstrates the pre-holiday effect in India between1979 and 1997. Coutts et al. (2000) provide evidence for the effect on the Athens Stock Ex-change. Therefore, the small number of studies that have considered other markets offer furthersupport for the existence of a pre-holiday effect.

2.2. Explanations of the pre-holiday effect

Various hypotheses have been offered to account for the pre-holiday effect. Pettengill (1989)considers the possibility that high pre-holiday returns may result from a closing effect. He statesthat other recurring return patterns involve high returns at market closings. For example, manystudies report high returns for securities when the markets close for the weekend. He tests theclosing effect hypothesis by examining returns before market closings not associated with hol-idays and returns before holidays not associated with market closings and finds no empiricalsupport for the hypothesis. Keim (1989) presents evidence that pre-holiday returns calculatedusing data from the CRSP data set may be inflated by systematic patterns in the relativefrequencies of bid and ask transaction prices. His results suggest that, in some surveys, thepre-holiday effect is partly explained by these systematic patterns. Ariel (1990) reviews varioushypotheses to explain the pre-holiday effect. He rules out the possibility that activity by special-ists at the market close can explain the effect both because positive returns start to accrue wellin advance of the market close and because there is little discernible bideask component to thereturn. He also notes that the hourly pattern of positive return accumulation throughout pre-holidays rules out most accounts of pre-holiday strength, which depend on measurement errors.He considers another explanation based on the ‘‘lore of the street’’ as reported in the popularpress that pre-holiday strength occurs due to short-sellers closing their risky positions in ad-vance of holidays. He casts doubt on this inventory adjustment explanation as it is not clearwhy traders should want to close short but not long positions in advance of holidays. In addi-tion, the modest returns on post-holiday trading days suggest that the short positions are notreinstated after the holiday. A further reason to reject the inventory adjustment explanationis that it does not explain the observed positive returns from pre-holiday close to post-holidayopen. Ariel suggests that a hypothesis consistent with the data is that there exists some clientelewhich preferentially buys (or avoids selling) on pre-holidays.

Liano et al. (1992) find that other documented calendar anomalies such as the turn-of-theyear effect, the monthly effect, or the day-of-the-week effect do not cause the pre-holidayeffect. Cadsby and Ratner (1992), by showing that pre-holiday effects exist in a number of in-ternational markets, conclude that the effect is not generated solely by American institutions.They additionally suggest that the absence of the effect in some markets indicates that itmay originate from country-specific institutional practices. Fabozzi et al. (1994) find evidencefor a lesser pre-holiday effect before holidays when the market was not closed. They suggestthat there may be several components to the pre-holiday effect. The inventory adjustmentprocess may dominate around holidays when markets are closed and a favorable holidaymood around holidays when markets are open. As support for the theory that good moods


may influence pre-holiday returns, they refer to the work of Deldin et al. (1986) who show thatthe psychological and physiological state of subjects varies by day of the week and may be re-sponsible for higher Friday returns. Kim and Park (1994) show that the pre-holiday effect existsin three of the major stock markets in the U.S.: the NYSE, AMEX and NASDAQ. They deducethat one (or more) of the following cannot contribute to the holiday effect: the attributes of thecompany and its stock listed on each exchange; the monopolistic specialist system used inNYSE and AMEX compared to a multiple-dealership market (NASDAQ), and the type of dom-inant investors in each exchange. They further point out that the persistence of the effect acrossa number of countries suggests that the effect is not driven by institutional arrangements uniqueto the stock market of a country. Thus institutional factors such as trading methods, clearingmechanisms, settlement procedures and bideask spreads cannot be explanations for the effectas these factors differ between countries. In summary, it can be seen from the previous literaturethat no definitive cause has been established for the effect.

3. Methodology and data

Whatever the cause of the pre-holiday effect, if the substantial number of papers publishedon the topic are coupled with some level of efficiency of the markets, then the effect shouldhave declined across time as investors take advantage of the predictable element of share pricemovements on the day before a holiday. Indeed, Tan and Tat (1998) noted that the effect hadweakened for the Singapore market in the period 1975e1994. Therefore, the publication ofsubstantial evidence on the topic, the relative sophistication of the markets being consideredhere (U.S., U.K. and Hong Kong) and the result of Tan and Tat lead to the following hypothesis:

H1 e the pre-holiday effect has declined across the past three decades.

In testing the above hypothesis daily stock index returns are drawn from Datastream, andverified from independent sources. The sample period, January 1973eJuly 2003, has been cho-sen to capture a long enough time frame over which the holiday effect may have declined. Forthe U.S. market, the Standard and Poor Composite index (S&P500) is used; for the U.K. mar-ket, the Financial Times Industrial Ordinary Index (FT30) is used; and, for the Hong Kong mar-ket, the Hang Seng Index is used.

In this analysis, a holiday is defined as a public holiday which induces the closure of thestock exchange. Any holidays which last for more than a single day, such as the Lunar NewYear in Hong Kong, but which only result in a single market closure are treated as a single hol-iday for the purpose of the analysis. Any holidays which occur back to back, such as ChristmasDay and Boxing Day in Hong Kong and the U.K., or back to back with only an interveningweekend, such as Good Friday and Easter Monday in Hong Kong and the U.K., are treatedas a single holiday for the purpose of the analysis as they result in only a single market closure.Table 1 shows the holidays which have been considered for each country.

4. Empirical results

Broadly following the methodology of Ariel (1990), the trading days in 1973e2003 weredivided into two subsets for each of the international indices: the trading days prior to the


holidays and all the rest. The means and variances of the three indices for these two sets ofdates were calculated and are reported in Table 2, Panel A, together with a t-statistic for thedifference in the means.

The t-test for the difference in the means reported in Table 2, Panel A, assumes that the re-turns in the two samples of data are independent and that the return generating process has beenconstant over the period of the sample. A non-parametric test, less sensitive to these assump-tions, can be carried out under the assumption that the pre-holidays are merely random drawsfrom the full sample of trading days in the investigation period. Table 2, Panel B, reports the c2-statistic testing the null hypothesis that the expected frequency of positive return days amongthe pre-holiday days equals the realized frequency of positive return days among all the tradingdays in the period.

The means of the pre-holiday returns exceed the means of the non-pre-holiday returns byfactors of 4.46, 8.95 and 12.87 for the U.S., U.K. and Hong Kong indices, respectively. Thecorresponding t-statistics show that the difference in means is highly significant in the HongKong market, significant at the 5% level for the U.K., but only significant at the 10% levelin the U.S. The c2 statistics are highly significant in the Hong Kong market, and significantat the 5% level in the U.S. and the U.K. In summary, over the whole period of investigation,the results give strong evidence of a pre-holiday effect in Hong Kong and the U.K., and mar-ginally significant evidence of a pre-holiday effect in the U.S.

Table 1

Holidays for each country 1973e2003

Country Public holidays included for applicable years

Hong Kong Regular

New Year, Lunar New Year, Ching Ming Festival, Good Friday, Easter Monday, Her Majesty the

Queen’s Birthday, Labor Day, Birth of Buddha, Tuen Ng (Dragon Boat) Festival, Hong Kong

Special Administrative Region Establishment Day, July Bank Holiday, August Bank Holiday,

Victory Day, Liberation Day, Mid-autumn Festival, National Day, Chung Yeung Festival, Christ-

mas Day and Boxing Day.

Irregular

The transition of Hong Kong from U.K. to Chinese Rule and Millennium Eve.

Unanticipated market closures (e.g. for severe weather disruption) are not included.

U.S. Regular

New Year, Presidents’ Day, Good Friday, Memorial Day, Fourth of July, Labor Day,

Election Day, Thanksgiving and Christmas Day.

Irregular

National Days of Mourning and Millennium Eve.

Unanticipated market closures (e.g. for power failures, severe weather disruption and on days

following September 11, 2001) are not included.

U.K. Regular

New Year, Good Friday, Easter Monday, May Day, Spring Bank Holiday, August Bank Holiday,

Christmas Day and Boxing Day.

Irregular

Her Majesty the Queen’s Silver Jubilee, Millennium Eve and Her Majesty the Queen’s Golden

Jubilee.

The London market was closed on Thursday 31st December 1998 for conversion to the Euro.

Wednesday 30th December 1998 was the last trading day prior to the New Year holiday.

Unanticipated market closures (e.g. for severe weather disruption) are not included.


To examine whether the effect had diminished over the period under investigation, theexcess of the mean pre-holiday return over that achieved on non-pre-holiday days, withinany given five year sub-period, was plotted. Fig. 1 shows the variation in the effect overtime. For the Hong Kong market, the mean pre-holiday return remains consistently higherthan the mean for non-pre-holiday days. For the U.K., the excess of the mean pre-holiday returnis less pronounced, but it is also predominantly positive across the investigation period. For theU.S. market, the effect appears to decline to the extent that it becomes negative during the late1990s, after which it again begins to increase.

To test for the existence and decline of the pre-holiday effect, the following time series re-gressions were run over the full investigation period:

Rc;tZa0Ca1Dc;tCa2Dc;tTc;tCuc;t ð1Þ

where Rc,t is the daily index return on country c (the U.S., U.K. or Hong Kong) at date t. Dc,t isa dummy variable equal to 1 if date t is a pre-holiday day in country c, and equal to 0 otherwise.Tc,t is a time trend variable equal to the elapsed number of trading days from the start of theinvestigation.

Table 2

Sample means, standard deviations and frequency of positive returns days, for the pre-holiday and non-pre-holiday sub-

sets of days, for the three international indices during 1973e2003

Period 1973e2003 Hang Seng S&P500 FT30

Panel A: means and standard deviationsNon-pre-holiday days

Mean 0.0358% 0.0297% 0.0198%

Standard deviation 1.9665% 1.0458% 1.2630%

Number of days 7242 7460 7544

Pre-holiday days

Mean 0.4608% 0.1326% 0.1771%

Standard deviation 2.1244% 0.8628% 0.8909%

Number of days 300 250 178

t-Statistic for difference of the meansa tZ 3.405*** tZ 1.840* tZ 2.302**

Ratio of pre-holiday returns to non-pre-holidays 12.87 4.46 8.95

Panel B: frequency of advances

Positive return days among total days 3859 3985 3925

Fraction positive return days among total days 0.5117 0.5169 0.5083

Positive return days among pre-holiday days 195 145 104

Fraction positive return days among pre-holiday days 0.6500 0.5800 0.5843

c2-Statisticb 22.439 3.856 4.044

t-Statisticc tZ 4.737*** tZ 1.964** tZ 2.011**

*Significant at 10% level; **significant at 5% level; ***significant at 1% level.a Standard error used in deriving the t-statistic is calculated as:

ðs2holiday=nholidayCs2

other=notherÞ0:5

where sZ standard deviation and nZ number of days.b Letting O signify the observed number of positive return pre-holidays and E signify the expected number of positive

pre-holidays on the null hypothesis that pre-holidays are random draws from the global sample, the c2-statistic is cal-

culated as: c2Z 2(O� E )2/E.c The number given here is the square root of the corresponding c2-statistic; it can be interpreted as a t-statistic for

a two-tailed t-test.


The results of the regressions are shown in Table 3. (Given the graphical evidence of a rever-sal in the decline of the effect in the U.S. market from the late 1990s, the linear test was re-peated for the sample period 1973e1997 and these results are given in Table 3, Panel B.)The significance of the a1 coefficients demonstrates the dependency of the daily returns onpre-holiday days. The negative coefficient of a2 in each regression shows that the effect hastended to decline over time in each of the markets investigated. For the whole sample period,this decline is significant in the U.S. market at the 10% level, but not significant in the othermarkets. However, for the sample period prior to the reversal of the decline in 1997, boththe a1 and the negative a2 coefficients are significant at the 1% level for the U.S. market.

Given the decline in the pre-holiday effect revealed in Table 3 for the whole data set, a ro-bustness check is made to ascertain the extent to which the effect has been exhibited in differentsub-periods. The data in respect of each index was broken down into five sub-periods of equallength. A similar analysis to that reported in Table 2 was performed for each of the sub-periods.Tables 4e6 present the results of these investigations.

In interpreting these results it should be recognized that the sub-periods are comparativelyshort periods of time in which to demonstrate statistical significance given the infrequent oc-currences of holidays. In the Hong Kong market, the mean return on pre-holiday days is largerthan the mean return on non-pre-holiday days for all sub-periods (see Table 4). In each of thefirst four sub-periods, the differences in mean returns are statistically significant on the non-parametric test. In the U.K. market the mean return on pre-holiday days is larger than themean return on non-pre-holiday days for all sub-periods (see Table 6). In the most recentsub-period, the mean return on pre-holiday days is positive, in contrast to the mean returnachieved on non-pre-holiday days. The differences in mean returns are not statistically signif-icant for any of the sub-periods. In the U.S. market the mean return on pre-holiday days is largerthan the mean return on non-pre-holiday days for the first three sub-periods (see Table 5). Thedifference in mean returns is strongly statistically significant in the first sub-period. In thefourth sub-period, the mean return on pre-holiday days was negative in contrast to that achieved

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Fig. 1. The difference between the mean of daily returns (%) on pre-holiday days and on non-pre-holiday days achieved

over any five year sub-period.


Table 3

Results of the time series regression: Rc;tZa0Ca1Dc;tCa2Dc;tTc;tCuc;t

Hang Seng S&P500 FT30

Panel A: period 1973e2003

a0 0.03579 (1.544) 0.02972 (2.467)** 0.01978 (1.368)

a1 0.620 (2.836)*** 0.319 (2.404)** 0.208 (1.060)

a2 �5.342! 10�5 (�1.053) �5.498! 10�5 (�1.886)* �1.27! 10�5 (�0.295)

R2 0.002 0.001 0.000

Annualized percentage

reduction in pre-holiday

effecta

2.24 4.48 1.59

Panel B: period 1973e1997

a0 0.04865 (1.896)* 0.03299 (2.694)*** 0.03283 (0.1958)

a1 0.643 (2.640)*** 0.434 (3.198)*** 0.209 (0.958)

a2 �6.912! 10�5 (�0.943) �1.089! 10�4 (�2.864)*** �1.616! 10�5 (�0.270)

R2 0.002 0.002 0.000

Annualized percentage

reduction in pre-holiday

effecta

2.80 6.53 2.01

*Significant at 10% level; **significant at 5% level; ***significant at 1% level.a Daily proportionate reduction calculated as a2/a1; annualized as a percentage by multiplying by 260! 100.

Table 4

Hong Kong sample means, standard deviations and frequency of positive returns, for the pre-holiday and non-pre-hol-

iday subsets of days, for the Hang Seng during 1973e2003; broken down into five trading sub-periods of equal length

Sub-period 1 2 3 4 5

1973e1979 1979e1985 1985e1991 1991e1997 1997e2003

Panel A: means and standard deviations

Non-pre-holiday days

Mean �0.0357 0.0718% 0.0702% 0.0891% �0.0175%

Standard deviation 2.4570% 2.0187% 1.7564% 1.4023% 2.0492%

Number of days 1439 1448 1450 1460 1445

Pre-holiday days

Mean 0.6854% 0.4205% 0.3674% 0.4807% 0.3241%


Number of days 69 61 58 49 63

t-Statistic for difference of the means tZ 1.952* tZ 1.105 tZ 2.041** tZ 2.664** tZ 1.300

Ratio of pre-holiday returns to

non-pre-holidays

Abs.19.22 5.86 5.24 5.39 Abs.18.55


Positive return days among total days 712 789 813 808 737

Fraction positive return days among total days 0.4721 0.5229 0.5391 0.5355 0.4887

Positive return days among pre-holiday days 41 43 41 34 36

Fraction positive return days among

pre-holiday days

0.5942 0.7049 0.7069 0.6939 0.5714

c2-Statistic 4.354 7.734 6.056 4.594 1.763

t-Statistic 2.087* 2.781*** 2.461** 2.143* 1.328

*Significant at 10% level; **significant at 5% level; ***significant at 1% level.

t and c2 statistics calculated as in Table 2.


on non-pre-holiday days. This negative pre-holiday effect was significant at the 1% level usingthe parametric test. In the final sub-period, the mean pre-holiday return was once again higher,by a factor of 8 times, than that for non-pre-holiday days.

In summary, the results of this section are as follows. First, over the whole investigation pe-riod, there is strong evidence of a pre-holiday effect in Hong Kong and the U.K., and margin-ally significant evidence of a pre-holiday effect in the U.S. Second, regression analysisindicated that the effect had declined for the U.S. (until the late 1990s), but the evidence ofa decline was limited for the other two markets. Third, analysis by sub-periods revealed thatfor the U.S. the effect was positive and strongly significant in the first sub-period (1973e1979); not significant in the second and third sub-periods (1979e1985 and 1985e1991), andnegative and strongly significant for the fourth sub-period (1991e1997). In the final sub-periodthe observed effect returns to being positive, but is not statistically significant.

5. Conclusions

This paper has extended the substantial literature on pre-holiday effects by consideringwhether the effect has declined in recent years for the major international markets of theU.S., the U.K. and Hong Kong. While the results indicate a decline in all three markets, it isonly statistically significant for the U.S. until the late 1990s. Such a result is not surprising giv-en the substantial number and history of papers documenting a pre-holiday effect for the U.S.

Table 5

U.S.: sample means, standard deviations and frequency of positive returns, for the pre-holiday and non-pre-holiday sub-

sets of days, for the S&P Index during 1973e2003; broken down into five trading sub-periods of equal length


1973e1979 1979e1985 1985e1991 1991e1997 1997e2003



Mean �0.0212% 0.0404% 0.0514% 0.0613% 0.0166%


Number of days 1492 1493 1493 1493 1489

Pre-holiday days

Mean 0.3877% 0.1217% 0.2286% �0.2167% 0.1341%



t-Statistic for difference of the means tZ 3.543*** tZ 0.866 tZ 1.698* tZ 3.08*** tZ 0.678

Ratio of pre-holiday returns to

non-pre-holidays

Abs.18.30 3.01 4.45 Abs. 3.53 8.07

Panel B: frequency of advancesPositive return days among total days 757 775 852 828 773

Fraction positive return days among total days 0.4912 0.5026 0.5525 0.5373 0.5006

Positive return days among pre-holiday days 35 32 31 20 27

Fraction positive return days among

pre-holiday days

0.7143 0.6531 0.6327 0.4167 0.4909

c2-Statistic 9.925 4.415 1.139 2.601 0.021

t-Statistic 3.150*** 2.101** 1.067 1.613 0.144




and the relative sophistication of the market. What is slightly surprising, however, is the rever-sal of the effect in the period 1991e1997, with the mean return on pre-holiday days actuallybecoming negative, and the subsequent elimination of this negative effect in the final periodof 1997e2003.

One possible explanation of the ‘double’ reversal is that some market participants are basingtheir trading on the findings of studies which are rather too historic. If traders continue to try toexploit an anomaly, which no longer exists, they may induce a new anomaly, which is the re-verse of the first. The issue of determining when an anomaly has ceased to exist is more dif-ficult than it may appear on first consideration. It requires a careful assessment of thebalance to be struck between using a data series sufficiently long to obtain a reasonable levelof statistical significance and a series short enough to give conclusions which are adequatelytimely. For example, as shown in this study, in the U.S. market an investigation of the effectusing a data period from 1973 to 2003 would conclude that the positive effect still existed.Shorter investigations using data from 1991 to 1997 might come to entirely differentconclusions.

The significant results reported here suggest the need for the following further research.First, there is a need to ascertain whether the pre-holiday effect has declined in other markets.Second, there is a need to explore the range of potential explanations of the reversal. For

Table 6

U.K.: sample means, standard deviations and frequency of positive returns, for the pre-holiday and non-pre-holiday sub-

sets of days, for the FT30 Index during 1973e2003; broken down into five trading sub-periods of equal length


1973e1979 1979e1985 1985e1991 1991e1997 1997e2003



Mean 0.0056% 0.0524% 0.0465% 0.0254% �0.0310%


Number of days 1513 1508 1507 1507 1509

Pre-holiday days

Mean 0.2240% 0.1571% 0.1900% 0.1945% 0.1250%



t-Statistic for difference of

the means

tZ 0.99 tZ 0.694 tZ 1.1370 tZ 1.365 tZ 1.008

Ratio of pre-holiday returns

to non-pre-holidays

39.71 2.99 4.09 7.67 Abs. 4.03


Positive return days among

total days

718 798 831 805 773

Fraction positive return days

among total days

0.4650 0.5168 0.5382 0.5210 0.5003

Positive return days among

pre-holiday days

17 22 24 23 18

Fraction positive return days

among pre-holiday days

0.5484 0.6111 0.6486 0.6053 0.5000

c2-Statistic 0.926 1.238 1.677 1.035 0.000

t-Statistic 0.963 1.113 1.295 1.017 0.004




example, has the reversal been caused by a change in the behavior of the same pool of investorsand/or has the pool of investors changed? Third, as the number of U.S. pre-holiday days in-creases post the reversal, there is the need to determine whether a cyclical pattern of positiveand negative pre-holiday effects is emerging.

In conclusion, the really significant result of the present paper is that the well documentedpre-holiday effect in U.S. markets has declined and then temporarily reversed; one anomalyseems to have been temporarily replaced with another and further research might usefully ex-plore possible causes of such reversals.

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