Brokerage Commissions and Institutional Trading Patterns

Transcription

1 rokerage Commiion and Intitutional Trading Pattern Michael Goldtein abon College Paul Irvine Emory Univerity Eugene Kandel Hebrew Univerity and Zvi Wiener Hebrew Univerity June 00 btract Why do broker charge per hare commiion to intitutional trader? What determine the commiion charge? The choice of per hare commiion a a payment method i puzzling, a commiion are not the mot natural way to charge for order execution becaue cot are not proportional to the trade ize and commiion are uppoed to deter trading. We contend that commiion, rather than repreenting a per hare price of execution, contitute a convenient way of charging fixed fee for broker ervice. We develop a imple theoretical model of how broker chooe to allocate ervice to their client. We claim that client payment are tructured in the form of commiion for convenience and regulatory reaon; however, it i the total payment that determine a client level of ervice from their broker. Client adjut the order flow routed to a particular broker and the per-hare commiion to maintain the required payment for their deired level of ervice. Uing a large data et of intitutional trade, we invetigate the ditribution of intitutional commiion analyze commiion by client and broker attribute. We find reult that are conitent with our view of the commiion contract. Preliminary verion. We would like to thank bel Noer for providing the data. We alo thank Cheter Spatt, Ekkehart oehmer and the participant in the 00 New York Stock Exchange conference for their helpful comment. We apologize for the error remaining in thi draft.

2 rokerage Commiion and Intitutional Trading Pattern btract Why do broker charge per hare commiion to intitutional trader? What determine the commiion charge? The choice of per hare commiion a a payment method i puzzling, a commiion are not the mot natural way to charge for order execution becaue cot are not proportional to the trade ize and commiion are uppoed to deter trading. We contend that commiion, rather than repreenting a per hare price of execution, contitute a convenient way of charging fixed fee for broker ervice. We develop a imple theoretical model of how broker chooe to allocate ervice to their client. We claim that client payment are tructured in the form of commiion for convenience and regulatory reaon; however, it i the total payment that determine a client level of ervice from their broker. Client adjut the order flow routed to a particular broker and the per-hare commiion to maintain the required payment for their deired level of ervice. Uing a large data et of intitutional trade, we invetigate the ditribution of intitutional commiion analyze commiion by client and broker attribute. We find reult that are conitent with our view of the commiion contract.

3 I kept my buy rating, but I told my favorite invetor to ell -anonymou ell-ide analyt quoted in uine Week 3/0/000.. Introduction Why do broker charge per hare commiion for execution of intitutional trade? The choice of per hare commiion a a payment method i puzzling, a they are not the mot natural way to charge for order execution. per-hare commiion i not driven by marginal cot conideration becaue execution cot are not proportional to the trade ize, and a a tranaction cot, commiion are uppoed to deter trading. We contend that commiion, rather than repreenting a per hare price of execution, contitute a convenient way of charging fixed fee for broker ervice provided to intitutional client. Thee ervice include difficult order execution, acce to initial public offering and information proviion. We aume that intitution prefer to hide their trading trategie from the market. Conequently, in the abence of other conideration, intitution would like to dipere their total trading volume rather widely among many broker. Empirically, however, we find that thi conjecture doe not hold. Uing a proprietary data et of intitutional trade we report that intitution concentrate the bulk of their trading with a mall fraction of the broker they deal with. The larget client in our data ue an average of 78 broker, but execute 47.6 percent of their trade with their top five broker. Smaller intitution concentrate their trade even more. The mallet intitution in our data execute 75.3 percent of their trade with their top five broker. We refer to thi phenomenon a the bunching of intitutional trading. We develop a model of the broker-client contract where the broker provide a higher level of ervice to client that provide them with the greatet total revenue. What make the implication of the model intereting i the fact that there i a fixed upply of valuable broker ervice uch a acce to ell-ide analyt information or IPO acce. roker allocate thee ervice baed on the total revenue provided by the client. The See for example, mihud and Mendelon (986), Contantinide (986), Vayano (998), and arclay, Kandel, and Marx (998). 3

4 larget intitution uch a idelity Invetment provide enough total revenue to receive a high level of ervice from many broker. ut mot intitution are faced with the deciion to trade off the benefit of hiding their trading trategy by trading with many broker againt the benefit of concentrating their trading with a mall et of broker; becoming important client to thee broker. The maller the intitution, the more they mut concentrate their trade. The model outline the condition under which a bunching equilibrium can exit and provide analytical olution for the equilibrium for a imple tatic example. In our framework, per hare commiion are jut a convenient way of determining the broker total revenue. The implication of the model are teted by examining intitutional trading at the time when the broker ell-ide analyt information i likely to be particularly valuable; when they change their recommendation (Elton, Gruber and Groman, 986; Womack, 996). Section outline our view of the per-hare commiion contract a a vehicle to account for the broker total revenue from a client. Section 3 decribe the model. Section 4 dicue the empirical tet and ection 5 conclude.. The commiion contract rennan and Chordia (993) model per hare commiion a an optimal rikharing contract. In their model, broker wih to ell information to client but the value of the information to the client i uncertain ex-ante. a olution to thi problem rennan and Chordia (993) potulate that the le rik-avere broker give the information away to the more rik-avere client. If, ex-pot, the information i ueful to the client, the reulting trade reward the broker through commiion dollar. However, thi explanation i unlikely to explain intitutional commiion contract. In the abence of forcing contract, the high cot of monitoring every client trade make it eay for client to cheat and execute the trade with the cheapet available provider of execution ervice, uch a dicount broker. Moreover, thi argument i unlikely to apply to 4

5 intitution: optimal rik haring may actually involve a large intitution bearing mot of the rik. Thu, the quetion a to why broker charge per hare commiion, particularly to intitution, remain an open one. Perhap one can view commiion a a linear incentive contract. In many principal-agent environment, the principal pay a commiion baed on performance meaure that inform him ex-pot of the effort being exerted by the agent ex-ante (Holmtrom 979). Linear contract are optimal in ituation where effort i multidimenional and contract are long-lived (Holmtrom and Milgrom 987). However, the incentive proviion i unlikely to be the explanation for commiion contract, ince the tranaction ize i determined olely by the principal (client) and i unlikely to erve a a performance meaure of the agent (broker). Linear contract are ued a payment for ervice when the impact of thee ervice i hard to quantify, and thu hard to bae on an objective performance meaure: one example i advertiing. In thee cae, payment are baed on an eaily meaurable variable that i under the full control of the client, o that the client determine the total payment. Then the agent chooe the quality of the ervice and the client chooe the amount he pay for it. Thee two trategy choice mut be optimal in equilibrium. Thi concept i very imilar to the product quality aurance argument of Klein, Crawford, and lchian (983). In their paper, the equilibrium i uch that a firm price the product above it marginal cot, while maintaining high quality. People are willing to overpay (relative to cheaper competitor), a long a the quality i above ome predetermined level. The firm ha no incentive to ave on quality proviion, ince it will ruin the tream of poitive profit for the future. We contend that if the level of broker ervice replace product quality, the intitutional commiion contract fit nicely into the Klein, Crawford, and lchian (983) framework. Equilibrium in thi framework enure that full ervice broker provide the required level of ervice, and eliminate the poibility in the rennan and Chordia (993) olution that client could free ride on the broker ervice. In thi 5

6 framework commiion repreent a imple and convenient way to pay for ervice provided by the broker. Such ervice include baic execution ervice, execution ervice for more difficult trade, information proviion, and acce to IPO underwritten by the broker. aic execution i a commodity, thu mut be competitively priced. Dicount broker and electronic network (ECN) dominate the market for baic execution. Thi market i highly competitive: commiion in thi market are - cent per hare. In many cae intitution can even get even cheaper fixed-fee execution. or other trade, the potential price impact i greater and the quality of execution depend on the amount of reource, uch a the capital committed or trader earch cot, the broker expend on execution. The broker inherent quality, the kill of the trading dek, could alo affect execution quality. Conequently, thi egment of the indutry provide a differentiated ervice, in a le competitive environment. While meaure of execution quality are available (we will ue ome of them), thee meaure rely on aumption about the trading environment, which can be diputed by the partie. Information quality i even more difficult to define. On one hand, information quality certainly depend on the analyt talent, for which the broker mut pay the ongoing market rate. However, once the analyt work for the broker, the cot of generating information and diipating it i mall. On the urface it would appear that information i a public good, and thu no ingle individual would be willing to pay enough for it generation. Thi impreion, however, i mileading. rom any ingle client perpective, the value of information he receive crucially depend on the timing of it tranmiion from the broker. Since information i upplied equentially, not all client are called at the ame time. a reult, the broker ha dicretion on whom to call firt. In financial market, information i mot valuable to thoe who receive it the earliet. Indeed, ince price adjut to reflect information imbedded in trade (ee Gloten and Milgrom (985), Kyle (985), Ealey and O Hara (987)), information loe it value upon receipt by additional market participant (Kyle 985). Thu, the carce 6

7 reource in thi context i the client place in the queue: the client who i called firt by the broker get the mot valuable information, and hould be willing to pay more for getting it. cce to IPO can be viewed in thi context a a imple rebate program. Larger client get larger allocation of better IPO, and ince thee uually yield ignificant hort-term return, larger client get larger reward. While broker could charge each client explicitly for the carce reource utilized in hi providing thee ervice, thi might not be the mot efficient contract. an alternative, we preent a tatic model of broker ervice, uch a information proviion, in which broker compete for client by etting explicit fee for place in the queue, while client optimally elf-elect. We how that in equilibrium client who value information the mot, get it firt, thu the equilibrium i efficient. The efficient olution doe not, however, explain why commiion dominate the payment of a lump-um fee for a place in the queue for information. There are fixed fee alternative to commiion in the market for information. One example i the multitude of newletter that are ditributed to ubcriber. Value Line offer everal ubcription rate: higher ubcription fee enure earlier information delivery. However, commiion have trong hitorical and regulatory root. Minimal per hare commiion were mandated firt by the NYSE, and then by the SEC for over 00 year, until the indutry wa deregulated in 975. The conequence of deregulation have been profound in the retail brokerage indutry. Two alternative contract, the fixed fee per trade charged by the dicount broker and the percentage of aet managed fee employed by full-ervice broker uccefully coexit with the commiion contract. Surpriingly, the fixed-fee execution contract provided by the dicount broker and their intitutional counterpart ha not driven out commiion contract in either the intitutional market or the full-ervice retail market. nother potentially important reaon for the urvival of the commiion contract 7

8 i the regulatory treatment of commiion paid by the buy-ide intitution. Intitution compete, among other parameter, on their management fee. If an intitution pay fixed payment for auxiliary ervice received from broker, it mut increae it management fee to cover them. Commiion, on the contrary, are deducted directly from the fund under management, thu do not neceitate raiing management fee. Thi rationale i the driver behind the oft-dollar market, where commiion explicitly ued a a payment for ervice that are unrelated to the execution of pecific tranaction. inally, pychology may play a role. Propect theory (Kahneman and Tverky 980) applied to marketing ugget that a eller of a product or a ervice hould preent it in uch a way that the buyer ee aggregate loe (one price) but egregated gain. Charging a ingle price, that i mall on a per hare bai, and providing a lew of ervice in return i conitent with maximization of the buyer perception of the broker value added... Our view of the commiion contract In our interpretation of the commiion contract, commiion provide a convenient ubtitute for fixed fee. The average per hare commiion paid by an intitution i jut the ratio of the total payment required to obtain the choen ervice level to the total hare volume directed by thi intitution to the broker. unching or aggregating trade with a few broker increae thee broker revenue through the volume component of total revenue. Thu, there will be relatively little variation in the average per hare commiion charge. igure, which preent cro-ectional average of commiion per hare confirm thi peculation. The majority of intitutional trade pay 5 or 6 cent per hare. Thi reult doe not preclude the poibility that the average commiion component can vary to ome extent acro client. Large volume client can pay maller average commiion and till maintain a poition a one of the broker mot important client. On the other hand, maller intitution may voluntarily agree on greater average 8

9 commiion payment becaue their total volume i not large enough to inure them acce to the level of broker ervice they deire. We find that average commiion vary acro client depending on the client ize. Empirically, mall intitution pay higher commiion to the broker with whom they trade the mot. The larget client pay the lowet commiion to their larget volume broker; they provide adequate compenation to the broker through their large trading volume. Total commiion revenue from the larget intitution to their mot active broker i roughly 40 time larger than the overall commiion from the mallet intitution to their mot active broker. ny tranaction cot induce inefficiencie and reduce the volume of trading. ut the effect of commiion on the volume of trade by intitution i minimal, given that baic execution i alway available at competitive price. long a an intitutional client can trade (their marginal hare) with a dicount broker or ECN, hi deired trading volume hould be et uing the ECN low tranaction cot, ince the higher commiion that include the payment for other ervice are inframarginal for the intitution. Conequently, the detrimental effect of charging for broker ervice through higher commiion i mall. In fact, it i poible commiion may actually increae the volume of trading to the detriment of the invetor. If intitutional invetor do not bear the cot of trading directly, they might trade too much to get the deired amount of ervice. Thi problem i particularly relevant for maller intitution that may want to increae their ervice above the level they would receive baed on their ize. Conrad, Johnon and Wahal (00) find that oft-dollar trade receive inferior execution; thu exceive oft-dollar trading could negatively impact performance. We proceed by preenting a imple model of competition between broker, who mut allocate their ervice capacity among intitutional client. Then we potulate and tet empirical hypothee derived from our view of commiion. 9

10 3. The Model Thi purpoe of thi model i to how the exitence of equilibria where broker of different quality compete on fee, and client elect and pay for the amount of ervice they deire. Exitence i hown in a one-period model, but any equilibrium that can be upported in a one-hot game can alo be upported in a dynamic game. We outline the model in a imple by framework for analytical tractability, but we contend that the model could be extended to the cae of many client and broker. The model alo demontrate that two type of equilibria are poible. In the firt, the larget client dominate both broker. unching exit i thi equilibrium if the larget client chooe to ue one broker proportionately more than the other. The econd equilibrium prove the exitence of a tricter definition of bunching; in thi cae each client i the larget trader with a particular broker. Thi cae require localized economie of cale. 3 Economie of cale can arie if: there i a fixed cot of dealing with each broker, or if broker fee are concave in the level of ervice, or if the benefit of receiving a high level of broker ervice exhibit increaing return to cale. inally, we contend that the payment for broker ervice i not paid a a lump um, but charged on a per hare bai. Then the number of hare ent to a particular broker by a particular client determine the level of ervice the client receive from that broker. 3.. Model etup: the intitution choice of ervice There are two intitution, and, with different portfolio ize. We aume that portfolio ize i poitively correlated with the value they derive from broker ervice. Thee differential valuation are repreented by Q > Q >. We alo aume that there exit two broker, who differ in term of the quality of ervice they can provide. Thi Intitution loe on performance if they pend too much on commiion, but it may be of minor importance relative to what they gain from getting extra ervice. 3 Thi reult can be obtained in a model where all broker provide the ame ervice (perfect ubtitute), but due to economie of cale they provide quantity dicount. Client, on the other hand, prefer to trade through many broker o a to prevent front running and conceal their trade. The tradeoff between the two create bunching for ome client. 0

11 quality i denoted by j : j = [,] uch that >. The level of ervice provided by broker j to client i i denoted by ji The total value of the ervice for client i i a follow: Notice that: [ ln( ) + ( )] i i i i V = Q ln i i () Vi i Qi = i which i poitive if we aume that and i, Q > i i vi i i () = - < 0. Thi implie that the ervice provided by the competing broker are ubtitute. We alo aume that broker have limited capacitie, S and S, which they have to allocate among all the demander for their ervice. Thu: = S and + = S + (3) We further aume that broker are limited in charging a fee per unit of ervice provided. We denote thee fee,, for the firt and econd broker repectively., The firt tep i to figure out what would be the equilibrium in thi market, if broker could charge pecific price for their ervice. The demand for ervice from each intitutional client i determined by the following optimization problem: max Si S i [ ln( ) + ( )] i ln i i i i i Qi (4) The OC are: and Q = 0 (5a) Q = 0 (5b) If we aume, a before, that Q ii > 0 then the indifference curve are convex in the relevant range, enuring the exitence of the maximum.

12 Solving for the optimal choice, we obtain: ( ) [ ] 0 = + + Q Q, or ( ) ( ) [ ] 4 Q Q Q =, (6a) and ( ) ( ) [ ] 4 Q Q Q =. (6b) Similarly: ( ) ( ) [ ] 4 Q Q Q = (7a) ( ) ( ) [ ] 4 Q Q Q = (7b) 3.. The broker optimization The broker mut decide on the fee for their repective ervice in a imultaneou one-hot game. roker maximize their fee given the olution to the intitution choice problem and ubject to the capacity contraint: max ( ) ( ) [ ] p ; ; + (8a) ( ) ( ) S t = + ; ;.. ( ) ( ) [ ] ( ) ( ) S t a p = + + ; ;.. ; ; max (8b) It i clear that without explicitly meauring the broker cot function, the capacity contraint mut be binding in equilibrium. Thi implie that the hadow price of the capacity contraint mut be equal, and both capacity contraint are atified a equalitie. In other word, the broker mut olve the optimal capacity allocation problem. It i poible to model an additional tage in the game where broker firt

13 chooe their capacity. However, given the complete information nature of the game choice, a broker would never chooe exce cotly capacity. Thu we retrict our attention to the econd tage of the game. Conequently: ( ) + ( ; ) ; (9a) = S ( ) + ( ; ) ; (9b) = S Equation (9a) pecifie the reaction function of the firt broker and (9b) that of the econd broker. We et S = S =, o that we interpret each client allocation a hare of the total broker capacity. Subtituting (6a,b) and (7a,b) into (9a,b) we conclude that in the equilibrium ( )( ) * * = + Q + Q. (0) The equilibrium difference between the broker fee i directly proportional to the difference in broker quality. The next tep i to prove the exitence of the equilibrium. irt we evaluate the reaction function of the firt broker (9a) at =0, which yield: ( ) = ( )( ). = 0 Q + Q () We can how that ( ) i a monotonically increaing concave function, which converge aymptotically to = ( + ) Q Q a. We cannot evaluate the reaction function of the econd broker, (9b), at = 0, but we can evaluate it at = 0 which yield: Notice, that: < ( )( Q + ) = 0 = () Q. We can how that the reaction function ( ) i a monotonically increaing concave function that converge aymptotically to ( Q + Q ) a = equilibrium of the game between the two broker.. Thee reult imply that there exit a unique Nah 3

14 In thi equilibrium, the larget client dominate both broker. Thi i quite intuitive, ince the marginal benefit of any combination i proportional to the client ize. Thi i the only equilibrium type poible given our current et of aumption. Thi equilibrium exhibit bunching when the larget client ue le of the econd broker capacity than he doe of the firt broker capacity. It i poible to derive an alternative equilibrium in which bunching i o extreme that each client i the larget trader with a particular broker. The clearet way to how thi i to prove the exitence of an equilibrium in which the maller client () would prefer to completely forego the ervice of the firt broker and intead, concentrate all of their trading with the econd broker. In the proce may become the larget client of the econd broker. To obtain thi equilibrium require the aumption of increaing return to cale in broker ervice. The implet way to model increaing return i through the fixed fee each client ha to pay for dealing with the broker. 4 Thi fee can be exogenou, or choen by the broker. We model the firt cae for implicity fixed cot equilibrium If there were a non-trivial fixed cot of uing a broker, the enuing equilibrium could be uch that the econd client chooe not to buy from the firt broker. 5 Since, in thi cae: = 0, thu = S, broker two ervice would be given by: Q S + =, (3a) and Q =. (3b) Thi yield: Q S + + = S Q, (4a) 4 Conceptually, increaing return to cale can be repreented in other way, uch a the increaing return to cale in broker ervice dicued above. 5 He could alo forego the ervice of the econd broker, and intead focu on the fir, but he will be able to buy much le ervice there, due to more intene competition from client. 4

15 or S ' ( S S ( Q + Q ) Q 0, ' P + S = (4b) ' where: S S /. Solving, we obtain: ' ' ( Q + Q ) S S + ( S S ( Q + Q ) ' + =. (5) ' ' Let S = S = S, then = S ( Q + Q ) + ( ( Q + Q ) 4Q S S + 4Q = (6) Subtituting into the demand function, we obtain: Q = (7) ( Q + Q ) + ( ( Q + Q ) + 4Q Next we determine the condition under which client demand more than half of the econd broker ervice: > Thi i equivalent to: ( Q + Q ) ( ( Q + Q ) + Q Q > (8) or Q > Q. Thu, given the increaing return induced by the fixed fee, the econd client will take more than half of the capacity of the econd broker, while foregoing the ervice of the firt broker altogether. Thi can occur when the two client are not too different in their valuation {Q, Q }. Conceptually, any form of increaing return, whether exogenouly determined a in thi example, or endogenou, could reult in a bunching equilibrium. roker may prefer one equilibrium to the other. The firt equilibrium involve more competition between broker, but alo more competition between the client. The econd equilibrium i a le competitive environment. 5

16 3.4. Commiion in our framework In the equilibria preented above, a per-hare commiion can be eaily calculated a the per hare amount required to generate the ervice fee given the client equilibrium trading volume. Denote by q ij the equilibrium hare volume ent by client i to broker j, which i the deciion variable of client i. The per-hare commiion each client pay i computed from the total payment required for the ervice, and the volume allocated to each broker. The per hare commiion paid by client i to broker j, which we denote by c ji i therefore, jut the ratio of the required payment for the ervice, and the volume ent by the client to the broker: c ji = j ij / q ij. (9) Notice that while the commiion i expreed in per hare term, it repreent the average payment, rather than the marginal cot of execution. Thi i a new way of looking at the commiion contract. The empirical evidence preented below upport our alternative view of commiion. We contend that equilibria with more broker and client will exhibit imilar feature to thi imple by cae. bunching equilibrium could exit in a world with many client and many broker. The larget intitution will tend to be important client to many broker. ut large intitution will not necearily be the mot important client for every broker. Smaller intitution mut concentrate their trade with a few broker in order to obtain their deired level of broker ervice. roker rank client in a queue; allocating the bet ervice to thoe client who chooe to pay the fee. ecaue fee payment are tracked by per hare commiion, in a bunching equilibrium mall intitution will trade relatively more with their top broker than large intitution do. We tet thi implication of the model uing a proprietary databae of intitutional trade. Thi data and the accompanying tet are decribed in the next ection. 6

17 4. Data, hypothee and empirical reult The data ued to tet our hypothee conit of 65,83 trade by 305 intitutional invetor executed between January, 997 and March 3, The data i obtained from bel-noer Corporation, a NYSE member firm and a leading provider of tranaction cot analyi to intitutional invetor. Information in the databae conit of everal unique item including: identification of the executing broker, identification of the intitutional client, and a trade indicator (uy or Sell). In addition, the databae contain the per-hare commiion cot of each trade the trade date, ize, and the execution price. 4.. Decriptive tatitic Intitutional commiion are quoted on a per hare bai; their level vary, but the vat majority are denominated in term of round cent per hare. igure preent the ditribution of commiion per hare baed on the trade ize. We ee that the majority of intitutional commiion are 5-6 cent per hare. There i a relative paucity of trade at 4 cent per hare, however many trade are charged between 0-3 cent per hare. The frequency of both 3 and 5 cent-per-hare commiion increae with the trade ize. Sixty percent of all block trade (above 50,000) are charged thee two commiion. We peculate that the ditribution of commiion ugget that there are eentially two type of trade in the databae. ull ervice trade, uually charging 5 or 6 cent per hare and execution-only trade charging 3 cent per hare or le. 7 We examine the breakdown of thee trade acro different ize broker and client in ection 4.. The ize of the intitutional client i important to everal of our hypothee. To undertand more about the different intitution in the databae, we firt ort the client into five quintile, ranked by trading volume, and examine aggregate trading tatitic by 6 We are unure whether thi databae, although it i very large, contain all the trade by every client, and it certainly doe not contain all the trade by every broker. Thu there may be a bia in the data toward particular broker. Neverthele, a we examine the client trading pattern, a long a the majority of trade for each client are reported or the ampling mechanim i unbiaed, our reult hould be repreented of the entire market 7

18 quintile. What i immediately evident in Table i that trading activity i kewed toward the larget client. The high-volume quintile dominate the other quintile in term of total trading volume, total trade and total commiion paid to broker. The trading activity of the mallet 80 percent of all intitution i only percent of the total number of tranaction, with the larget quintile executing the bulk of all tranaction. trade ize alo rie with client ize, from a total hare volume perpective, thee dicrepancie are even larger. Clearly, the larget intitution are going to be deired cutomer for all broker. rom our perpective, thi bring up the intereting quetion of how the mallet 80 percent of all intitution compete for broker ervice. We potulate that the maller broker will tend to bunch their trade among fewer broker, perhap concentrating their full-ervice trade among the maller broker where they obtain adequate level of broker ervice from relatively mall trading volume. 4.. Client trading by broker ize Table examine aggregate trading tatitic for our five client quintile againt five broker quintile, orted by total broker volume. Table preent aggregate trading tatitic for twenty-five cell, five for client ize and five for broker ize. In addition, we analyze the importance of each cell trading volume relative to the total volume eparating trade into thoe that charge 5 cent or more per hare (full-ervice trade) and thoe trade that charge le than five cent per trade (execution-only trade). The mot triking reult in Table i that trading volume i trongly kewed toward the larget client executing with the larget broker. Over ixty-five percent of total volume i trade by the larget intitution with the larget broker where the commiion cot i at leat five cent per hare. n additional twenty five percent of all volume i accounted for by the execution-only trade of thi group. In term of aggregate volume, all intitutional trading on Wall Street i eentially the larget intitution trading with the larget broker. 7 We confirmed the accuracy of our peculation in converation with intitutional trading dek. 8

19 Neverthele there are ome intereting pattern in overall full-ervice volume that are evident in the table. Conider, for example, the full-ervice trade of the mallet intitution. The three mallet client quintile all do le trading with the larget broker quintile than they do with ome other broker quintile. Thi reult i counterintuitive, becaue total trading volume increae a broker quintile go from to 5. However, thi reult i conitent with our hypothee. Smaller client chooe to concentrate their trade with the maller broker. With little chance of competing in the queue for ervice with the larger broker, the maller intitution tend to concentrate their trade with broker to which they are relatively important. Thi tendency to bunch trading with particular broker i explicitly documented in Table 3. verage commiion cot are relatively contant acro the twenty-five cell. One notable exception i that the larget client-broker quintile per-hare commiion are the lowet average in the table. Thi finding tend to upport our contention that the larget client provide enough volume-baed revenue to the broker that large client can achieve ome cot per hare dicount Evidence on intitutional clutering of trade Table 3 preent evidence on the bunching or clutering of trade for each client quintile. The firt panel preent the average amount of trading done with each quintile highet volume (Top) broker, their top 3 broker, their top 5 broker, their top 0 broker and the total number of broker employed. The data in Table 3 indicate a very kewed allocation of client trade among broker. The larget intitution end 0% of their total volume to their top broker, 7% to the next two, % to the following two, and 7% to the next five. The mallet intitution concentrate their trading even more, they end 38% of their trading volume to their top broker, 5% to the next two larget broker, % to the next two, and 8% to the next five. Thee reult contradict the naïve aumption that client want to hide their 9

20 trading trategie by maximizing the number of broker they ue. There mut be a trong reaon to deviate from that trategy, namely the benefit from moving up higher in the queue for broker ervice. Thee reult are conitent with our model. Notice that the exitence of fixed cot of dealing with every broker would alo prompt maller client to reduce the number of broker they engage. However, thi imple tory would not explain the aymmetry of dealing with broker that we document. The middle panel of Table 3 preent average commiion cot for each client quintile. The average commiion cot for the top-ranked broker confirm our intuition that maller intitution that cannot move up the broker queue with higher volume might chooe to do o by paying higher per hare commiion. In fact, in each of the mallet three client quintile the average commiion paid to the larget broker are larger than the average commiion paid to all other group of broker. Thee reult are contrary to the evidence of volume dicount in the retail market preented in rennan and Chordia (993), but they are conitent with maller client increaing their revenue with their mot important broker. In contrat, larger client receive volume dicount and pay le in average commiion to their top broker than they do to other broker Determinant of commiion per hare Table 4 preent regreion reult uing the commiion per hare on each trade a the dependent variable. The regreion pecification i: Commiion= + β Share+ β Price+ β Percentmarket+ β QVOL+ β QVOL+ η (0) In Equation (0) Commiion i commiion per hare on a ingle trade, Share i the trade ize, Price i the trade price, Percent market i the trade ize a a percentage of the daily trading volume in the tock, QVOL i the quintile rank of the client and QVOL i the quintile rank of the executing broker. Table 4, panel preent Equation (0) regreion reult for 644,49 trade. ll 0

21 trade in thi regreion had commiion of le than 8 cent per hare. 8 The trade ize, the percent of daily market volume and the price are all variable that repreent the marginal cot of tranacting. Larger trade, meaured a both the number of hare and by the dollar volume (Price) are widely ued to repreent the cot of trade execution. The percent of the market (Percent market) i an additional and ueful meaure of trading cot, becaue it control for difference in trading volume acro tock. The coefficient of the number of hare and the percent of the market have the predicted ign: the greater the number of hare and percent of the market, the higher the commiion cot. The coefficient on Price ha a negative ign, which i not predicted by the tandard execution cot argument. The triking reult in thi table i that thee tandard meaure of tranaction cot do not explain much of the variation in commiion per hare. Much more effective are the control for the ize of the client, QVOL and the ize of the broker, QVOL. Particularly relevant to our argument i the explanatory power of QVOL, the quintile rank of the client. We make the argument that larger client can eaily reach their deired fixed fee becaue their total trading volume are o large. We peculate in our dicuion of Table 3 that the commiion per hare charged to the larget client could be lower than the commiion for maller client for thi reaon. We view the fact that client ize i the mot important variable in thi regreion a further confirmation of our hypothei. Panel and C preent commiion per hare regreion that eparate the data into execution-only tranaction, 0-3 commiion per hare, and reearch tranaction, which charge between 3 and 8 cent per hare. In Panel, execution-only trade, the ize of the client add very little explanatory power to the regreion. Thi reult i conitent with our contention that the execution-only market i competitive and priced at marginal cot. We do not expect to ee volume dicount in thi ub-ample. In contrat to thee reult, QVOL i the variable with the greatet explanatory power in Panel C; a regreion uing only the reearch trade. or reearch trade commiion per hare 8 Commiion per hare are truncated at 8 cent to minimize the effect of outlier on the regreion

22 exhibit volume dicount that are conitent with our hypothee Trading efficiency around information event If our hypothei on the client-broker relationhip i correct, we hould expect to find ome tangible benefit from a higher poition in the queue for information. To invetigate thi we have collected a ample of brokerage-pecific analyt recommendation change that previou reearch ha hown to be informative event (Elton, Gruber and Groman, 986, Womack, 996, and arber, Lehavy, McNichol and Trueman, 00). We examine the pattern of client trading at the time of thee information event. If certain client are preferred and get earlier or more complete information prior to other client, then trading gain are poible for thee client. We tet if the trading pattern in our data are conitent with thi hypothei by examining the profitability of client trade at the time the analyt report i releaed. Our ample of analyt recommendation change conit of 44 upgrade or downgrade on NYSE-lited tock that were recorded by the Dow Jone New Service in the firt quarter of 997. The Dow Jone New Service analyt report are timetamped o that we know when the report became public, although public diemination may occur after diemination to important client. The analyt report are iued excluively by broker in our larget quintile. Table 5 preent the average event-day abnormal return for the analyt recommendation change. Our purpoe i not to examine the market reaction to thee event, but rather to confirm that they are information event, a meaured by abnormal return, and that the market reaction i conitent with previou reearch. The event day i defined a the day the report wa releaed if the report i time-tamped before the cloe of trading and the following day if the report i time-tamped after the NYSE 4:00 cloe. bnormal return are etimated uing market exce return on the event day. CRSP provide the raw ecurity return and the value-weighted market return for the coefficient.

23 calculation of market exce return. Our ample of analyt upgrade and downgrade produce ignificant abnormal return. Upgrade produce an average abnormal return of.7% (t-tatitic = 0.4) and downgrade produce and average abnormal return of.98% (t-tatitic = -7.80). The only tatitically inignificant analyt recommendation are upgrade to a hold recommendation. Thi background analyi allow u to tate that we find analyt recommendation to be information event a meaured by abnormal return and therefore trading in thee tock on thee day may provide better than average profit or lo avoidance opportunitie. With the daily cloing price a a benchmark, we can determine the trading efficacy of intitution that execute trade on thee high-information day. urther, we can examine whether trading profit, if they exit, are related to the nature of the clientbroker relationhip Intitutional trading on analyt information Table 6 preent an analyi of client trade on the day analyt change their recommendation. We compare the execution cot of trade through the broker that iue the analyt recommendation againt trading through other broker. 9 Thi i a powerful and direct tet of the informational value of being a client of a reearch broker. Client who traded that day through the recommending broker are by definition client of that broker. We find that trade through the initiating broker on the day of the recommendation change paid higher commiion (5.56 cent), while trade in the ame tock on the ame day through any other broker paid lower commiion (4.68 cent). Thi difference i tatitically ignificant at the % level. We ue the buy and ell indicator variable in our data and the price of the trade to calculate trade profitability. Only trade through the initiating broker are profitable. On average, all intitutional client trading in the tock on the recommendation day beat the volume weighted-average price 3

24 (VWP), though the gain relative to the VWP are modet. The tranaction price relative to the cloe preent the mot triking evidence of profitability. Client who trade through the recommending broker have an execution price 4.55 cent per hare better than the cloe, while trade through the non-recommending broker received only modet price improvement of.70 cent per hare relative to the cloe. or client trading through the recommending broker the price improvement received repreent a gro per-trade profit, baed on the average trade ize of $3,68.9. Thu, client of the initiating broker paid more for their commiion but made profitable trade, while trade done through other broker paid le but lot money relative to the commiion paid. Thee reult are trongly conitent with the model uggetion that for broker ervice uch a information, the place in the queue matter, and that broker inform ome client earlier than other. 5. Concluion Timmon (000) claim that broker treat their preferred intitutional client to privileged information. If her aertion i true, then broker mut have a mechanim that determine the relative importance of an intitutional client. We tart from the natural premie that the broker preferred client will be thoe providing the larget revenue to the brokerage firm. We model the total revenue paid to a broker a a fixed fee, client optimally elect their deired level of broker ervice and pay the aociated fixed fee through commiion per hare on their trade. Thu, commiion per hare repreent an average per hare cot of broker ervice. Thi reult contrat with the prevailing view of per hare commiion a a tranaction cot that i priced at marginal cot. One example of a brokerage ervice that i allocated acro client i acce to information, not all information reache all partie at the ame time. Thu, the receipt of information earlier provide the opportunity for profit to thoe who receive it. Commiion repreent a way for client to pay the broker not only for the information, but alo for the it timely receipt. poition in the queue to receive information i a 9 The ample ize in table 6 i 433. Eight Dow Jone analyt recommendation could not be matched to 4

25 care reource, broker are more likely to provide thi carce reource to thoe that will pay the mot. In repone, client who would otherwie try to diguie their trade by uing many broker will intead try to buy their way up the queue by concentrating their trade acro a few broker. We preent a model of the allocation of broker ervice, uch a a place in the queue for information, and how that a fixed payment mechanim i both an equilibrium and efficient. Empirical reult indicate that client, conitent with attempt to buy their way up the queue, bunch or concentrate their trade, and that maller firm pay higher commiion than larger firm to their top broker. Other empirical reult indicate that brokerage recommendation do affect tock price, and that client who trade through initiating broker on the day of the recommendation make profitable trade while client who trade elewhere do not. Thee reult are conitent with the model and with information being dieminated to broker bet client firt, with client paying more for the privilege of being higher in the queue and receiving information earlier than the ret of the market. tock on the bel-noer databae. 5

26 Reference mihud, Y. nd H. Mendelon, 986, et Pricing and the id-k Spread, Journal of inancial Economic, 5, pp arber,., Lehavy, R., McNichol, M., & Trueman (00) Can Invetor Profit from the Prophet? Security nalyt Recommendation and Stock Return Journal of inance, 56., arclay, M.J., E. Kandel and L. M. Marx, 998, The Effect of Tranaction Cot on Stock Price and Trading Volume, Journal of inancial Intermediation, 7(), pril 998, pp rennan, M. and T. Chordia, 993, rokerage Commiion Schedule, Journal of inance, 48, pp Conrad J., Johnton, K., and S. Wahal, 00, Intitutional Trading and Soft Dollar, Journal of inance, 56., Contantinide, G., 986, Capital Market Equilibrium with Tranaction Cot, Journal of Political Economy, 94, Ealey, D. and M. O Hara, 987, Price, Trade Size and Information in Securitie Market, Journal of inancial Economic, 9. Elton, N., Gruber, M., and S. Groman, 986, Dicrete Expectational Data nd Portfolio Performance, Journal of inance, 46, Gloten, L., and P. Milgrom, 985, id, k and Tranaction Price in a Specialit Market with Heterogeneouly Informed Trader, Journal of inancial Economic, 4, Holmtrom,., 979, Moral Hazard and Obervability, ell Journal of Economic, 0, Holmtrom,., and P. Milgrom, 987, ggregation and Linearity in Proviion of Intertemporal Incentive, Econometrica, 55, Jone, C., and M. Lipon, 999, Execution Cot of Intitutional Equity Order, Journal of inancial Intermediation, 8, Kim, S., Lin J., and M. Slovin 997, Market Structure, Informed Trading and nalyt Recommendation, Journal of inancial and Quantitative nalyi, 3, pp Klein,., Crawford,., and. lchian, 983 Vertical Integration, ppropriable Rent, and the Competitive Contracting Proce, Journal of Law and Economic, Kyle,. 985, Continuou uction and Inider Trading, Econometrica, 53,

27 Madhavan., and D. Keim, 995, natomy of the Trading Proce: Empirical Evidence on the Motivation for and Execution of Intitutional Equity Trade, Journal of inancial Economic, 37, Timmon, H., March 7,000, I Kept on the uy Rating, but I Told My avorite Invetor to Sell, uine Week. Vayano, D. 997, Tranaction Cot and et Price, Dynamic Equilibrium Network, Review of inancial Studie,, -58. Womack, K. 996, Do rokerage nalyt Recommendation Have Invetment Value? Journal of inance, 5, pp

28 igure Comm by Share in % 50.00% 45.00% 40.00% 35.00% 30.00% 5.00% 0.00% 5.00% ,000 5,000 50,000 50, % 5.00% 0.00% Comm , ,000 5,000 0,000 hare

29 Table Decription of intitution (client) trading activity in the ample Thi table preent ummary trading information for the trading activity of 305 intitutional client in the firt quarter of 997. Client are orted into 5 quintile by total trading volume. Total volume, total commiion and the number of trade are total for each client quintile. verage commiion per hare, per trade, trade ize and tock price per hare are average of all trade for each quintile. Price VWP i the buy trade price le that day value-weighted average price; or the value weighted price le the ell trade price. Price open i the ame relative to that day opening price. Price-vwap and price open quintile average and median are reported. Trade direction (uy or Sell) information provided by the client i ued to calculate thee execution cot meaure. Client quintile by trading volume = low = high Total volume (000 ) $ 6,698 5,943 0,754 74,76 5,505,833 Total commiion (000 ) $ 96,904 6,4 0,370 57,05 trade,45 3,564 4,08 59, 54,890 verage commiion c/hare verage commiion $/trade verage trade ize,344,04,939 4,639 0,693 verage price $/hare Price impact VWP cent (median) Price impact Open cent (median).3 (0) -. (0) 0.7 () 3. (0.).9 ().4 (0) 3.7 ().8 (0) -0.9 (-0.) 3.8 (0) 9

30 Table Intitutional Trading by roker and Client Quintile Thi table preent client quintile by broker quintile ummary trading information decribing the commiion and trading activity of 305 intitutional client in the firt quarter of 997. Client are orted into quintile by client volume, broker are orted into quintile by broker volume. or example, trade in the (,) group repreent trade by the mallet volume client with the mallet volume broker. Variable are decribed in table, except for Total volume => 5 (< 5) cent per hare which repreent the percentage of total volume in each quintile paying high commiion (=> 5 cent per hare) or paying low commiion (< 5 cent per hare). roker quintile by broker trading volume Client quintile = low = high Quintile verage commiion cent per hare verage commiion $ per trade Total volume = >5 cent per hare (% of ample) Total volume < 5 cent per hare (% of ample) <0.0 <0.0 <0.0 <0.0 <0.0 verage trade ize,5,8,39,370,348 Price impact VWP $ Price impact Open $ Quintile verage commiion cent per hare verage commiion $ per trade Total volume = >5 cent per hare (% of ample) Total volume < 5 cent per hare (% of ample) <0.0 < < verage trade ize,35 3,30,7,993,0 Price impact VWP $ Price impact Open $ Quintile 3 verage commiion cent per hare verage commiion $ per trade Total volume = >5 cent per hare (% of ample) Total volume < 5 cent per hare (% of ample) < verage trade ize,37,05 3,84 3,33,904 Price impact VWP $ Price impact Open $ Quintile 4 verage commiion cent per hare verage commiion $ per trade Total volume = >5 cent per hare (% of ample) Total volume < 5 cent per hare (% of ample) verage trade ize 5,038 3,090 6,73 5,05 4,584 Price impact VWP $ Price impact Open $ Quintile 5 verage commiion cent per hare verage commiion $ per trade Total volume = >5 cent per hare (% of ample) Total volume < 5 cent per hare (% of ample) < verage trade ize 4,840 6,6 8,05 3,04 0,630 Price impact VWP $ Price impact Open $