Day-of-the-Week Trading Patterns of Individual and Institutional Investors

Transcription

1 Day-of-the-Week Tradng Patterns of Indvdual and Instutonal Investors Joel N. Morse, Hoang Nguyen, and Hao M. Quach Ths study examnes the day-of-the-week tradng patterns of ndvdual and nstutonal nvestors. Consstent wh prevous evdence, we fnd an ncrease n the proporton of Monday tradng volume attrbutable to ndvdual nvestors relatve to other days of the week. However, we document that ths ncrease results from a reducton n tradng by nstutonal nvestors, rather than from an absolute ncrease n tradng by ndvdual nvestors. In fact, the absolute tradng volume by ndvdual nvestors s sgnfcantly lower on Monday than on any other weekday. We also document that the degree of day-of-the-week effect vares wh the qualy and dssemnaton of publc nformaton proxed by the market capalaton of each company. I. Introducton The nteractons among dfferent types of nvestors determne the tradng volume, return volatly, transacton costs and the prce of a stock. The tradng behavor of dfferent types of nvestors mght not be the same, due to dfferences n wealth, nformaton and lqudy. Among nvestors, the two groups that attract the most researcher and practoner nterest are ndvdual nvestors and nstutonal nvestors. Gven the ncreasng mportance of nstutons n the U.S. equy markets, understandng the dfferent tradng patterns of the two groups can mprove our knowledge of stock prce dynamcs. Emprcal evdence on stock returns, tradng volume, return volatly and transacton costs for dfferent days of the week s extensve. Monday returns are documented to be generally negatve [French (1980), Gbbons and Hess (1981), Kem and Stambaugh (1984), Lakonshok and Lev (1982), Rogalsk (1984)] and Monday tradng volume s sgnfcantly lower than other days of the week [Jan and Joh (1988), Lakonshok and Maberly (1990)]. In addon, the adverse selecton cost of tradng appears to be hghest on Monday [Foster and Vswanathan (1993)]. Return volatly over the weekend s sgnfcantly lower than the volatly over other days of the week [French and Roll (1986)]. Recently, Venea and Shapra (2007) dscuss how weekends affect both amateur and professonal nvestors. Subsequent to the weekend, ndvduals are prone to ncrease both buyng and sellng, whereas nstutonal nvestors tend towards the oppose behavor. Akyol (2013) fnds that as the length of non-tradng perods such as weekends or holdays lengthens, an upward prce effect n the mornng sesson before the non-tradng perod, The authors thank an anonymous referee, as well as Professor Honghu Chen for helpful comments and suggestons. Joel N. Morse s a Professor of Fnance at Merrck School of Busness, Unversy of Baltmore, Baltmore, MD, USA. Hoang H. Nguyen s an Assocate Professor of Fnance at Merrck School of Busness, Unversy of Baltmore, Baltmore, MD, USA. Hao M. Quach s a Lecturer n Fnance at Lncoln Busness School, Unversy of Lncoln, UK Global Busness and Fnance Revew Fall 2014 Pages

2 178 Global Busness and Fnance Revew Fall 2014 as well as a downward prce effect n the mornng sesson after the non-tradng nterval are both accentuated. Interestngly, he attrbutes ths to uncertanty that ncreases n the length of the nontradng suaton. Chen and Snghal (2003) suggest that short sellers could be responsble for the day of the week effect snce they reverse short posons before a weekend, and re-establsh them after a weekend. Berument and Kyma (2001) do not dfferentate between retal and nstutonal partcpants, but do note that Monday returns are lower than on other days, and the volatly of returns are hgher on Frdays. Recent work on non-us market by Dcle and Levends (2012) who study 51 markets, and Lnden et al (2006) who examne 18 stock exchanges both found evdence for the day-of-the-week effect. One potental explanaton for the above day-of-the-week anomales could be the dfferental behavor of dfferent groups of nvestors. A number of emprcal studes have examned tradng by eher nstutonal nvestors or ndvdual nvestors over the week. On one sde, Lakonshok and Maberly (1990), and Abraham and Ikenberry (1994) use odd-lot sales on the New York Stock Exchange (NYSE) as a percentage of NYSE volume to proxy for ndvdual nvestor s actves, and document an ncrease n the proporton of odd-lot trades on Monday. They propose that ndvdual traders are the cause of the day-of-the-week rregulary. On the other sde, Sas and Starks (1995) use nstutonal ownershp data to proxy for the presence of nstutonal nvestors and fnd that the day-of-the-week effect s stronger n stocks havng more nstutonal ownershp. Usng more recent data, Chan et al (2004) also examne the Monday effect condoned on nstutonal ownershp, and fnd that ths phenomenon becomes weaker n stock markets charactered by a hgh percentage of nstutonal holdngs. It should be noted that these studes focus on the day-of-the-week varatons n tradng whn only one group of nvestors at a tme. Thus, n ths study, we attempt to fll the gap n the lerature by smultaneously examnng the tradng behavor of both nstutonal and ndvdual nvestors, whch wll allow us to have a better understandng about ther relatve tradng actves and roles n the day-of-the-week anomaly. Usng methodologes developed by Lee (1992), we examne the tradng actvy on a sample of 300 NYSE stocks durng the year We classfy each trade as eher large or small, based on s dollar tradng volume. All the transactons wh dollar volume of less than $10,000 are classfed as small trades, and those of more than or equal to $10,000 are classfed as large trades. The small trades and large trades are used to proxy for the tradng actvy by ndvdual nvestors and by nstutonal nvestors, respectvely. Ths approach yelds new nsghts nto the varaton n tradng volumes throughout the week. Specfcally, we fnd that the fracton of trades executed by ndvdual nvestors s hgher on Monday than on any other days of the week. Moreover, we document that ndvdual nvestors trade less frequently on Monday than on other days. Further analyss of ths apparent paradox shows that the greater fracton of trades by ndvdual nvestors on Monday s a result of a sgnfcant reducton n trades by nstutonal nvestors on that day. The evdence s consstent wh the hypothess suggested by Sas and Starks (1995) that the durnal varaton n tradng actvy by the nstutonal nvestors s lkely to be the cause for the observed day-of-the-week effect. The results of ths study are related to the theoretcal work of Foster and Vswanathan (1990). In ther model, nformed traders accumulate prvate nformaton through the weekend, when publc nformaton s not produced at the normal weekday rate. As a result, unnformed traders are at a larger dsadvantage at the begnnng of the week. Therefore, unnformed traders who have 1 The revewer suggested the mportance of expandng the tmeframe of the data beyond ths sngle year. We agree, and take ths as a suggeston for future research.

3 Morse, Hguyen & Quach Day-of-the-Week Tradng Patterns 179 dscreton over the tmng of trade wll delay ther transactons untl later n the week. The results from ths study ndcate that a proporton of both ndvdual nvestors and nstutonal nvestors try to avod costly Monday. Also, the reducton n absolute tradng actves by both types of nvestors vares wh the qualy and dssemnaton of publc nformaton proxed by the market capalaton of each company. II. Data and Methodology A. Data We examne tradng actvy for a random sample of 300 common stocks (those wh a CRSP code of eher 10 or 11) lsted on the NYSE. We use two databases n our analyss. The frst one s the TAQ database, from whch we extract tradng nformaton. The second data source s the Center for Research n Secury Prces (CRSP), from whch we gather general nformaton about the sample of secures. After matchng stocks from the two databases, we keep only those equy secures that have a begnnng-of-year prce and an end-of-year prce between $5 and $100 per share. The excluson of stocks wh a prce less than fve dollars ensures that lqudy s not affected by the relatvely hgh percentage bd-ask spread caused by low prce, whle stocks wh prce greater than $100 are excluded because they are less lkely to have small trades assocated wh ndvdual nvestors. Fnally, we requre that stocks n the sample have at least an average of 12 trades per day to ensure enough observatons for analyss. From the resultng sample, we randomly choose 300 stocks to use n our analyss. The descrptve statstcs n Table 1 show that the mean (medan) market capalaton of the 300 sample frms s 8,422 (1,950) mllon dollars and the average (medan) number of trades for the 300 stocks s 69,326 (24,131). Table 1: Descrptve Statstcs Our sample ncludes 300 randomly selected common stocks (those wh a CRSP code of eher 10 or 11) lsted on the NYSE on the year We requre that selected stocks have an end-of- year prce between $5.00 and $ and have at least 12 trades per days to ensure that the sample has suffcent lqudy. Ths table reports descrptve statstcs for our sample n terms of number of trades, market capalaton and average stock prces. Characterstcs Mean (Medan) Frst Quartle (Thrd Quartle) Mnmum (Maxmum) Number of Trades 69,326 (24,131) 15,585 (65,838) 4,256 (2,969,473) Market at Begnnng (In Mllons of Dollars) 8,422 (1,950) (7,595) (45,532) Average Prce at the Begnnng (24.47) (34.71) 5.21 (99.51)

4 180 Global Busness and Fnance Revew Fall 2014 B. Methodology Ths study uses a method developed by Lee (1992) to classfy each trade as large or small based on s dollar volume. All transactons of $10,000 or less are classfed as small trades, and the remander s classfed as large trades 2. Although ndvdual nvestors may place orders valued greater than $10,000, s unlkely that any nstutonal nvestors wll trade at dollar volume less than $10,000. Lee (1992) justfes the use of the $10,000 threshold for small trades snce ensures small trades wll have ltle nstutonal actvy yet stll contan enough observatons. Usng ths creron, about 48% of all the trades are classfed as small trades. The small trades are used to proxy for the tradng actvy by ndvdual nvestors, whle the large trades are used to proxy for the tradng actvy by nstutonal nvestors. Each day, the numbers (volume and dollar volume) of small and large trades are obtaned for each stock. To make them comparable across stocks, these numbers are further deflated by the total aggregated numbers (volumes dollar volume) of small and large trades of the stock durng the year. The deflated measure on each day represents the small (large) trades on that day as a proporton of annual small (large) trades n year Mathematcally, let y T Year where y s the scaled measure of number of trades (volume, dollar volume) of se (small or large) of stock durng perod t, T s the total number of trades (volume, dollar volume) of se (small or large) of stock on day t. s the total number of trades (volume, dollar volume) of se of stock durng the year For each stock, the followng statstcal model s estmated for both ndvdual and nstutonal trades. 3 Year y 5 j2 D j, j (1) Where y s the measure of tradng actvy for stock on day t, Dj (j = 2, 3, 4, 5) s the day of the week, from Tuesday through Frday. Therefore, wll capture the average tradng actvy for stock on Monday whle,j wll capture the dfference n tradng between other weekday and Monday. To reduce the mpact of heteroscedestcy and seral-correlaton n resduals, we employ generaled methods of moments (GMM) and Newey-West (1987) correcton for resdual seral correlaton n our regresson model. We use an asymptotc normal dstrbuton to test the sgnfcance of coeffcent on each day-of-the-week dummy varable. 2 To check the sensvy of the results to the threshold of small trades, a threshold of $20,000 for small trades s also used. The results from the two dfferent thresholds are qualatvely smlar. 3 Ths regresson model s frst used by French (1980) to nvestgate the varaton n stock return among days of the week and become popular n ths feld.

5 Morse, Hguyen & Quach Day-of-the-Week Tradng Patterns 181 Based on estmaton on ndvdual stock, we report the average of coeffcents for each day-ofthe-week dummy varable, as well as the number of posve coeffcents. These results are reported for the entre sample of 300 stocks and each capalaton-subsample of 100 stocks. III. Emprcal Evdence A. Varaton n the Proporton of Trades by Indvduals Table 2 provdes evdence on day-of-the-week varaton n the proporton of trades by ndvdual nvestors. Panel A of Table 2 reports results based on the proporton of volume ordered by ndvdual traders. For the entre sample, the proporton of ndvdual trades on Monday s 0.823%, 0.785%, 0.692%, and 0.581% hgher than that on Tuesday, Wednesday, Thursday, and Frday, respectvely; and all coeffcents are sgnfcant at level. Ths suggests that there s sgnfcant varaton n day-of-the-week tradng actvy by ndvdual nvestors. A smlar concluson can be drawn from other panels. Panel B of Table 2 shows that the dayof-the-week varaton n dollar tradng volume s sgnfcant. For the entre sample, the dollar volume made by ndvdual nvestors on Monday s 0.731% hgher than that on Tuesday, 0.613% more than that on Wednesday, 0.583% more than that on Thursday and 0.461% more than that on Frday. Smlarly, Panel C ndcates that the proporton of number of trades by ndvduals on Monday hgher than other tradng day by 1.268%, 0.924%, 1.151% and 0.804%, respectvely. These results are consstent wh the results of Lakonshok and Maberly (1990), who document a relatve ncrease n tradng actves by ndvdual nvestors. Another fndng on Table 2 s that the ncrease n proportonal tradng on Monday by ndvduals s largest for the lowest capalaton sub-sample. In terms of proporton of tradng volume, for small-capalaton stocks, Monday tradng by ndvduals s more than 1% hgher than on any other tradng days, whle for the medum and large stock sub-samples, the numbers are all less than 0.8%. A smlar tendency can be observed for dollar volume and number of trades by ndvduals n Panel B and C. Table 2 documents a sgnfcant drop n tradng by ndvduals on other week days compared to Monday. That phenomenon could result from greater partcpaton by ndvdual nvestors n the equy market on Monday, or from a reducton n tradng actves by other traders, namely nstutons, on Monday. To clarfy the above ssue, n the followng sectons, we examne the absolute partcpaton of ndvdual nvestors and by nstutons ndependently across days of the week. For brevy, below only the results based on tradng volume are reported. 4 B. Varaton n Indvdual Trades Table 3 provdes further detals on the day-of-the-week varaton n the ndvdual tradng volume. For the whole sample, the coeffcent of % means that Tuesday tradng volume by ndvdual traders s hgher than that on Monday by an average of % of the total ndvdual tradng volume of the year Also, tradng volume by ndvdual on Monday s lower when comparng wh Wednesday and Thursday numbers by about % and % of the total ndvdual tradng volume of the year; all numbers are statstcally sgnfcant at 1% level. The 4 The results based on dollar volume and number of trades s quantatvely and qualatvely smlar to those based on tradng volume, and are avalable upon request.

6 182 Global Busness and Fnance Revew Fall 2014 dfference between Frday and Monday s % and margnally sgnfcant at 10% level. Out of 300 stocks, there are about 200 posve coeffcents for each day. Table 2: Day-of-the-Week Varaton n the Proporton of Trades by Indvduals The proporton of ndvdual trades on a gven day s calculated by addng all the ndvdual trades (volume, dollar volume) together across all the stocks, then dvded by all the trades (volume, dollar volume) of all the stocks on that day. Ths proporton s then analyed for the day-of-the-week varaton. y t 5 D 2 t where t s the error term, y t s the dependent varable calculated as defned above, and the D s the day of the week dummy. ***,**,* are the sgnfcant level of 1%, 5% and 10%, respectvely. Day-of-the-Week Tests Panel A: Varaton n Proporton of Volume by Indvdual Traders Lowest Market Medum Market Hghest Market All 300 stocks Tuesday *** ** *** *** Wednesday *** ** *** Thursday *** ** ** *** Frday * * *** Day-of-the-Week Tests Panel B: Varaton n Proporton of Dollar Volume by Indvdual Traders Lowest Market Medum Market Hghest Market All 300 stocks Tuesday *** *** *** *** Wednesday *** ** *** *** Thursday *** *** *** *** Frday *** *** Day-of-the-Week Tests Panel C: Varaton n Proporton of Number of Trades by Indvdual Traders Lowest Market Medum Market Hghest Market All 300 stocks Tuesday *** *** *** *** Wednesday *** ** *** *** Thursday *** ** *** *** Frday * *** ***

7 Morse, Hguyen & Quach Day-of-the-Week Tradng Patterns 183 Table 3: Day-of-the-Week Varaton n Tradng Volume by Indvdual For each tradng day, the volume of ndvdual trades on each stock s scaled by the 2000 total volume of ndvdual trades on that stock. The followng regresson equaton s estmated for each stock usng GMM. y 5 j2 D j, j where s the error term for stock, y s the scaled ndvdual tradng volume on each day t, and the D j s the day of the week dummy. ***,**,* are the sgnfcant level of 1%, 5% and 10%, respectvely. Day-of-the-Week Tests Lowest Market Medum Market Hghest Market All 300 stocks Tuesday Coeffcent Average (*10 4 ) 1.235*** 1.965*** 1.862*** 1.687*** Wednesday Coeffcent Posve Number Average (*10 4 ) 1.258*** 1.102*** 1.852*** 1.404*** Posve Number Thursday Coeffcent Average (*10 4 ) 0.689** 1.981*** 0.957*** 1.209*** Posve Number Frday Coeffcent Average (*10 4 ) 0.892* 1.287** * Posve Number When we look at the three capalaton sub-samples we see a smlar tendency. For the subsample of the hghest market capalaton stocks, the average of the Tuesday coeffcent s %, whch ndcates that ndvdual tradng volume s hgher on Tuesday than on Monday, by % of the annual ndvdual tradng volume. The number of posve coeffcents for ths group of stocks s 85. For the other two se groups, Tuesday tradng s hgher than Monday level for %, %, respectvely. Also, the number of posve coeffcents s 74 and 68, respectvely. On Wednesday and Thursday, the coeffcents are all posve and sgnfcant at 1% level. For the three subsamples, ndvdual tradng volumes seems to reduce the least for the Lowest market capalaton group as coeffcent for ths groups s smaller than the other two n most cases. The results of ths secton suggest that ndvdual traders are less actve on Monday n absolute terms. Ths fndng ndcates that the greater proporton of tradng accounted for by ndvdual traders on Monday (documented n Table 2) s not caused by an ncreases n tradng by ndvdual on Monday but by an even greater reducton n nstutonal tradng on Monday. The next secton examnes the day-of-the-week varaton n nstutonal tradng volume.

8 184 Global Busness and Fnance Revew Fall 2014 C. Varaton n Instutonal Trades Table 4 reports the day-of-the-week varaton n tradng volume by nstutons. It s evdent that all coeffcent show posve and sgnfcant and ths mples that nstutons also trade more on other days than on Monday. For the whole 300-stock sample, Monday tradng volume by nstutons s lower than that on Tuesday, Wednesday, Thursday and Frday by %, %, %, and %, respectvely. The coeffcent of % on Tuesday suggests that tradng volume by nstutons s hgher than that on Monday by an average of % of the total nstutonal tradng volume of the year The number of posve coeffcents for those 4 days s above 200. When we examne the three capalaton subsamples, we see a smlar pcture; all coeffcents are posve and statstcally sgnfcant. Ths suggests that the varaton n tradng by nstutons prevals for all market capalaton segments. Another mportant fndng s that, the coeffcents vewed n Table 4 are sgnfcantly larger than correspondng number n Table 3. It means that on Monday, nstutons reduce ther tradng more, n percentage terms, than do ndvdual nvestors. For example, for the whole sample Monday tradng by ndvdual nvestors s % lower than ther actves on Tuesday whle the dfference for nstutons s %. Smlarly, the dfference number between Wednesday and Monday s % and % for ndvduals and nstutons, respectvely. It s consstent wh our argument that the relatve ncrease n proportonal tradng actves by ndvdual nvestors on Monday s not caused by an ncrease n ther absolute tradng volume but rather by a larger reducton n tradng by nstutonal nvestors. Table 4: Day-of-the-Week Varatons n Tradng Volume by Instutons For each tradng day, the volume of nstutonal trades on each stock s scaled by the 2000 total volume of trades by nstutons on that stock. The followng regresson equaton s estmated for each stock usng GMM. where y 5 j2 D j, j s the error term for stock, y s the scaled nstutonal tradng volume on each day t, and the D j s the day of the week dummy. ***,**,* are the sgnfcant level of 1%, 5% and 10%, respectvely. Day-of-the-Week Tests Lowest Market Medum Market Hghest Market All 300 stocks Tuesday Coeffcent Average (*10 4 ) 3.261*** 2.671*** 5.293*** *** Posve Number Wednesday Coeffcent Average (*10 4 ) 4.201*** 3.282*** 2.679*** 3.387*** Posve Number Thursday Coeffcent Average (*10 4 ) 4.251*** 3.502*** 6.287*** 4.680*** Posve Number Frday Coeffcent Average (*10 4 ) 0.758* 0.897** 2.814*** 1.491*** Posve Number

9 Morse, Hguyen & Quach Day-of-the-Week Tradng Patterns 185 IV. Conclusons The lerature has documented a day-of-the-week phenomenon n whch tradng actvy on Monday s sgnfcantly lower than on other busness days. A number of studes have nvestgated ths day-of-the-week varaton by examnng the tradng behavor of eher nstutons or ndvduals n solaton. In ths study, we attempt to fll a gap n the lerature by smultaneously examnng the tradng behavor of both nstutonal and ndvdual nvestors. Our results shed lght on the role each type of nvestor plays n ths tradng anomaly. A revewer suggested the mportance of expandng the tmeframe of the data beyond the sngle year analyed. We agree, and suggest ths for future research. Consstent wh the lerature, we fnd that the proporton of tradng volume by ndvdual nvestors ncreases on Monday. However, when we examne the absolute tradng actves by ndvdual nvestors, we fnd that ther tradng on Monday s actually sgnfcantly less than other day of the week. Hence, we hypothese that the relatve ncrease n proportonal tradng by ndvdual nvestors documented on Monday may be caused by a sgnfcant drop n the absolute level of tradng by nstutons. Consstent wh our hypothess, when examnng tradng by nstutons alone, we fnd that relatve to other weekday, on Monday nstutons reduce ther tradng by a large percentage than that by ndvdual. In general, our fndngs support the hypothess that uneven tradng pattern of nstutons s the man factor behnd the day-of-the-week agent varaton phenomenon. References Abraham, Abraham and Davd Ikenberry 1994, The Indvdual Investor and the Weekend Effect, Journal of Fnancal and Quantatve Analyss 29, Aykol, Al C., 2011, Stock Returns Around Nontradng Perods: Evdence from an Emergng Market, 21, 20, Berument, Hakan and Kyma, Hall, 2001, The Day of the Week Effect on Stock Market Volatly, Journal of Economcs and Fnance, 25, 2, Chan, S.H., Leung,W.K. and K. Wang, 2004, The Impact of Instutonal Investors on the Monday Seasonal, Journal of Busness 77, Chen, Honghu and Sngal, Vjay, 2003, Role of Speculatve Short Sales n Prce Formaton: The Case of the Weekend effect, LVIII, 2, Dcle, M. F. and Levends, J.D., 2012, The Day-of-the-Week Effect Revsed: Internatonal Evdence, Journal of Economcs and Fnance, Foster, F. Douglas and S. Vswanathan, 1990, A Theory of the Interday Varatons n Volume, Varance, and Tradng Costs n Secury Markets, Revew of Fnancal Studes 3(4), Foster, F. Douglas and S. Vswanathan, 1993, Varatons n Tradng Volume, Return Varably, and Tradng Costs, Evdence on Recent Prce Formaton Models, Journal of Fnance 48,

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