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Managerial FinanceEmerald Article: The effect of stock splits on iShare exchange-traded funds

Pia Bandyopadhyay, James Hackard, Yiuman Tse

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Managerial FinanceVol. 36 No. 2, 2010pp. 134-159# Emerald Group Publishing Limited

0307-4358DOI 10.1108/03074351011014550

The effect of stock splits oniShare exchange-traded funds

Pia BandyopadhyayCollege of Business Administration, California State University,

Long Beach, California, USA

James HackardTexas A&M University San Antonio, San Antonio, Texas, USA, and

Yiuman TseCollege of Business, University of Texas at San Antonio,

San Antonio, Texas, USA

Abstract

Purpose The purpose of this paper is to examine the pre- and post-split behavior for trades and

quotes of iShare exchange-traded funds (ETFs) that split in June 2005. The objective is to determinewhether post-split changes in the bid-ask spread, trade turnover, average dollar-size trade, frequencyof small trades, trade price location, and order imbalance support either or both of the two widelyexamined hypotheses for the motivation for share splits.Design/methodology/approach The impact of the iShares split around the split date wasstudied, using the measures above to examine the support, if any, for each of two hypotheses, brokerpromotion and/or the trading inconvenience, with regard to the sample and time period under study.Findings Bid-ask spread, average dollar order size, and frequency of small trades were found tofail to reject the broker-promotion hypothesis, while the increase in post-split turnover fails to rejectthe trading-inconvenience hypothesis. Changes in the trade-price-location parameter and in orderimbalance fail to support either hypothesis.Practical implications Because of the importance of basket securities in the determination of theprices for listed securities, issuers of these securities, investors and regulators should be interestedwhether the price behavior of splitting iShares is similar to that experienced in other securities.Originality/value Numerous studies in the literature have investigated the effects of stock splitson individual securities, but it is believed, none has yet appeared studying the recent splits in iShares.

Keywords Bid offer spreads, Share prices, Share values, Investment funds, Stock exchanges

Paper type Research paper

IntroductionCorporations issuing stocks and investment companies trading stocks face thechallenge of providing securities that can be purchased by a wide variety of investorswho wish to diversify their investment risk. Companies have used stock splits of shareswhose price is increasing to attract a broader base of shareholders. For existingshareholders, the effect of the split is cosmetic, as their proportionate ownership is the

same after the split as before, and the companys cash flows are unaffected. Stock splitshave been widely investigated in finance literature.Stock splits have been common for individually listed securities, but only recently

have splits occurred in the exchange-traded-funds (ETF) market. In June 2005,Barclays Global Investors undertook the first-ever share splits for 12 of the iShareETFs they had issued, thus allowing smaller initial investments in the relativelyhigher-priced funds. Their goal was to cause the price per share of the iShare funds toapproximate the average share price of a US listed security (stock).

On June 9, 2005, share prices of the 12 iShare (ETFs) dropped to recognize the effectof splits for those ETFs. We study pre-and post-split behavior of the measures

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Stock splits oiShare exchang

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indicative of the motivations of the investors of these funds and of the brokers sellingthe funds. We investigate two hypotheses that have been of interest in split literature;broker promotion and trading inconvenience. The broker-promotion hypothesis(Angel, 1997; Schultz, 2000) is based on the premise that a post-split increase in relative

spreads motivates brokers to promote the splitting stocks to small investors. Thetrading-inconvenience hypothesis posits that investors will postpone purchases untilafter the ex-date in order not to deal with the inconvenience of the due-bill process,which requires that stockholders who sell their shares between the record date of thesplit and the ex-date of the split must provide the broker a document (the due bill)stating that additional shares are due the purchaser as a result of the split.

Measures that could favor or reject either hypothesis include: relative bid-askspread, volume turnover, frequency of small trades, transaction price placement, andorder imbalance. We detect mixed results, with the increase in average daily spreads,decline in average order size, and increase in frequency of small trades failing to rejectthe broker-promotion hypothesis, while the increase in turnover following the split

fails to reject the trading-inconvenience hypothesis. Changes in trade-price-locationparameter and order imbalance fail to support either hypothesis.The growing significance of trading in basket securities such as ETFs has meant

that changes in the prices of the individual securities upon which the ETFs are basedare often determined by price changes in the ETF markets. The iShares series of ETFsissued by Barclays Global International track major market indexes and cover a broadspectrum of investment market capitalization, investment styles, market sectors, andinvestment options across domestic and global markets.

Because of the importance of basket securities in the determination of the pricesfor listed securities, issuers of these securities, investors, and regulators should beinterested whether the price behavior of splitting iShares is similar to that experiencedin other security markets. A point of particular interest should be the difference

between the fees in ETF markets and those of regular mutual funds, determined by thebid-ask spread and broker commissions.

Bid-ask spread is an implicit transaction cost that investors bear when buyingor selling an ETF. This transaction cost is approximately one-half of the ETFs spread.Conventional mutual funds are exempt from spread fees since investors purchase atthe net asset value of the fund. Also, purchasing no-load funds directly from a fundcompany eliminates broker commissions in mutual funds, while trading in most ETFsinvolves broker-dealer commissions that can range between $10 and $50 per trade,depending on the size of the trade, the assets invested, and the type of broker i.e.discount or full service. All of these costs can be exacerbated through active trading orby holding an ETF for short periods, or both.

Spread costs are particularly interesting since they give rise to a paradox. On theone hand these can be minimized through a passive buy and hold strategy, but doing sowould defeat the advantage of intraday trading offered by ETF markets. ETFs wereoriginally constructed to provide a single security that tracks a major index, equitysector, international market, region, country, or commodity. Intraday trading of ETFsenables investors to buy or sell all of the securities that make up an entire market witha single trade, thereby providing the flexibility to get into or out of a position at anytime throughout the day. Traders thus have the opportunity to track the direction of themarket, and execute accordingly, allowing active traders to take advantage of short-term movements in the market while still maintaining a passive strategy.

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With the overwhelmingly large number of ETFs that have recently begun trading,investors now have a plethora of funds from which to choose[1]. Competition hasdriven the cost of buying ETF shares to low levels, and brokers are under mountingpressure to promote the funds, and be more aggressive when pitching their products.

Marketing of ETFs is a recently observed trend, and mutual funds outsold ETFs byas much as 50 to 1 in the latter 1990s. Predictions of the Financial Research Corporationare that by the year 2007 total ETF assets will approach $1 trillion, but that is still notas large as the $7 trillion assets of the mutual funds industry in 2003. An explanationfor this is that, until recently, ETFs were benign instruments that nobody sold, unlikemutual funds that have always been actively promoted by the sell side. Competitionappears to have altered this outlook. Our results indicate that besides the intention toincrease customer base, a split provides brokers added incentive to promote an ETF toinvestors, in order to profit from higher spreads.

Effective promotion entails active trading, leading to higher spreads for brokers,since trading characteristics of ETFs resemble those of single stocks. At the same time,they offer certain advantages over both mutual funds and stocks.

Advantages over mutual funds include:

. Continuous price determination and share pricing of ETFs vs end of day pricingand trading of mutual funds.

. Purchase and sale of ETF shares on margin, which is not allowed for mutualfunds.

. Placement of stop and limit orders for ETFs, also not allowed for mutual funds.

Advantages of ETFs compared to owning a stock include:

. Holding ETF securities offers investors the advantage of maximum diversificationof firm-specific risk.

.

Cost of informed trading is minimized with basket securities.. iShares have no minimum required investment.

. Odd-lot trading of iShares is allowed.

Our research investigates the effects of the split in iShares at the time the resultingshare prices arising from the splits are reflected in the funds (the ex-date price). Thereare numerous studies in the literature investigating the effects of stock splits onindividual securities, but to our knowledge, none has yet appeared studying the recentsplits in iShares. We investigate the effect of iShares splits in two broad categories:transaction costs and trading characteristics around the event date. The analysis oftransactions costs employs the measurement of the bid-ask spread, which determines

the traders profit. The possibility of an increase in spreads following the split mightmotivate a broker to promote the shares of a fund that has split. The effects of the splitson number of trade and average size trade are summarized in Appendix 1.

The analysis of trading characteristics involves several variables. First, wedetermine the volume turnover, which measures the volume of trades as a percentageof the number of shares outstanding. This measurement indicates how actively a stockis traded. Second, we look at the average trade size, computed as total amount of trades(shares of the fund traded) divided by the number of transactions, and the frequencyof small trades (those of one or two lots). A lot is the minimum number of shares thatmay be traded at one time. For stocks the usual minimum lot size is 100 shares.

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The change in average order size and frequency of small trades indicates whetherbrokers are motivated to promote the splitting shares to smaller investors.

The third variable we study is the placement of the transaction price relative to thebid and ask prices. Having more trades executed around the ask price would indicate

pressure to purchase, while more trades executed around the bid price would indicatepressure to sell. The final variable we examine is order imbalance, which is the excessof buy orders over sell orders, expressed as a percentage of total trades executed duringeach day. A positive order imbalance is indicative of the pressure to purchase shares.

Recall that the objective of our analysis is to test the two major hypothesesregarding the effects and motivations for stock splits; the broker-promotion hypothesisand the trading-inconvenience hypothesis. If the evidence shows that brokers aremotivated to promote more investments by small investors after the split of theiShares, and that the wider spreads following the split occur to the disadvantage ofthese investors, this finding would suggest that regulators should step up theirsupervision of brokers to insure that they act in the best interest of investors withregard to share splits.

The rest of the study is organized as follows. The following section discusses priorliterature and develops the hypotheses. The next section describes the data andpreliminary descriptive statistics. The penultimate section lays out the methodologyand analyzes the evidence. The last section briefly summarizes and concludes thestudy.

Prior literature and hypothesesSeveral studies have investigated the effects of stock splits on individual securities,primarily looking at the broker-promotion hypothesis and the trading-inconveniencehypothesis. The broker-promotion hypothesis is based on the premise that a post-splitincrease in relative spreads (Angel, 1997; Schultz, 2000) motivates brokers to promotethese stocks to small investors and profit from the higher spreads.

The trading-inconvenience hypothesis posits that investors prefer not to deal withthe inconvenience of the due-bill process and will postpone purchases until after theex-date. This is because the stock split makes it unattractive for investors to tradethe stock between the record date and the ex-date as they have to deal with attacheddue bills, which are documents telling the broker that additional shares are due to thepurchasing shareholder after the split.

Studies advancing support for the broker-promotion hypothesis include Baker andGallagher (1980), Angel (1997), and Schultz (2000). Schultz (2000) identifies a significantincrease in the number of small buy orders after a split as evidence of the broker-promotion hypothesis. Grinblatt et al. (1984) find significant cumulative abnormalreturns for the three-day period extending from one day before the ex-date until one day

after the ex-date. They explain these abnormal returns as the result of broker promotion.Maloney and Mulherin (1992) support the broker-promotion hypothesis on the basis thatclosing prices on or after the ex-date are closer to the ask than to the bid price, resultingin a higher ex-split return due to an increase in small investor buying accompanied byhigher spreads.

Nayar and Rozeff (2001) offer support for the trading-inconvenience hypothesis.They provide evidence that relates record-date returns, when-issued premiums, andex-date returns to lower stock prices that are probably a result of investor aversion tosplits. The trading-inconvenience theory is consistent with the microstructure view ofsplits. Easley et al. (2001) report an increase in trading costs for uninformed investors

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after a stock split. Conrad and Conroy (1994) provide evidence of changes in orderflow around the ex-date that may be considered an indication of investors avoidingpurchases of shares until after a split.

While the studies above examine splits in common stocks, the first study that

investigates splits in mutual funds is by Rozeff (1998). He finds that, unlike commonstocks, mutual funds are not associated with post-split capital appreciation, increase inthe number of shareholders, or an increase in total assets. The only effect of the split isto bring the level of the average per-account number of shares back into the range ofnon-splitting funds. Rozeff cites this as the only likely rationale for a mutual fund split.

Dennis (2003) examines the March 2000 two-for-one split of the Nasdaq-100 IndexTracking Stock. He argues that the absence of a signaling effect in the index stock splitallows investigation of the pure liquidity effects of the split. He finds post-splitimprovement in liquidity for smaller trades which helps smaller investors. However,the split puts large traders at a disadvantage as the wider bid-ask spread results inhigher trading costs that cut into the profit of these traders. In an earlier study, Conroyet al. (1990) provide evidence of post-split wider spreads in New York Stock Exchange

(NYSE) listed equities.We investigate the recent splits in the increasingly popular iShares, which is

interesting for two reasons. First, the iShares are among the first ETFs to split; andsecond, they comprise an important part of equity markets, as they offer investors theadvantages of traditional mutual funds in addition to the trading flexibility of a stock.We test the two most popular hypotheses forwarded by the literature with respect tosplits: the broker-promotion hypothesis and the trading-inconvenience hypothesis.

We use measures of liquidity, order-flow characteristics, and volume turnover toanalyze the hypotheses. If the broker-promotion hypothesis holds we would expect tofind significant decreases in average buy-order size, corresponding increases infrequency of small trades, and transaction prices closer to ask prices within the bid-ask

spread. Conversely, fewer buy orders, coupled with transaction prices closer to bidprices, would lend support to the trading-inconvenience hypothesis. Inconsistencies inevidence would suggest that the motives for fund managers in splitting iShares differfrom the motives surrounding a company managers decision to split common stock.For example, Rozeff (1998) suggests that, all else equal, investors prefer a lower pricedfund and that managers respond to this demand by splitting the stock.

Data and price statisticsWe examine 12 iShare funds that split in June 2005, all of which are traded on theAmerican Stock Exchange. Additionally, we designate a sample of 12 non-splittingiShare funds as the control group. We repeat the analyses for the control group, tocompare and contrast the results between the splitting and non-splitting funds.

We select the 12 most actively traded funds from among those that did not split.Appendices 1 and 2 list, respectively, our split sample and the control group, alongwith their ticker symbols. The split sample also includes the split factors. Of the 12funds in our sample, eight experience a two-for-one split while the remaining fourundergo a three-for-one split.

The chronology of the split event was as follows:

(1) June 6, 2005, the record date determining shareholders of record;

(2) June 8, the payable date, post-split shares were delivered to the DepositoryTrust Company (DTC);

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(3) June 9, the ex-date, split-adjusted shares and prices were reflected in the market;and

(4) June 13, the due-bill redemption date, additional shares were delivered from the DTCto shareholders of record and to those who purchased shares on June 6, 7, and 8.

We obtain from the NYSEs Trade and Quote (TAQ) database intraday transaction datafor all trades and quotes between 9:30 AM and 4:00 PM for the trading days during theperiod of our study. The TAQ data are filtered following procedures recommended byBessembinder (1999, 2000).

The period before the ex-date is the pre-period, and the period after the ex-date isthe post-period. We report results for ten-day pre- and post-periods[2]. Table Isummarizes information about the pre- and post-split prices of the splitting funds aswell as those for the 12 control funds. We report the high, low, mean, median, andstandard deviation of the prices over the sample period for each fund, as well as theaverage for all of the funds. For the overall sample the average pre-split median price is148.73 dollars while the corresponding post-split average median price is 64.44 dollars.

The funds with a split factor of 3.0 have an average pre-split median price of 180dollars while those with a split factor of 2.0 report an average pre-split median price of139 dollars (not shown in the table). For the control sample, median prices range from10.32 dollars for the EWJ to 120.21 for IVV, with an average median price of 71.10dollars. The average pre-split median price of the splitting funds is significantly higherthan the median price for all of the non-splitting funds. These observations pointtoward price reduction as one possible motive for splitting.

Methodology and resultsWe study the impact of the iShares split on measures of liquidity, turnover, and orderimbalance around the split date. These measures allow us to examine the support, ifany, for the broker-promotion hypothesis and/or the trading-inconvenience hypothesis,with regard to the sample and time period under study. Specifically, we analyze thepre- and post-split turnover ratio, relative bid-ask spread, frequency of small trades,average order size, and order imbalance, around the ex-date.

Relative spreadsLiquidity has been extensively discussed in the literature as one of the explanations fora stock split that. Support for liquidity improvement has been presented by Baker andGallagher (1980), which provides survey-type evidence in favor of company managersintentions to improve liquidity through the result of the split and Muscarella andVetsuypens (1996) study, which investigates and provides evidence of improvedliquidity among splitting American Depository Receipts.

We analyze the liquidity effects of the iShare splits in terms of the relative spread,which is defined as:

Sij Aij Bij=Mij

whereAij andBij are the quoted ask and bid prices and Mij is the midpoint of the bid andask prices. We designate the ex-date as Day 0 and report the results for ten days prior toand following the ex-date. We use a similar convention for all subsequent analyses.

Table II presents the results of the spread analysis, reporting the figures for eachiShare fund in our sample, along with the average across all funds for each day. We

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report the t-statistics that test the significance of the difference between the mean of thespread on a given day from the overall mean during the pre-event period. Results in

Panel A show a significant increase in the average relative spread, from 0.151 percenton the day before the ex-date (Day 1) to 0.180 percent on the day of the split (Day 0),with a t-statistic of 8.74. The increase in the relative spread persists throughoutthe post-period, with the only exception occurring on Day 6, when the spread (0.139)is actually lower than the pre-split spread. Panel B of Table II presents the spreadanalysis for the control funds. The average spread for the control group variesrandomly between a minimum of 0.131 percent to a maximum of 0.176 percent. Unlikethe splitting funds, this group displays no consistent pattern over the 21 days.

The result of the relative spread analysis thus fails to reject the broker-promotionhypothesis, implying that splitting a fund provides an incentive for promoting the fund

Table I.Summary price statistics

Pre-split Post-splitLowest Median Highest Mean Std dev. Lowest Median Highest Mean Std dev.

Panel A: Descriptive statistics for split sample

EEM $209.77 $211.25 $211.92 $210.94 0.69 $70.02 $70.25 $70.66 $70.31 0.15EFA 156.85 158.29 158.63 157.94 0.58 52.08 52.22 52.64 52.26 0.13ICF 141.45 142.08 142.65 142.06 0.36 70.50 70.72 71.00 70.73 0.12IGE 143.75 144.71 146.44 144.96 0.85 73.31 73.79 74.08 73.78 0.16IJH 134.75 135.80 136.10 135.58 0.43 67.76 68.00 68.21 68.00 0.10IJJ 130.43 131.46 131.76 131.30 0.39 65.73 65.88 66.08 65.89 0.07IJK 136.94 138.00 138.55 137.82 0.46 68.79 69.05 69.23 69.05 0.09IJR 161.15 162.32 163.05 162.12 0.66 54.00 54.15 54.42 54.16 0.09IJS 120.32 121.36 121.66 121.20 0.39 60.52 60.69 60.96 60.71 0.09IWM 123.25 124.38 124.70 124.07 0.51 62.09 62.25 62.55 62.27 0.09IWN 187.38 187.89 189.18 188.23 0.61 62.90 63.00 63.19 63.02 0.08IYR 126.20 127.28 127.66 127.27 0.28 63.19 63.31 63.60 63.32 0.09

Average 147.69 148.73 149.36 148.62 64.24 64.44 64.72 64.46

Panel B: Descriptive statistics for control groupEWJ $10.25 $10.32 $10.35 $10.30 0.03IVV 119.60 120.21 120.41 120.05 0.29IBB 64.28 64.66 64.95 64.60 0.17IJT 106.63 107.69 108.10 107.46 0.46IVE 61.81 62.13 62.23 62.06 0.13IVW 57.37 57.70 57.88 57.66 0.13IWD 66.59 66.76 67.07 66.81 0.17IWF 48.25 48.42 48.75 48.44 0.12IWO 62.84 63.33 63.62 63.23 0.29IWS 115.58 116.20 116.48 116.13 0.27IYE 73.58 74.76 75.13 74.52 0.47IYH 60.90 61.04 61.62 61.12 0.18

Average $70.64 $71.10 $71.38 $71.03

Notes: This table summarizes information about the pre- and post-split prices of the splittingfunds as well as the two control funds. We report the high, low, mean, median, and standarddeviation of the prices over the sample period for each fund and also the average of thesestatistics for all the funds. The stated goal of the split was to bring the average share price of theETFs in line with the average share price of a US listed security (stock), $42.21 at the time of thesplit. While the average share of the iShare ETFs was still greater than that of the average USlisted security, it was significantly closer than before split

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Table Relative spre

PanelA:Relativespread(%)forsplitsample

Day

EEM

IWN

IJR

EFA

IGE

IJK

IJH

IJJ

IWM

ICF

IJS

IYR

Average

t-stat

10

0.0838

0.1718

0.1361

0.0730

0.2172

0.1630

0.1910

0.1384

0.1097

0.1078

0.2743

0.0988

0.1471

0.65

9

0.0721

0.1074

0.1173

0.0729

0.2945

0.1031

0.1653

0.1156

0.0928

0.1141

0.2533

0.1266

0.1363

2.02

8

0.0753

0.1574

0.1137

0.0818

0.1555

0.1661

0.1066

0.1771

0.0905

0.1638

0.2277

0.1465

0.1385

1.47

7

0.0571

0.1886

0.1365

0.0723

0.2179

0.2825

0.2209

0.1594

0.1182

0.1068

0.2547

0.1254

0.1617

4.27

6

0.0663

0.1273

0.1440

0.0917

0.1882

0.2220

0.1300

0.1733

0.1082

0.1149

0.2276

0.1585

0.1460

0.39

5

0.0631

0.1182

0.1474

0.0965

0.1946

0.2089

0.1800

0.1871

0.1004

0.1128

0.2393

0.1550

0.1503

1.44

4

0.0870

0.0966

0.1737

0.1092

0.1778

0.1690

0.1806

0.1890

0.1229

0.1311

0.2327

0.1011

0.1476

0.77

3

0.0652

0.1128

0.1345

0.0515

0.1812

0.1966

0.2073

0.1763

0.0958

0.1106

0.1839

0.1059

0.1351

2.3

2

0.0620

0.1122

0.1471

0.0835

0.1824

0.1315

0.1573

0.1794

0.0913

0.0891

0.2202

0.1177

0.1311

3.28

1

0.0844

0.1285

0.1421

0.0825

0.2618

0.2217

0.2091

0.1765

0.0776

0.1062

0.2108

0.1075

0.1507

1.55

0

0.1365

0.1164

0.1631

0.1555

0.2387

0.2714

0.2541

0.2141

0.0917

0.1367

0.2195

0.1600

0.180

8.74

1

0.1380

0.1009

0.1905

0.1834

0.2889

0.2865

0.2233

0.2585

0.0553

0.1549

0.2504

0.1763

0.1923

11.81

2

0.0917

0.1068

0.3064

0.1553

0.2258

0.2461

0.2186

0.2649

0.0698

0.1334

0.2537

0.1098

0.1819

9.24

3

0.1278

0.1188

0.1595

0.1069

0.2500

0.2439

0.2254

0.2003

0.0815

0.1491

0.2650

0.1255

0.1711

6.6

4

0.0982

0.1013

0.1502

0.1115

0.2282

0.2911

0.2627

0.2055

0.0721

0.1202

0.2130

0.1289

0.1652

5.14

5

0.0852

0.0924

0.1416

0.1681

0.2210

0.2408

0.2088

0.1125

0.0720

0.1383

0.1926

0.1592

0.1527

2.04

6

0.0946

0.0947

0.1586

0.1037

0.2108

0.2039

0.1378

0.1631

0.0773

0.1284

0.1904

0.1078

0.1393

1.28

7

0.1264

0.0911

0.2106

0.1492

0.2051

0.1963

0.2511

0.1661

0.0757

0.1341

0.2458

0.1221

0.1644

4.94

8

0.0691

0.1284

0.1863

0.1338

0.3472

0.2441

0.1951

0.1650

0.0805

0.1254

0.2139

0.1194

0.1673

5.66

9

0.1043

0.0764

0.1988

0.1778

0.2780

0.2664

0.2931

0.2310

0.0774

0.1395

0.2217

0.1515

0.1847

9.94

10

0.0972

0.1025

0.2259

0.1182

0.2787

0.2741

0.2870

0.2226

0.0717

0.1280

0.2496

0.1409

0.1830

9.53

(continued)

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traded fund

14

to small investors. This post-split increase in spread is consistent with the resultsreported by Kadapakkam et al. (2005), Dennis (2003), Conroy et al. (1990), and Gray et al.(2003). An increase in spreads indicates that the split results in a decrease in aggregateliquidity (i.e. higher spreads mean lower liquidity). We take a closer look at the liquidity

effects when we examine the frequency of small trades and order imbalance.

TurnoverTable III reports changes in volume turnover around the split date. If the trading-inconvenience hypothesis prevails, a post-split increase in small buy orders would resultin an increase in turnover. Turnover is computed in the logarithmic form shown below,which is used to minimize the impact of extreme observations (Kadapakkam et al., 2005):

Turnover 100 log1 Trading Volume=Number of Shares Outstanding:

The average percentage turnover increases from 0.24 percent on Day 1 to 0.58 percenton Day 0 (t-statistic 6.85). The turnover for each day of the post-period remains higher

than the turnover in the days before the split, favoring the trading-inconveniencehypothesis which predicts an increase in turnover due to pre-split lower trading volume.A possible explanation provided in the literature and supported by our evidence is thatinvestors avoid the inconvenience of having to deal with due bills. However, since theanalysis looks at only daily aggregate turnover, we need to specifically look at thefrequency of small trades in order to determine if that contributes to the observedincrease in turnover. Our finding agrees with Dennis (2003), who detects a post-splitincrease in share volume in the Nasdaq-100 index tracking stock.

The control group sample does not display any particular pattern. The averageturnover in the days before the split is about 0.31 percent. Beginning on the ex-date, June6, the turnover appears to decline over the next four days, registering a minimum of 0.20percent. However, the fifth day following the split exhibits a surge in the ratio to 0.58percent. The sixth, seventh, and eighth days register an average of 0.43 percent, afterwhich the ratio drops to an average of 0.28 percent over the last two days. One possibleexplanation for the low turnover immediately following the split is that investorsincrease trading activity in the splitting funds in order to take advantage of the new priceper unit of these funds, and reduce the amount of trading in the non-splitting funds.

Order size and frequency of small tradesIn this section we begin by investigating whether the split causes any changes in theaverage order size. Under the broker-promotion hypothesis the higher spreads shouldmotivate brokers to promote the splitting fund to small investors, resulting in decliningbuy-order size caused by an increase in the number of small trades.

This analysis requires us to classify trades as buy or sell orders. We employ thewidely used algorithm forwarded by Lee and Ready (1991) for this purpose, computingthe dollar-order size as the trade size in shares multiplied by the per-share price. Apost-split decline in average buy-order size indicates more buying by small investors.Table IV summarizes the evidence for the average dollar-order size. Panel A presentsthe results for the buy orders while Panel B presents the sell order results for thesplitting sample. Panels C and D present the control group results for buy and sellorders, respectively.

Panel A shows that the buy-order size declines from a pre-period average of about12,118,000 dollars (with a range from 8,349,000 to 17,049,000) to a post-period average

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Table III.Daily turnover

PanelA:Dailyturnover(%)forsplitsample

Day

EEM

IWN

IJR

EFA

IGE

IJK

IJH

IJJ

IWM

ICF

IJS

IYR

Average

t-stat

10

0.202

0.081

0.087

0.204

0.260

0.062

0.040

0.164

0.438

0.134

0.088

0.555

0.193

1.51

9

0.212

0.052

0.093

0.106

0.221

0.345

0.057

0.108

0.977

0.261

0.125

0.437

0.250

0.29

8

0.146

0.053

0.294

0.102

0.085

0.068

0.058

0.096

0.678

0.128

0.042

0.344

0.175

1.90

7

0.188

0.081

0.246

0.139

0.486

0.072

0.070

0.189

0.651

0.160

0.066

0.875

0.269

0.11

6

0.510

0.544

0.215

0.090

0.725

0.118

0.600

0.133

1.459

0.111

0.132

0.703

0.445

3.88

5

0.193

0.039

0.076

0.047

0.195

0.079

0.138

0.115

0.363

0.124

0.087

0.233

0.141

2.63

4

0.285

0.413

0.077

0.045

0.088

0.124

0.090

0.287

0.699

0.186

0.040

1.404

0.312

1.03

3

0.223

0.322

0.072

0.114

0.417

0.157

0.036

0.290

0.788

0.115

0.086

0.487

0.259

0.09

2

0.398

0.278

0.136

0.107

0.134

0.126

0.526

0.202

0.749

0.226

0.102

1.246

0.352

1.90

1

0.345

0.047

0.086

0.252

0.140

0.076

0.071

0.104

0.618

0.156

0.117

0.868

0.240

0.50

0

0.784

0.164

0.147

0.270

1.522

0.143

0.096

0.197

1.290

0.273

0.855

1.264

0.584

6.86

1

0.326

0.119

0.176

0.509

0.684

0.198

0.063

0.185

1.069

0.296

0.093

0.671

0.366

2.19

2

0.592

0.147

0.108

0.142

0.359

0.157

0.070

0.221

0.995

0.246

0.144

0.971

0.346

1.76

3

0.833

0.205

0.290

0.269

0.606

0.157

0.126

0.179

0.961

0.406

0.190

0.913

0.428

3.52

4

1.189

0.245

0.247

0.260

0.445

0.176

0.105

0.800

2.036

0.293

0.165

1.029

0.582

6.82

5

0.948

0.364

0.366

0.225

0.416

0.202

0.311

1.600

1.623

0.290

0.205

0.626

0.598

7.16

6

1.719

0.204

0.227

0.490

0.522

0.177

0.233

0.730

1.654

0.203

0.265

2.846

0.773

10.89

7

0.701

0.760

0.148

0.209

0.639

0.230

0.115

0.422

2.032

0.157

0.222

0.955

0.549

6.11

8

0.461

0.331

0.194

0.236

0.364

0.188

0.240

0.337

1.103

0.245

0.137

1.864

0.475

4.53

9

0.455

0.596

0.179

0.186

0.889

0.188

0.138

0.251

1.034

0.244

0.144

1.028

0.444

3.87

10

0.791

0.405

0.256

0.254

0.294

0.158

0.120

0.237

1.928

0.361

0.231

1.396

0.536

5.83

(continued)

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traded fund

14

Table IPanelB:Dailyturnover(%)fo

rcontrolgroup

Day

IVV

EWJ

IBB

IWF

IWD

IVW

IVE

IWO

IYE

IYH

IJT

IWS

Average

t-stat

10

0.184

0.235

0.600

0.273

0.100

0.127

0.114

0.308

0.430

0.144

0.304

0.167

0.249

3.26

9

0.148

0.261

0.498

0.295

0.356

0.175

0.153

0.315

0.205

0.309

0.337

0.453

0.292

1.08

8

0.099

0.191

0.675

0.134

0.139

0.472

0.317

0.280

0.142

0.145

0.769

0.384

0.312

0.07

7

0.076

0.245

0.619

0.275

0.292

0.188

0.145

0.203

0.433

0.323

0.297

0.234

0.278

1.81

6

0.110

0.263

0.663

0.255

0.350

0.392

0.140

0.332

0.530

0.475

0.369

0.292

0.348

1.70

5

0.057

0.125

0.846

0.271

0.306

0.499

0.135

0.127

0.272

0.513

0.410

0.472

0.336

1.13

4

0.058

0.222

1.331

0.352

0.305

0.295

0.151

0.182

0.215

0.258

0.334

0.188

0.324

0.53

3

0.045

0.157

1.260

0.344

0.251

0.240

0.252

0.365

0.327

0.235

0.396

0.322

0.350

1.80

2

0.154

0.275

0.755

0.398

0.208

0.122

0.161

0.591

0.484

0.271

0.261

1.057

0.395

4.08

1

0.031

0.174

0.653

0.182

0.141

0.229

0.184

0.190

0.229

0.157

0.266

0.607

0.254

3.02

0

0.047

0.157

0.600

0.189

0.144

0.190

0.268

0.239

0.425

0.144

0.249

0.317

0.247

3.33

1

0.119

0.151

0.397

0.234

0.177

0.143

0.141

0.171

0.337

0.166

0.435

0.134

0.217

4.85

2

0.077

0.228

0.241

0.203

0.117

0.146

0.139

0.174

0.193

0.263

0.244

0.397

0.202

5.62

3

0.063

0.160

0.291

0.413

0.261

0.160

0.185

0.378

0.136

0.136

0.397

0.390

0.248

3.32

4

0.047

0.266

0.454

0.224

0.206

0.140

0.205

0.222

0.254

0.164

0.305

0.542

0.252

3.07

5

0.056

0.116

1.756

0.888

0.129

0.176

0.071

0.517

0.757

0.452

0.706

1.365

0.582

13.51

6

0.060

0.211

1.158

0.242

0.181

0.120

0.139

0.722

0.752

0.454

0.157

1.111

0.442

6.46

7

0.095

0.164

2.304

0.195

0.335

0.134

0.239

0.241

0.608

0.263

0.227

0.480

0.441

6.37

8

0.185

0.192

1.454

0.150

0.477

0.162

0.117

0.350

0.282

0.718

0.272

0.450

0.401

4.37

9

0.114

0.185

0.884

0.238

0.370

0.289

0.070

0.150

0.512

0.173

0.116

0.234

0.278

1.79

10

0.083

0.167

0.691

0.261

0.254

0.201

0.173

0.145

0.573

0.241

0.170

0.573

0.294

0.97

Notes:Thistablereportsch

angesinvolumeturnoveraroundth

esplitdate.Turnoveriscomputedinthelogarithmicformshownbelow

inorderto

minimizetheimpactofextremeobservations

Turnover

100

log1

TradingVolume=NumberofSharesOu

tstanding

Ifthetrading-inconvenienceh

ypothesisprevails,apost-splitincrea

seinsmallbuyorderswouldresultinanincreaseinturnover.Theaverag

epercentage

turnoverforiSharesthatsplit(PanelA)increasesfrom0.24onDay1percentonto0.58percentonDay0(t-statistic6.85).Theturnover

foreachday

ofthepost-periodremainshigherthantheturnoverinthedaysbeforethesplit,thusfavoringthetra

ding-inconveniencehypothesis.Thec

ontrolgroup

funds(PanelB)donotdisplayanyparticularpattern,butfromJune6(theex-date)onwardsexhibitan

overalldeclineintheturnoverratio

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Table IV.Daily order size

PanelA:Averagedollarorder

sizeforbuyorders(in000)

Day

EEM

IWN

IJR

EFA

IGE

IJK

IJH

IJJ

IWM

ICF

IJS

IYR

Average

t-stat

10

10,913

25,496

7,319

36,466

3,771

2,274

4,257

2,740

11,605

5,824

14,814

4,449

10,827

1.54

9

10,949

7,257

8,315

14,448

6,576

5,763

4,918

5,721

38,232

9,160

6,151

4,935

10,202

2.29

8

8,911

4,635

31,068

26,493

2,212

6,522

5,728

5,430

19,450

7,768

1,638

7,831

10,640

1.76

7

9,975

55,300

25,620

22,835

7,755

3,806

6,614

7,374

18,614

9,682

2,859

10,612

15,087

3.55

6

12,214

32,700

10,924

19,828

13,609

5,154

41,827

6,238

39,936

6,585

4,193

11,375

17,049

5.89

5

9,637

8,422

3,771

14,408

6,141

4,092

11,466

4,893

13,952

8,804

3,020

11,579

8,349

4.50

4

22,147

4,3917

5,054

15,089

2,776

3,152

3,162

13,474

26,896

5,916

2,673

12,424

13,057

1.12

3

10,512

29,095

4,667

17,272

22,292

12,635

4,910

6,234

25,049

7,599

6,150

6,436

12,738

0.74

2

20,738

15,350

7,755

8,349

3,741

3,764

46,614

3,892

17,313

1

2,492

4,264

11,320

12,966

1.01

1

17,190

5,000

7,515

48,481

5,059

2,562

7,877

2,729

8,424

6,114

5,136

7,039

10,260

2.22

0

8,737

4,261

2,057

6,797

16,365

1,582

3,192

1,872

8,657

3,777

5,854

5,576

5,727

7.63

1

3,606

4,418

4,894

9,758

4,371

4,201

2,105

3,017

6,243

2,252

1,425

4,504

4,233

9.42

2

8,797

4,564

3,339

4,902

4,276

1,157

3,264

2,227

10,071

5,978

2,047

6,790

4,784

8.76

3

14,594

7,139

5,053

8,427

3,564

2,421

2,618

1,804

14,475

7,965

2,124

4,096

6,190

7.08

4

15,507

2,592

3,747

9,114

3,117

4,501

2,379

12,622

13,928

2,757

2,399

2,896

6,297

6.95

5

10,772

5,295

5,408

5,444

2,101

3,786

2,115

5,938

13,479

5,523

2,477

5,261

5,633

7.74

6

17,635

6,110

2,504

23,369

3,895

2,068

1,839

4,147

16,585

4,489

6,636

5,598

7,906

5.03

7

9,274

12,085

2,370

7,103

7,698

4,683

1,762

3,155

14,662

2,786

2,603

4,199

6,032

7.27

8

5,258

3,763

4,953

8,244

2,122

1,148

2,213

3,866

13,284

3,887

2,178

3,301

4,518

9.07

9

6,963

6,185

7,864

5,222

3,590

1,734

1,653

3,158

11,450

5,389

1,747

3,031

4,832

8.70

10

6,496

7,964

5,738

7,399

3,622

2,590

4,058

2,157

11,018

4,846

2,826

4,708

5,285

8.16

(continued)

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traded fund

14

Table IPanelB:Averagedollarorder

sizeforsellorders(in000)

Day

EEM

IWN

IJR

EFA

IGE

IJK

IJH

IJJ

IWM

ICF

IJS

IYR

Average

t-stat

10

16,945

9,803

9,373

25,601

12,289

7,680

2,711

5,720

16,342

5,982

2,808

12,033

10,607

1.55

9

12,266

6,843

7,078

31,421

2,174

10,569

3,515

2,669

23,333

18,214

2,558

5,968

10,550

1.62

8

9,213

15,891

10,529

26,964

2,825

3,063

3,836

6,444

12,732

12,734

3,919

10,684

9,903

2.39

7

9,678

7,149

17,515

29,464

13,418

7,011

4,172

5,633

18,287

9,250

4,165

13,067

11,567

0.41

6

21,186

37,230

11,213

15,568

31,136

2,565

77,694

3,741

23,966

5,078

3,847

11,539

20,397

10.11

5

8,990

6,966

12,892

8,043

7,999

2,761

8,124

6,421

9,732

6,663

7,309

6,863

7,730

4.97

4

14,689

10,915

13,099

12,602

1,857

6,194

10,889

3,989

11,290

9,368

2,831

13,291

9,251

3.16

3

17,258

15,391

8,310

22,373

4,407

5,229

3,114

7,064

16,484

4,242

2,187

11,938

9,833

2.47

2

15,777

26,726

15,409

51,852

3,265

5,545

26,751

5,385

19,174

26,016

3,231

12,594

17,644

6.83

1

29,073

7,776

7,544

49,702

3,258

6,662

4,494

3,693

9,567

6,508

4,321

6,552

11,596

0.37

0

16,300

3,614

3,254

20,631

1,092

5,328

1,988

3,534

9,871

4,768

11,438

10,053

7,656

5.06

1

4,988

5,917

2,623

34,165

4,337

3,037

1,914

3,868

8,667

9,028

2,178

3,792

7,043

5.79

2

6,567

9,470

3,156

8,090

3,760

3,522

2,165

3,182

7,986

4,596

2,935

4,243

4,973

8.26

3

10,325

8,085

11,287

13,009

9,461

2,404

4,241

3,067

8,854

3,367

2,873

2,721

6,641

6.27

4

13,575

5,090

2,787

7,686

2,431

9,46

2,756

3,908

14,489

4,367

4,238

2,311

5,382

7.77

5

7,693

9,975

5,557

8,626

4,919

7,366

2,338

8,872

12,464

2,955

3,070

4,466

6,525

6.41

6

20,290

8,023

3,374

22,947

3,512

4,058

2,642

5,246

12,218

4,712

3,820

5,850

8,058

4.58

7

14,514

13,836

3,668

9,505

2,117

4,573

2,617

3,391

18,014

3,000

6,223

3,572

7,086

5.74

8

6,110

3,952

2,445

12,495

1,843

6,680

5,222

2,934

9,697

5,472

1,983

6,093

5,411

7.73

9

5,057

18,960

3,373

18,183

8,470

3,639

4,828

3,074

12,616

4,721

2,429

3,198

7,379

5.39

10

10,574

7,788

3,500

8,747

2,471

4,811

2,825

3,074

16,353

13,667

6,170

3,801

6,982

5.86

(continued)

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MF36,2

148

Table IV.PanelC:Averagedollarorder

sizeforbuyordersforcontrolgroup

(in000)

Day

IVV

EWJ

IBB

IWF

IWD

IVW

IVE

IWO

IYE

IYH

IJT

IWS

Average

t-stat

10

12,490

2,797

11,569

3,000

4,791

2,343

1,434

9,083

3,166

3,810

3,807

4,329

5,218

0.93

9

21,267

3,675

3,198

8,700

9,756

3,090

2,577

5,754

1,984

4,722

3,308

12,507

6,711

5.99

8

3,681

2,983

6,941

4,431

4,829

9,349

1,844

8,479

1,211

1,412

8,541

3,081

4,732

0.72

7

5,035

1,771

4,819

3,945

4,532

2,034

2,538

4,266

3,126

4,642

3,454

8,732

4,075

2.95

6

3,975

6,450

3,782

2,500

7,366

2,028

4,227

3,110

4,628

4,833

2,279

8,160

4,445

1.69

5

4,605

2,012

4,280

9,323

6,384

4,092

1,816

5,487

2,532

2,260

4,287

9,065

4,679

0.90

4

4,361

3,280

8,188

7,185

3,560

1,847

1,675

3,789

2,743

5,347

3,831

5,926

4,311

2.15

3

6,808

2,984

7,380

2,103

3,886

3,602

5,716

2,662

2,436

5,354

4,749

13,749

5,119

0.59

2

13,138

4,934

5,558

4,461

8,330

1,889

4,681

12,539

3,653

2,682

2,765

10,740

6,281

4.53

1

3,273

4,040

5,992

2,719

6,632

2,213

3,038

6,594

2,100

1,139

2,460

6,320

3,877

3.62

0

5,522

4,230

5,062

5,831

4,125

1,609

6,234

5,486

2,726

2,069

3,288

11,017

4,767

0.60

1

5,807

3,024

3,163

4,362

7,163

2,315

2,106

3,408

3,107

3,772

2,739

4,698

3,805

3.86

2

17,361

6,285

2,843

2,082

2,584

2,376

1,478

4,026

1,802

3,055

1,851

9,428

4,598

1.18

3

4,551

2,545

1,394

14,847

5,205

1,489

1,899

9,371

1,529

2,864

4,635

6,997

4,777

0.57

4

7,386

6,421

2,530

4,658

5,286

2,508

6,766

4,552

2,133

3,896

3,613

36,653

7,200

7.65

5

5,995

777

6,615

23,542

3,428

4,173

2,066

4,738

2,241

5,019

4,614

8,314

5,960

3.44

6

7,728

3,847

6,061

4,181

5,014

3,362

3,024

10,632

3,275

6,074

2,104

12,281

5,632

2.33

7

8,540

4,324

7,111

2,943

4,873

3,908

7,692

6,073

2,483

2,260

3,618

7,233

5,088

0.49

8

7,294

3,666

3,351

3,317

8,231

3,539

3,108

3,709

1,390

1

3,490

2,587

7,718

5,117

0.58

9

7,281

7,084

2,848

5,006

5,575

2,377

1,764

6,649

2,028

1,792

1,957

6,974

4,278

2.26

10

7,424

3,322

3,602

2,599

11,056

4,094

2,957

3,408

2,311

2,981

3,120

24,964

5,987

3.53

(continued)

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MF36,2

150

value of about 5,585,000 dollars (with a range from 4,233,000 to 7,906,000). This resultis consistent with the broker-promotion explanation of increased broker incentive topromote the splitting stock to small investors in order to take advantage of the widerspreads. However, from Panel B we also note a decrease in the sell-order size that

declines from a pre-slit average of 11,908,000 dollars (with a range of 7,730,000-20,397,000) to a post-split average of 6,649,000 dollars (with a range of 4,973,000-8,058,000). The t-statistics remain significant over the entire post-split period. Since thebroker-promotion hypothesis makes no prediction regarding a decline in sell-order size,there could be other factors influencing trading patterns around splits. A similarobservation is noted by Kadapakkam et al. (2005).

This evidence appears to be consistent with Ohlson and Penmans (1985) discussionof a post-split increase in the number of noise traders. They attribute this clientelefactor (advanced by Black, 1986) to the lower post-split price. Evidence of an increasein return volatility, and hence uninformed trading following a stock split, has beenprovided by Ohlson and Penman (1985), Conroy et al. (1990), and Dubofsky (1991).

The fact that we observe declines in order size on both the buy and sell side could

be an indication of increased noise trading, which securely rules out any informationeffect of the split.

While information or signaling should not be an issue in the ETF market, recentarticles in the Wall Street Journaldiscuss a crucial shift in the behavior pattern of thesesecurities. Some current trends reveal new risks, unexpected results, and seriousperformance deviations from the respective benchmarks. Given such discrepancies, theresults from our analysis do not necessarily indicate any contrarian behavior in oursample.

The buy and sell order size for the control group does not follow the decliningexample of the splitting sample. The buy order size varies randomly between aminimum value of 3,805,000 dollars and a maximum of 7,200,000 dollars. The averageover the sample period is about 5,079,000 dollars. The sell side numbers are generallyhigher than the buy side. The minimum sell order size is 3,948,000 dollars while themaximum is 9,070,000 dollars, and the average over the sample period is about5,514,000 dollars.

We next examine possible changes in trading patterns around the ex-date of thesplit from the perspective of the frequency of small trades. We follow Kadapakkam et al.(2005) in computing the frequency of small trades before and after the event on a split-adjusted basis. For example, for a two-for-one split, we compare the frequency of one-lot trades before the split with the cumulative frequency of one- and two-lot trades afterthe split. An increase in the post-split frequency of small trades would corroborate theevidence provided by the buy-order size in the previous section and lend furthersupport to the broker-promotion hypothesis.

Table V reports the results for the analysis of the frequency of small trades. We notea post-split increase in the percentage of small trades. The ex postaverage frequency ofsmall trades increases to about 61.5 percent (ranging from 57.4 to 65.0 percent), from anex ante average of about 45.4 percent (ranging from 41.0 to 48.3 percent). This evidencefurther substantiates our results on the post-event decline in buy-order size. Clearly,both these findings lend support to the broker-promotion hypothesis.

Transaction price placement and order imbalanceTo examine the effect of order flow around the ex-date we analyze two variables, thetrade-price location parameter and order imbalance. First, we examine the trade-price

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traded fund

15

Table Frequency of sp

adjusted small trad(in perce

Day

EEM

IWN

IJR

EFA

IGE

IJK

IJH

IJJ

IWM

ICF

IJS

IYR

Average

t-stat

10

32.806

59.574

55.046

22.910

52.459

45.71

4

64.706

45.370

50.281

40.260

42.857

37.179

45.764

0.22

9

45.541

74.510

33.333

37.358

48.485

30.70

2

63.235

50.549

47.917

43.210

49.231

43.979

47.338

1.06

8

53.208

52.000

41.259

28.796

51.351

48.14

8

39.344

42.857

42.418

40.909

56.522

34.043

44.238

0.60

7

41.503

31.034

36.154

27.737

38.596

50.00

0

42.857

41.284

38.043

49.254

54.167

41.799

41.036

2.32

6

47.030

85.044

25.238

30.483

41.071

53.24

7

46.377

41.739

40.351

39.437

39.560

48.630

44.851

0.27

5

49.718

85.393

42.424

35.204

34.286

52.50

0

43.478

42.169

47.575

38.710

52.542

34.328

46.527

0.63

4

30.233

84.025

38.158

35.366

58.824

41.50

9

56.364

44.371

45.372

50.000

40.909

16.732

45.155

0.11

3

35.503

78.226

50.427

39.818

36.170

38.00

0

58.000

42.949

58.299

60.759

45.455

36.232

48.320

1.59

2

30.667

72.414

42.105

41.667

47.059

45.33

3

37.662

41.772

49.783

40.000

37.037

28.521

42.835

1.36

1

31.200

79.787

41.667

28.309

53.061

52.08

3

50.000

56.140

50.000

40.816

45.570

42.038

47.556

1.18

0

58.876

76.316

75.419

57.026

75.325

76.11

9

65.882

52.206

69.515

58.772

28.395

52.679

62.211

9.04

1

71.394

71.186

74.233

54.377

69.388

74.66

7

67.073

51.042

77.760

53.571

64.286

50.980

64.996

10.54

2

50.114

75.556

63.415

65.333

56.250

79.16

7

69.841

61.146

63.092

54.545

62.745

57.143

63.196

9.57

3

57.895

81.197

67.669

57.447

61.111

64.63

4

53.846

65.217

53.537

43.860

63.704

56.150

60.522

8.14

4

52.802

89.547

71.250

64.348

73.684

70.17

5

61.458

54.217

45.281

59.690

51.765

75.042

64.105

10.06

5

52.545

71.429

61.345

56.000

67.368

66.66

7

60.870

48.872

52.875

52.174

61.157

77.477

60.732

8.25

6

38.131

86.636

67.249

55.457

66.337

62.33

8

68.263

56.452

45.308

53.846

59.091

61.911

60.085

7.90

7

48.034

71.186

58.108

57.477

61.111

58.46

2

61.250

61.307

41.463

64.130

51.852

54.006

57.365

6.44

8

51.168

56.534

67.526

55.689

82.069

81.69

0

59.420

60.116

40.995

47.727

54.717

42.357

58.334

6.96

9

63.861

93.294

64.063

60.160

52.336

64.55

7

65.556

54.610

43.689

60.952

60.000

50.195

61.106

8.45

10

49.367

93.400

66.000

52.147

73.239

60.65

6

52.577

68.817

43.646

52.475

71.429

75.883

63.303

9.63

Notes:Thistablesummarizesthefrequencyofsmalltradesbefor

eandafterthesplit,followingKadap

akkametal.(2005)incomputingthe

frequencyof

smalltradesbeforeandaftertheeventonasplit-adjustedbasis.

Anincreaseinthepost-splitfrequencyofsmalltradeswouldcorroborate

theevidence

providedbythebuy-ordersizeintheprevioustableandlendfurthersupporttothebroker-promotionhypothesis

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152

location parameter (Lij) as defined by Keim (1989).Lij for firm iat timej is defined as

Lij Pij Bij=Aij Bij

where Pij is the transaction price, and Bij and Aij are the prevailing bid and ask prices,respectively. A value ofLij between 0.5 and 1 indicates a trade that occurred at or nearthe ask quote and a value between 0 and 0.5 indicates a trade that occurred at or nearthe bid quote. Thus, on any given day a location parameter greater than 0.5 indicatesmore trades nearer the ask price (i.e. more buy orders) which we would expect underthe broker-promotion hypothesis. Conversely, a trade location parameter less than 0.5(i.e. more sell orders) implies a deficiency of buy orders, perhaps owing to theinconvenience of dealing with due bills attached to splits, as suggested by the trading-inconvenience hypothesis.

Table VI shows the placement of the trade price within the bid-ask spread. Panel Apresents the results for the splitting sample of iShares. The average value of the locationparameter on the ex-date is 0.58 (t-statistic of 6.64) which is significantly higher than the

previous days average of 0.47. This indicates a significantly greater number of buyorders on the ex-date. However, on subsequent days we observe no consistent pattern forthe position of the location parameter. The pre- and post-event averages are close to 0.5(about 0.52 and 0.51, respectively) indicating the absence of buying or selling pressure.Thus the evidence does not appear to support either of the two hypotheses.

Panel B presents the results of the control group. Similar to the splitting sample,there appears to be a surge in buy orders, 0.58 (t-statistic of 7.95), on the day of the split.This is a significant increase from the previous days location parameter, 0.43. Apartfrom this, there is no consistent pattern in the variation of buy and sell orders.

Next, we investigate whether the split affects order imbalance. Order imbalancemeasures the difference between the number of buy orders and the number of sellorders as a percentage of the total buy and sell orders. It is defined by

OIMij NBUYij NSELLij=NBUYij NSELLij

where NBUYij and NSELLij represent the number of orders to brokers to buy or sell theiShare ion a given day j. A positive value for OIMij indicates a greater number of buyorders than sell orders and would be considered evidence favoring the broker-promotion hypothesis.

Table VII presents the results for the analysis of order imbalance. Our findingsparallel those from the analysis using the location parameter. For the splitting sampleshown in Panel A we note a positive OIM on Day 0 of 0.27, which is significantly higher(t-statictic 7.51) than the pre-split average on Day 1 of about 0.12. This

demonstrates a tendency for trades on Day 0 to execute near the ask price, which isindicative of more buy orders. This observation corresponds to our findings for thelocation parameter. However, this effect dissipates over Day 1 which records anapproximate average of0.12 indicating a reversion to more sell orders. Consequently,we do not document any consistent pattern of either buying or selling tendencies. Thusthe evidence from the order-imbalance analysis is unable to provide support for eitherhypothesis.

Panel B shows the results for the control group of funds. Similar to the results of thesplitting sample, we note a switch from sell orders on Day 1 (an average of 0.18with a t-statistic of 9.2), to buy orders on Day 0 (an average of 0.18 with a t-statistic of

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traded fund

15

Table VPlacement of transactiprice within the bid-a

sprePanelA:Averagelocationparameterforsplitsample

Day

EEM

IWN

IJR

EFA

IGE

IJK

IJH

IJJ

IWM

ICF

IJS

IYR

Average

t-stat

10

0.458

0.359

0.369

0.756

0.563

0.581

0.544

0.227

0.436

0.428

0.382

0.494

0.466

6.12

9

0.620

0.538

0.594

0.621

0.462

0.839

0.626

0.587

0.377

0.493

0.675

0.609

0.587

7.83

8

0.643

0.434

0.521

0.621

0.748

0.601

0.530

0.420

0.443

0.577

0.581

0.682

0.567

5.51

7

0.599

0.427

0.490

0.655

0.223

0.530

0.529

0.585

0.577

0.514

0.564

0.581

0.523

0.43

6

0.656

0.596

0.432

0.460

0.505

0.318

0.594

0.409

0.635

0.606

0.435

0.525

0.514

0.56

5

0.699

0.593

0.452

0.710

0.334

0.539

0.656

0.471

0.400

0.478

0.631

0.319

0.524

0.51

4

0.466

0.333

0.374

0.485

0.682

0.249

0.455

0.353

0.392

0.647

0.676

0.647

0.480

4.56

3

0.795

0.230

0.514

0.631

0.516

0.246

0.612

0.489

0.357

0.615

0.647

0.565

0.518

0.13

2

0.523

0.483

0.620

0.597

0.534

0.621

0.532

0.500

0.316

0.538

0.689

0.542

0.541

2.55

1

0.528

0.425

0.457

0.451

0.440

0.568

0.435

0.544

0.468

0.365

0.537

0.448

0.472

5.45

0

0.630

0.530

0.555

0.706

0.765

0.588

0.476

0.490

0.536

0.574

0.490

0.576

0.576

6.64

1

0.563

0.381

0.654

0.431

0.536

0.413

0.429

0.372

0.373

0.508

0.454

0.472

0.466

6.22

2

0.480

0.389

0.470

0.580

0.529

0.246

0.350

0.661

0.480

0.331

0.565

0.690

0.481

4.43

3

0.637

0.464

0.489

0.656

0.462

0.344

0.298

0.547

0.430

0.620

0.801

0.753

0.542

2.63

4

0.679

0.165

0.624

0.681

0.474

0.655

0.486

0.715

0.453

0.491

0.662

0.381

0.539

2.29

5

0.642

0.552

0.566

0.468

0.623

0.703

0.456

0.586

0.346

0.442

0.784

0.591

0.563

5.13

6

0.830

0.568

0.393

0.726

0.416

0.368

0.538

0.319

0.415

0.498

0.354

0.365

0.483

4.24

7

0.573

0.502

0.360

0.513

0.640

0.448

0.353

0.397

0.505

0.480

0.513

0.360

0.470

5.66

8

0.718

0.276

0.477

0.655

0.342

0.509

0.498

0.568

0.433

0.330

0.216

0.539

0.463

6.48

9

0.740

0.769

0.448

0.596

0.393

0.402

0.351

0.692

0.476

0.485

0.315

0.566

0.519

0.03

10

0.554

0.553

0.412

0.608

0.436

0.488

0.379

0.517

0.443

0.500

0.733

0.302

0.494

2.94

(continued)

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traded fund

15

Table VOrder imbalan

PanelA:Averageorderimbalanceforsplitsample

Day

EEM

IWN

IJR

EFA

IGE

IJK

IJH

IJJ

IWM

ICF

IJS

IYR

Avera

ge

t-stat

10

0.080

0.231

0.087

0.595

0.133

0.18

8

0.143

0.567

0.162

0.360

0.667

0.026

0.093

6.04

9

0.286

0.030

0.242

0.269

0.107

0.82

7

0.397

0.333

0.193

0.089

0.619

0.118

0.228

5.87

8

0.239

0.250

0.065

0.272

0.929

0.38

5

0.375

0.236

0.088

0.436

0.289

0.413

0.236

6.16

7

0.074

0.481

0.072

0.271

0.370

0.18

8

0.053

0.269

0.149

0.169

0.304

0.191

0.062

0.28

6

0.330

0.215

0.133

0.094

0.137

0.08

8

0.390

0.212

0.299

0.391

0.047

0.269

0.122

1.93

5

0.426

0.282

0.043

0.421

0.515

0.56

8

0.545

0.073

0.213

0.123

0.280

0.375

0.138

2.54

4

0.049

0.224

0.360

0.130

0.548

0.46

2

0.434

0.270

0.221

0.248

0.317

0.287

0.062

4.89

3

0.620

0.497

0.310

0.304

0.048

0.29

2

0.395

0.074

0.281

0.342

0.389

0.254

0.131

2.28

2

0.022

0.061

0.292

0.152

0.143

0.31

5

0.013

0.200

0.343

0.156

0.333

0.121

0.055

0.54

1

0.059

0.033

0.333

0.146

0.167

0.21

7

0.344

0.143

0.084

0.362

0.120

0.159

0.121

7.04

0

0.309

0.138

0.251

0.501

0.684

0.19

3

0.525

0.076

0.048

0.303

0.139

0.248

0.272

7.51

1

0.087

0.273

0.156

0.114

0.075

0.26

8

0.210

0.250

0.279

0.050

0.147

0.108

0.115

6.83

2

0.121

0.036

0.119

0.305

0.194

0.46

3

0.258

0.461

0.064

0.233

0.060

0.413

0.005

2.38

3

0.396

0.269

0.039

0.392

0.270

0.31

5

0.341

0.368

0.215

0.413

0.712

0.632

0.174

3.86

4

0.404

0.735

0.420

0.438

0.011

0.53

2

0.136

0.379

0.189

0.089

0.375

0.260

0.111

1.53

5

0.295

0.069

0.221

0.101

0.444

0.63

0

0.156

0.213

0.383

0.046

0.508

0.227

0.160

3.36

6

0.667

0.106

0.300

0.514

0.179

0.17

8

0.013

0.446

0.232

0.147

0.326

0.304

0.045

4.25

7

0.144

0.018

0.343

0.017

0.045

0.12

7

0.304

0.122

0.002

0.011

0.158

0.276

0.065

4.97

8

0.483

0.634

0.043

0.430

0.479

0.12

5

0.129

0.059

0.138

0.205

0.402

0.055

0.073

5.28

9

0.504

0.467

0.169

0.244

0.019

0.34

3

0.341

0.243

0.015

0.051

0.290

0.064

0.024

1.67

10

0.067

0.163

0.031

0.231

0.029

0.19

2

0.417

0.103

0.115

0.082

0.273

0.527

0.050

4.42

(continued)

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5.2). Apart from this, the prevalence of buy or sell orders on a given trading day doesnot exhibit any consistent trend.

A possible explanation for the observation in the splitting fund sample may lie inthe fact that a split is an anticipated event. Brooks et al. (2003) provide an explanation

for this phenomenon in their investigation of anticipated vs unanticipated events.

ConclusionsStudying the effects of share splits for 12 iShare ETFs issued by Barclay GlobalInvestors, we examine the two hypotheses that have been advanced for the pattern oftrade-and-quote price and activity behavior surrounding stock share splits. The broker-promotion hypothesis suggests that brokers will influence their small investors to delaypurchasing shares until after a split in order to profit from the increased bid-ask spreadsarising from the split. The trading-inconvenience hypothesis entails reluctance ofinvestors to deal with due bills, resulting in postponing purchases until after the ex-date.

We find that there are increases in spreads and frequency of small trades and the

decrease in average trade size experienced by the split iShares that are consistent withthe broker-promotion hypothesis, while there is a significant increase in daily turnoverafter the split that is consistent with the trading-inconvenience hypothesis. Neitherhypothesis is supported by the trade-price location parameter or by trade imbalance inthe post-split period. This suggests that stock splits, being anticipated events, allowmarket makers and small investors to be able to predict order flows and adjust theirpositions accordingly. Overall, we conclude that there is more support for the broker-promotion hypothesis than for the trading-inconvenience hypothesis in the iShare split.

Notes

1. As of 2005 global ETF assets grew 35 percent to about US $417 billion. The year 2005saw the introduction of 119 funds, 53 more than the previous year (Source: Financial

Post, February 20, 2006).2. We repeat the analysis for 60-day pre- and post-periods. Since results remain unchanged

we report only results of the ten-day periods for conciseness.

References

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Appendix 1. The iShares funds that split in June 2005Table AI is a list of the iShare funds that split in June 2005, and the number of shares that wereexchanged after the split for each share that existed before the split. All of the splitting fundswere traded on the American Stock Exchange.

Table AI.

Fund name Ticker Split factor

iShares MSCI Emerging Markets Index Fund EEM 3.0iShares Russell 2000 Value Index Fund IWN 3.0

iShares S&P SmallCap 600 Index Fund IJR 3.0iShares MSCI EAFE Index Fund IFA 3.0iShares Goldman Sachs Natural Resources Index Fund IGE 2.0iShares S&P MidCap 400/BARRA Growth Index Fund IJK 2.0iShares S&P MidCap 400 Index Fund IJH 2.0iShares S&P 400/BARRA Value Index Fund IJJ 2.0iShares Russell 2000 Index Fund IWM 2.0iShares Cohen & Steers Realty Majors Index Fund ICF 2.0iShares S&P SmallCap 600/BARRA Value Index Fund IJS 2.0iShares Dow Jones US Real Estate Fund IYR 2.0

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Appendix 2. iShares funds that did not split in June 2005

Table AII is a list of iShare funds that did split in June 2005, used as a control group to insure thatthe effects attributed to the splitting of the funds were not, in fact, the result of some other

economic event that affected all iShare funds.

Corresponding authorPia Bandyopadhyay can be contacted at: [email protected]

Table A

Fund name Ticker

iShare MSCI Japan Index EWJiShare S&P 500 Index IVViShare Nasdaq Biotechnology IBBiShare SPSC600 Growth Index IJTiShare SP 500 Value Index IVEiShare SP 500 Growth Index IVWiShare Russell 1000 Value Index IWDiShare Russell 1000 Growth Index IWFiShare Russell 2000 Growth Index IWOiShare RusseIl MidCap Value Index IWS

iShare Dow Jones US Energy IYEiShares Dow Jones US Health Care IYH

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