The Brokerage Business in the Era of Algorithmic Trading Takahiro TANAKA

Transcription

1 No. 121 September 1, 2007 The Brokerage Business in the Era of Algorithmic Trading Takahiro TANAKA

2 NRI Papers No. 121 September 1, 2007 The Brokerage Business in the Era of Algorithmic Trading Takahiro TANAKA I Sweeping Changes II Emergence of Algorithmic Trading III Comprehensive Assessment of Securities Firms by Asset Management Companies IV Future Brokerage Business In the wholesale stock brokerage business (targeting large-volume trades such as those executed by asset management companies), asset management companies generally assess the quality of research services and trade execution services offered by securities firms on an integrated basis. Based on such evaluations, they decide the order share volume, that is, the amount of brokerage commissions to be paid to each securities firm. Currently, however, the trend of the unbundling of commissions (paying separate charges for trade execution services and for research services) has begun to spread worldwide. A mechanism is now being developed whereby the quality of research services and that of trade execution services are separately evaluated to enable asset managers to select an optimal combination of service providers. In addition, algorithmic trading (an automated trade execution system using computers) that requires capabilities that have not been required of securities firms in the past has emerged. These trends make it increasingly more meaningful to separately compare and select individual services provided by securities firms. A shift from comprehensive evaluation to individual evaluation of securities firms by asset management companies will spur securities firms to create new ideas and services, which will eventually increase the benefits realized by asset management companies. Copyright 2007 by Nomura Research Institute, Ltd. 1

3 I Sweeping Changes Securities firms receive brokerage commissions by mediating orders between investors and stock exchanges, etc. This is called the brokerage business. Currently, two major changes have been occurring, especially in brokerage services for equities. First, as is widely known, online brokers have made rapid advances in the retail field targeting individual investors, causing a major shake-up of the conventional industrial map. The other change concerns the expansion of electronic means of trading as represented by algorithmic trading in business that targets professional investors such as asset management companies (i.e., wholesale business), and relates to the unbundling of commissions, through which the method of evaluating brokerage services has been changing. This paper focuses on the wholesale stock brokerage business. Chapters II and III explain algorithmic trading and how services provided by securities firms are evaluated and Chapter IV considers the future of the brokerage business. II Emergence of Algorithmic Trading 1 What is Algorithmic Trading? An algorithm refers to processing procedures used by human beings and/or computers to achieve intended purposes. Algorithmic trading applies algorithms to the execution of trades, and refers to the computer mechanism that automatically executes trades while continuously monitoring the ever-changing market situation. Currently, this mechanism is principally used for buying/selling equities. The scope of automation is limited to the execution of trades, and generally does not include the process of selecting issues. Accordingly, the algorithm is executed based on the issue and the number of shares that are designated. This mechanism was originally used by securities firms for their own account transactions. Currently, it is being extensively advertised as a system to skillfully execute orders placed by asset management companies that manage pension funds, mutual funds, etc, and is attracting a great deal of attention. Individual investors may consider that trade execution simply means placing an order with a stock exchange by designating a limit price or no limit, and that no complicated algorithm is necessary for such execution. However, for asset management companies that must deal with a large volume of orders, this process requires advanced expertise. For example, suppose an asset management company wishes to purchase one million shares of an issue that is modestly priced. The asset management company gives an order to a securities firm to purchase one million shares at the lowest price possible. Upon receiving the order, the securities firm determines the best method of executing the order while giving consideration to the impact that such a large order would have on the market. If one million shares are ordered without a price limit, the price of the ordered issue will soar; if a limit price is designated, the market will know the existence of the buy order for one million shares. As such, one million shares are generally divided into slices and multiple trades are executed for a smaller number of shares in consideration of the timing of such execution. Generally, it is believed that if shares are divided into as many small groups as possible and more time is taken for such execution, any increase of the price can be restrained. However, if a long time is taken to execute the trades, the stock price of the issue that was initially considered modest may rise rapidly, and eventually may reach a level that can in no way be considered modest (price fluctuation risk). Algorithmic trading is effective in such cases. Algorithmic trading creates a model of the trade-off relationships between the market impact being alleviated by taking time to execute trades and the price fluctuation risk being minimized by reducing the time to execute trades, calculates the best execution schedule and executes trades by dividing an order at a pace that meets such a schedule. In consideration of a market situation, the decision to issue an order without limit or to wait a little while by designating a limit price is also included in algorithmic trading (Figure 1). While the cases mentioned above are typical examples of algorithmic trading, many other aspects must also be considered to sell/buy a large volume of shares at the most advantageous price. For such purposes, securities firms make multiple algorithms available to meet a wide variety of the needs of asset management companies. 2 Automated Trading Improves Business Efficiency and Execution Quality Algorithmic trading has quickly become popular in the United States. Currently, it is beginning to spread in Europe and Japan. The background factor behind such moves is the issue commonly faced by securities firms in advanced countries all over the world. This issue is the need to concurrently improve business efficiency and execution quality. The background factor behind the need to improve business efficiency is that, although the scale of market transactions is expanding and the client requirements are becoming increasingly complicated, the level of commissions that constitute revenue remains low and there is a limit to the number of employees that can be added. Copyright 2007 by Nomura Research Institute, Ltd. 2

4 Figure 1. Overview of Processing a Typical Algorithmic Trade Asset management company Securities firm Stock exchange Market impact model Price fluctuation model Number of shares to be traded by a certain time 0 shares One million shares 9:00 Issuing an order Purchase of one million shares Time Best execution schedule Issuing an order Issuing an order 15:00 Ordering the necessary number of shares over time Figure 2. Distribution of Brokerage Commission Rates for Wholesale Trades in Japan (%) Share of monetary amount bps Commission rate Note: bps = basis point; 1 bps = 0.01%. Source: Compiled based on the data of asset management companies using Trading, an execution assessment service provided by Nomura Research Institute; calculated for the period between October 2005 and September For example, currently, the average level of commissions for wholesale business in Japan is about 10 bps (basis point; 1 bps = 0.01%) of the contracted amount. With respect to basket trades that handle many issues as a single product, the level declines to around 3 to 5 bps because a large amount of money is involved (Figure 2). Considering that the level of the brokerage commissions before liberalization was around 55 bps (when the contracted amount was 5 million), it is easy to understand how rapid the decline was. The background factor behind the focus on execution quality is an increased awareness of best execution. The awareness that best execution does not simply mean placing an order with securities firms offering low brokerage commissions, but means selecting an optimal means of ordering by considering the market impact and price fluctuation risk as mentioned above, has already been firmly established among asset management companies. To achieve best execution, investors frequently change the limit price and/or designate the upper limit of the rate of their involvement in market turnover. Securities firms that have applied automated execution in the past understand how extensively computers can be applied to skillfully execute trades under such complicated conditions. Based on such understanding, securities firms have started to attract client attention to algorithmic trading that was developed by further improving the conventional method of automated execution. In Japan, the conventional method of automated execution was used in the latter half of the 1990s principally for improving the efficiency of business operations. Using this method, traders of securities firms entered orders received by phone in an automated execution system and left the complicated operations up to the system. In this respect, the conventional method of automated execution is identical to algorithmic trading. However, Copyright 2007 by Nomura Research Institute, Ltd. 3

5 their differences are seen in securities firms attitude, selection and service format. In terms of attitude, in entering the orders received from asset management companies in the automated execution system, traders of securities firms had felt somewhat as if they were doing something wrong in that they were saving manual labor and leaving complicated work up to a machine. However, they have a completely different attitude towards algorithmic trading. They are taking a positive approach to emphasizing the excellence of algorithms. In terms of selection, only about one or two types of algorithms were available for the conventional method of automated execution. In contrast, algorithmic trading generally offers about five to ten different types of algorithms (Table 1). In addition, while only traders of securities firms could use the system in the past, algorithmic trading also offers a mechanism by which traders of asset management companies can select a certain algorithm on their PCs to execute trades. As such, although the same automated method used in the conventional system is used in the current system, the current system has been called algorithmic trading. This is because securities firms have highlighted the merchantability of the automated execution program itself. Table 1. Representative Algorithms Name of algorithm TWAP VWAP Arrival Price (IS) Participation Market on Close Short Sell Description Time weighted average price; this algorithm executes an order evenly over a defined time. Volume weighted average price; this algorithm splits an order so as to follow the volume distribution on the market over a particular time period in order to near the volume weighted average price on the market. This algorithm considers a trade-off between market impact and price fluctuation risk, and executes an order in such a way as to minimize the gap between the price at the time an order is received and the average execution price. This algorithm executes an order in such a way that the number of shares ordered accounts for a constant percentage of the total trading volume of the relevant stock. This algorithm executes an order in such a way that the average execution price nears the closing price while avoiding any rapid fluctuations of the closing price; this is used by index fund managers, etc. This algorithm automatically implements short selling in compliance with regulations. 3 Widespread Use of Algorithmic Trading in the US In addition to the environment that is commonly faced by securities firms all over the world, as mentioned above, the situation that is particular to the US also contributes to the widespread use of algorithmic trading in the US. The first issue concerns the existence of multiple markets. In many cases, one particular stock is listed on only one market in Japan. Even if the stock is listed on multiple markets, its trading volume on a specific market is overwhelmingly large. Because of this, the single market where trades should be executed can generally be identified. However, in the US, one particular stock is traded actively and concurrently on multiple markets. Therefore, if, for example, a person wants to purchase 1,000 shares of a certain stock, an algorithm that distributes order slices by calculating a combination of markets where trades can be executed at the most advantageous price becomes necessary. Another issue is the impact of so-called decimalization. In the past, stock prices were traded at fractions of sixteenths of a dollar. In 2001, this fractional pricing was changed to decimal pricing on a cent-unit basis. Because prices were divided into smaller pieces from sixteenths to hundredths, orders designating the limit price have been split into smaller slices, which have been placed for differing prices. This has given rise to the need to split orders into small slices for trade execution, which served as a reason for developing automated trading. The primary feature of algorithmic trading in the US is a do-it-yourself type of service in which asset management companies themselves select an algorithm they want on their PCs and push a button to execute a trade without going through securities firms. This feature has encouraged securities firms in the US to provide more enhanced services on the PCs of asset management companies, spurring them on to the acquisition of software firms, etc. The major functions of algorithmic trading in the US include: A function to monitor the progress of an order after entering it using an algorithm An analysis function to select the most appropriate algorithm from among many A function to assess and analyze the results of the execution of the algorithm-based trade Pair Contingent In cases where relationships such as prices of two designated stocks satisfy certain conditions, this algorithm simultaneously buys one stock and sells the other. With respect to a basket where buys and sells are mixed, this algorithm buys shares whose monetary amount equals the amount sold. Such a do it yourself trade execution method brought advantages to both asset management companies and securities firms. Asset management companies can receive high-quality execution services at lower brokerage commissions, and securities firms can handle a larger volume of orders with fewer staff members. Copyright 2007 by Nomura Research Institute, Ltd. 4

6 According to the Aite Group, a research company in the US, algorithmic trading accounted for 33 percent of all trades in the US at the end of The Aite Group predicts that it will expand to 53 percent in 2010 ( Algorithmic Trading 2006: More Bells and Whistles, November 6, 2006). Furthermore, almost all asset management companies in the US are said to be using algorithmic trading in some form or other although their usage frequency differs. As such, algorithmic trading is firmly rooted in the US as a new means of trade execution. 4 Algorithmic Trading at the Beginning Stage in Japan Foreign companies with extensive experience in the US have taken the lead in promoting algorithmic trading in Japan. They started this service by customizing their own systems for the Japanese market. On September 30, 2005, a Japanese newspaper first reported on algorithmic trading. At that time, algorithmic trading was introduced as Denshi zuno torihiki (electronic brain trading), and the newspapers reported that Credit Suisse First Boston (currently Credit Suisse Securities) was to start algorithmic trading in October 2005 in the Japanese language. Subsequently, this topic has often appeared in newspapers, and has been covered at a frequency of about once every ten days (by four Nikkei newspapers as of April 18, 2007). According to the reports in these newspapers and based on the results of interviews conducted by Nomura Research Institute (NRI), we presume that most major foreign securities firms are currently providing algorithmic trading in the Japanese market. On the other hand, Japanese securities firms lag behind the foreign firms in providing such service. Those Japanese securities firms equipped with facilities for the conventional type of automated execution are regarded as being advanced. When we turn our eyes to the do-it-yourself type of algorithmic trading as practiced in the US, we find that many Japanese securities firms are still on the way towards developing such a service. Then, what is the situation of users, i.e., Japanese asset management companies? From February to March 2007, NRI conducted a questionnaire survey targeting asset management companies that have offices in Japan. This Survey on Trading by Major Domestic Asset Management Companies revealed that the percentage of responding companies using algorithmic trading on a daily basis was only 17.6 percent. If responding companies using such a service on a trial basis are included, the percentage was about 35 percent. However, responding companies that answered not using now, but considering such usage accounted for Figure 3. Use of Algorithmic Trading in Japan Not using, and do not intend to use in the future Not using, but considering usage 23.5% 41.2% Using every day as a means of placing orders 17.6% 17.6% Using on a trial basis N = 34 Source: Survey on Trading by Major Domestic Asset Management Companies by Nomura Research Institute in February to March percent. If these companies are combined with those that answered using in some form, the responding asset management companies that have a positive attitude towards algorithmic trading account for more than three-fourths of the total (Figure 3). Nearly 60 percent of responding companies that have experience in using algorithmic trading answered that they will gradually increase the usage frequency in the future. The reasons many responding companies gave for using algorithmic trading include it enables the improvement of business efficiency and brokerage commissions can be reduced. Currently, algorithmic trading is not widely used by Japanese asset management companies. Nevertheless, the findings of the survey suggest the future expansion of its use. At present, algorithmic trading is just at its dawning stage in Japan. 5 Concerns over the Existing System of the Tokyo Stock Exchange As described above, asset management companies generally favor the use of algorithmic trading. However, concerns have started to appear over the performance of the system of the Tokyo Stock Exchange (TSE) if algorithmic trading is widely used. On January 18, 2006, with the occurrence of the socalled Livedoor shock, the TSE closed early due to worries that the trade volume would exceed its system capacity. Subsequently, it continued to close early for about three months. This event is still fresh in our memory. If algorithmic trading is introduced and orders are split into small slices, causing a rapid increase in the number of orders, the upper limit of the daily capacity of TSE s system might again be threatened, which is the concern that many people now have. In addition, there is the matter of the system s response time. This issue has already become apparent in that several seconds are required for response during periods when trades are concentrated such as near the opening of the market. Algorithmic trading uses computer Copyright 2007 by Nomura Research Institute, Ltd. 5

7 programs for repeat ordering and/or correction operations at high speeds. However, the current response time may delay the execution of transactions at the intended timing. This means that even if a user has a good plan, an algorithm that executes trades at high frequency cannot be applied. According to the TSE, however, a next-generation system will start operating in It is believed that this new system will resolve the matter of daily processing capacity and the issue of response time. 6 Keys to Wide Use As explained in describing the results of the survey of asset management companies, Japan will see the widespread use of algorithmic trading in the future. The following section outlines the issues facing Japan in the promotion of algorithmic trading. I would first like to focus on the reasons why many asset management companies are not using algorithmic trading. According to the results of the survey, the reasons selected by many responding companies that are not using algorithmic trading included concerns over the lack of involvement of human beings and no means are available to properly assess algorithms. These reasons imply an attitude wherein asset management companies are reluctant to use algorithmic trading about which they have insufficient understanding and which still represents an unfamiliar black box. The first key point to facilitate the use of algorithmic trading is to eliminate the concerns of asset management companies. To this end, securities firms must provide adequate information to their clients, such as how an offered algorithm executes a trade, and under what market environment it operates successfully or poorly. If a securities firm can explain the features of its own algorithm quantitatively by analyzing the results of execution using its algorithm, many of the concerns of asset management companies will be swept away. As such, acquiring personnel who are able to provide such advice to clients is a pressing need for securities firms. The system-based solution is also effective for wiping out client concerns. For example, a securities firm provides an environment where traders of an asset management company can monitor the operation of an algorithmic trade on their own PCs, stop the algorithm by manual operation in case of emergency and change parameters used by the algorithm. These features will give a sense of security to clients. Even among foreign securities firms, only a few companies provide such functions to Japanese asset management companies. The second point is to have asset management companies actually experience economic advantages. Discounting brokerage commissions by providing a do it yourself means of execution may be a simple way to have them sense an economic advantage. However, the current attitude of asset management companies is more sophisticated. Rather than being sensitive about the amount of the brokerage commission, they want to minimize the total trading cost after taking into account market impact and price fluctuation risk. Therefore, evaluation of the performance of an algorithm must be based on the total trading cost. It is effective for securities firms to show economic advantages quantitatively through such an evaluation. For this purpose, the algorithm must continue to be improved, and the competitive edge should be secured by its sophisticated features. In the future, the system infrastructure will constitute a source of competitiveness for securities firms to quickly implement an algorithm that is developed based on integrated expertise pertaining to the execution of trades. When the TSE s next-generation system starts operation in 2009, there will no longer be any concerns over processing capacity and response time. This means securities firms will be increasingly tested for their ability to create ideas and work out originality. The start of intense competition in developing algorithms is just around the corner. III Comprehensive Assessment of Securities Firms by Asset Management Companies In Chapter II, I explained algorithmic trading as a new means of trading, which is expected to expand in the future. Because securities firms offer many more services, the following section describes the services that securities firms provide to asset management companies. I will also explain how asset management companies assess such services. 1 Services Provided by Securities Firms Algorithmic trading is effective as a means of skillfully executing a large volume of orders. However, if the number of shares to be traded is limited, the received order can be directly routed to the stock exchange in the same way as is done by individual investors through online brokers. This method is called DMA (direct market access), and is known as a means of trading involving low brokerage commissions. In cases where a large volume of orders is involved, but a trader wants to conclude the deal quickly, a securities firm can act as a principal party to the deal and immediately complete the deal (principal trading). Another means of executing a large volume of orders is matching trading. Because a securities firm mediates between many investors, a client can ask the securities firm to find a buyer or seller if the client wants to sell or buy a certain stock. Copyright 2007 by Nomura Research Institute, Ltd. 6

8 As such, asset management companies use different methods of execution depending on the situation involved. All of these services provided by securities firms are classified as trade execution services. In addition, asset management companies receive projection reports on the performance of a specific company and macroscopic economic forecasts from analysts of securities firms. Furthermore, securities firms hold various seminars and arrange meetings with the executives of companies. These services are collectively referred to as research services. Currently, asset management companies pay compensation for both trade execution services and research services in the form of brokerage commissions. 2 What is Scoring of Securities Firms? Asset management companies score securities firms in some form or other in order to correlate the services provided by securities firms with the payment of brokerage commissions. By placing more orders with a securities firm gaining high scores, asset management companies eventually pay different brokerage commissions for each securities firm. The scoring of securities firms by asset management companies is conducted every quarter or every six months. The results of scoring are reflected in the share of brokerage commissions for the next term. Because there are many asset management companies where a scoring system is the only method of determining the brokerage commission amount to be paid to securities firms, securities firms must offer services effectively that can lead to an increase in their scores. Scoring generally consists of a portion for research services and a portion for trade execution services. In many cases, research services are evaluated by analysts and fund managers whereas trade execution services are assessed by traders. The scoring is usually conducted by adding points. The assessment personnel of asset management companies grade the service content of each securities firm. The accumulated points are then weighted in proportion to the ratios allocated to research services and trade execution services (e.g., 60% vs. 40%). The points so calculated become the final score of the relevant securities firm. The following section explains the assessment items used in scoring respective services. (1) Scoring of research services The assessment items of research services to be evaluated by analysts and fund managers are classified into analysis services, meeting arrangements and other services. Examples of respective assessment items are described below. Analysis services To assess analysis services, the content of reports submitted by analysts, the extent to which the projections on performance are actually achieved, etc. are evaluated. In some cases, the individual analysts of a securities firm are evaluated. Meeting arrangements Such activities as meetings with analysts, meetings with the executives of companies, tours of factories, seminars and study meetings are evaluated. The focus of the evaluation is placed on whether the meetings were useful, whether valuable opportunities were set up, whether many opportunities were arranged, etc. Other services Services that do not fall under any of the above items are evaluated. This assessment focuses on qualitative analysis, i.e., whether the personnel maintain a good communication status with a securities firm, whether a securities firm responded to a spot request, etc. (2) Scoring of trade execution services The assessment items of trade execution services to be evaluated by traders are classified into the ability to execute trades, the ability to provide information, clerical work processing capability, etc. In many cases, the ability to execute trades is evaluated by breaking it down into agency trading 1 and principal trading. While the concept of evaluating the ability to provide information is close to that of evaluating research services, as mentioned above, here this ability is evaluated as to whether the provided information is useful from the perspective of traders. In evaluating clerical wok processing capability, the accuracy and promptness of clerical processing is examined. For errors, points are usually deducted. Typical examples of respective assessment items are described below. Ability to execute trades The specific items used in evaluating the trade execution ability of the relevant securities firm include its execution technology, execution capacity, whether flexible responses can be made for execution, etc. In the case of agency trading, for example, the evaluation items include a comparison between the VWAP 2 and the execution price, the level of implementation shortfall 3, the order receiving system, the procurement capability 4 for matching trading, response to a complex order, etc. In the case of principal trading, the assessment is made in terms of the frequency of participation in competition and the percentage of trades that were successfully concluded. Ability to provide information The ability to provide information is evaluated by the content and volume of information provided to the traders of asset management companies. The targets to be evaluated under this item include reports related to trading systems, trading-related reports, the holding of study meetings, etc. Communication during the execution of a trade is also targeted under this evaluation item, such as whether quick contact is made concerning the progress of an ongoing trade, whether appropriate information on market changes is provided, etc. Copyright 2007 by Nomura Research Institute, Ltd. 7

9 Clerical work processing capability Promptness and accuracy in providing information on the trade content after the conclusion of a transaction is targeted under this evaluation item. 3 Unbundling of the commission As described above, the commission consists of pure compensation for trade execution and compensation for research service. The unbundling of the commission refers to separately paying for each service. Because the unbundling of the commission enables avoiding unnecessary burdens on investors by increasing transparency in paying the commission, regulatory authorities recommend this pricing mechanism. Increased attention has begun to be given to unbundling when the separation of the commission into a trade execution portion and other portions was required in disclosing information on the management of pension funds in the UK. Currently, in the UK, the number of contracts called commission sharing agreements (CSA) as a means of achieving unbundling is increasing. Under CSA, when an asset management company places an order with a securities firm, it pays a certain percentage of the commission to the securities firm as compensation for the trade execution service, and pools the remaining portion as compensation for research service, which is subsequently paid to the provider of the research service. In this case, the provider of the research service is not necessarily the securities firm that provided the trade execution service. The remaining portion of the commission can be allocated to multiple research companies in predesignated proportions. In the past, it was common to provide trade execution service together with research service on an integrated basis. However, the use of CSA enables the clients to select the optimal combination of service providers (Figure 4). In October 2005, Fidelity Group, a major mutual fund management company in the US, began a pilot program with Lehman Brothers, a major securities firm in the US, under which compensation for trade execution service and that for research service is completely separated. Fidelity has been paying compensation for research service in hard dollars (cash) from its corporate assets, rather than as part of the commission. As such, they have begun to move towards complete unbundling. 4 Unbundling of the Commission in Japan Actually, only a limited number of companies are currently implementing unbundling in Japan. According to the previously mentioned survey conducted by NRI, only around 6 percent of responding asset management companies in Japan have been implementing some form of unbundling. Among the remaining 94 percent, 38 percent have been studying their approach; 56 percent have not even been considering such a method. In some cases, the current status in which research service and trade execution service are always bundled is inconvenient. For example, in the case of a securities firm that provides extremely useful research service but is not so reliable with respect to its ability to execute trades, the choice available to users in Japan is either doing without the use of research service or simultaneously using an unreliable trade execution service. Under these circumstances, some asset management companies are forced to place orders with many securities firms because they want to obtain diversified views and opinions from a large amount of research information. In such cases, unbundling is useful as a scheme for Figure 4. CSA Achieving Unbundling Providing trade execution service Trade execution service Securities firm A 50% Compensation for trade execution service Securities firm A Asset management company Payment Brokerage commission 50% Compensation for research service Distribution Securities firm B Securities firm C Research service Securities firm D Providing research service Note: CSA = commission sharing agreement. Copyright 2007 by Nomura Research Institute, Ltd. 8

10 using research service that is separate from trade execution service. Will unbundling be widely accepted in Japan in the future? The results of the questionnaire survey mentioned previously revealed that 47 percent of responding companies answered that If I have to choose, I am for the expansion of unbundling in the future, with 33 percent selecting If I have to choose, I am opposed to the expansion of unbundling in the future and 20 percent selecting Can t say either way. As such, nearly half of responding companies project that unbundling will expand. Moves to increase the transparency of brokerage commissions have been seen all over the world. It is also necessary in Japan that companies reconsider future business strategies in preparation for the widespread use of unbundling. IV Future Brokerage Business With acceleration in the trend towards the separation of service functions in the future, asset management companies are likely to select securities firms that can provide the highest level of each service. The first phase towards this end will see the separation of research service from trade execution service. Because it is vital for asset managers to draw their own conclusions based on a wide variety of information, asset management companies will use a relatively large number of securities firms to obtain research information. In contrast, there will no longer be a need for asset management companies to use many securities firms to acquire diversified information although they did so in the past. Accordingly, the securities firms from which trade execution service is received will be limited to only top-ranked securities firms in line with the scoring results mentioned in Chapter III. This trend will lead to the use of only a limited number of securities firms by asset management companies as the providers of trade execution service, inevitably intensifying service competition among securities firms in this field. If the current scoring scheme is maintained by asset management companies, securities firms will be compelled to provide comprehensive trade execution services. This is because the present scoring method adopted by many asset management companies adds points for each evaluation item, and securities firms offering more diversified trade execution services have a greater advantage under this method. Securities firms that can provide a variety of services such as DMA, algorithmic trading, manual trading, matching trading, principal trading, etc. on a one-stop basis will have a competitive edge on their competitors. The question that comes to the fore after research services are separated is whether trade execution services should be provided on an integrated basis. Because the capabilities required for DMA and algorithmic trading are largely dependent on system-related elements, evaluation of such capabilities might be impossible under the conventional methods of assessing securities firms. Because of this, I believe that unbundling trade execution services and enabling asset managers to select the best securities firm for each service will best meet the interests of asset management companies. Actually, in the retail field, securities firms specializing in electronic means of trading such as online brokers are enjoying increased presence. In the US, securities firms specializing in DMA and algorithmic trading have appeared in the wholesale field and have been generally favorably evaluated. The expanded activities of these niche players will eventually produce desirable results for asset management companies through service competition among securities firms. Whether asset management companies are able to receive optimal service in each field depends on their own methods of assessment. Only after implementation of the ultimate unbundling of services, as explained above, will securities firms be exposed to competition in individual services. If such intense competition becomes a reality, venture firms specializing in specific services may emerge, which is likely to cause the reshuffling of the scope of influence in the industry. For existing securities firms as well, a management decision to identify its strong fields and to concentrate management resources on such fields will become imperative. Notes: (1) In agency trades, a securities firm acts as an agent on behalf of a client and mediates between the client and the stock exchange, etc. In principal trades, a securities firm becomes a principal party (a buyer or a seller) to the deal. (2) VWAP stands for Volume Weighted Average Price. This is the average price of all execution prices concluded for a specific stock in a day, which were weighted by the volume at each time of transaction conclusion. (3) Implementation shortfall refers to the difference between the decision price and the final execution price for a trade (including commissions, taxes, etc.). For example, this cost is calculated by measuring the difference between the middle rate of market quotation when a securities firm receives an order from an asset management company and the execution price. Another feature of this method is that if some shares are not traded, the lost opportunity cost is calculated for those shares. (4) Procurement ability for matching trading refers to the ability of a securities firm to find investors who will buy/sell shares when it receives a large volume of sell/buy orders. Takahiro TANAKA is senior researcher at NRI s Financial Technology and Market Research Department. His specialties include financial market analyses, securities front office systems and execution cost analyses. Copyright 2007 by Nomura Research Institute, Ltd. 9

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