Wissenschaft & Praxis

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1 19 Beiträge für die Wirtschaftspraxis Wissenschaft & Praxis Efficiency of Equity Trading Platforms with a Focus on Frankfurt Floor and Xetra Andreas Löhr Pantaleon Delgado Akademie Verlag

2 Löhr, Andreas; Delgado, Pantaleon Efficiency of Equity Trading Platforms with a Focus on Frankfurt Floor and Xetra FOM-Schriftenreihe: Beiträge für die Wirtschaftspraxis, Nr. 19 Essen 2011 ISBN C 2011 by Akademie Verlag MA Akademie Verlagsund Druck-Gesellschaft mbh Leimkugelstraße 6,45141 Essen Tel Fax Kein Teil des Manuskriptes darf ohne schriftliche Genehmigung in irgendeiner Form durch Fotokopie, Mikrofilm oder andere Verfahren reprodu ziert werden. Auch die Rechte der Wiedergabe durch Vortrag oder ähnliche Wege bleiben vorbehalten. ISBN

3 Foreword This issue of FOM Beiträge für die Wirtschaftspraxis deals with efficiency criteria and their practical appearance on equity trading platforms. In particular the two most liquid equity trading platforms in Germany, Xetra and Frankfurt Floor, are being compared both in theory and practice including an empirical study. Realizing the increasing pressure on trading platforms and banks to install more transparency and stricter regulatory measures, this paper should unfold importance beyond the two trading platforms primarily focused on. Efficiency criteria like transparency, transaction costs, price building and information efficiency are expected to play a major role in upcoming regulatory guidelines such as the next MiFID2 (Markets in Financial Instruments Directive) and for the competition and consolidation of equity and comparable trading platforms worldwide. The authors provide deep insights into the organisation of trading on security markets. They reveal where improvements could lead to advantages for the organization of markets and all participants trading there. Prof. Dr. Sabine Fichtner-Rosada FOM Hochschule für Oekonomie & Management Wissenschaftliche Schriftenleitung Essen, September 2011

4 Table of Contents List of Abbreviations... III List of Figures... IV 1 Introduction Brief Theoretical Background Functions and Efficiency Criteria of Equity Trading Platforms Expected Results versus Survey Structure of the Empirical Study The Allocation Function The Information Function The Operation Function Summary of Findings Conclusion and Outlook Bibliography II

5 List of Abbreviations APT BörsG CAPM CCP EMH ETC ETF ETS FSE IBIS IDR ISIN MiFID MTF NYSE OTC XETRA XLM Arbitrage Pricing Theory Börsengesetz Capital Asset Pricing Model Central Counterparty Efficient Market Hypothesis Exchange Traded Commodities Exchange Traded Funds Enhanced Transaction Solution System Frankfurt Stock Exchange Integriertes Boersenhandels- und Informationssystem International Depository Receipt International Securities Identification Number Markets in Financial Instruments Directive Multilateral Trading Facility New York Stock Exchange Over-the-Counter Exchange Electronic Trading Xetra Liquidity Measure III

6 List of Figures Figure 1: Market Share Xetra, Frankfurt Floor and Other Floor Exchanges 2 Figure 2: Functions and Efficiency Criteria of Equity Trading Platforms 6 Figure 3: Allocation Tree 7 Figure 4: Information Tree 8 Figure 5: Operation Tree 9 Figure 6: Price Building 11 Figure 7: Pricing Quality Xetra 12 Figure 8: Pricing Quality Frankfurt Floor 12 Figure 9: Marks reg. Price Building 12 Figure 10: Reliability on Order Execution 13 Figure 11: Information Quality Xetra 14 Figure 12: Order Execution Xetra 14 Figure 13: Platform Technology Xetra 14 Figure 14: Information Quality Frankfurt Floor 15 Figure 15: Order Execution Frankfurt Floor 15 Figure 16: Platform Technology Frankfurt Floor (Peak Load Reliability) 15 Figure 17: Marks reg. Reliability on Order Execution 16 Figure 18: Trade Execution Efficiency 16 Figure 19: Votes reg. Clearing and Settlement Xetra 18 Figure 20: Votes reg. Clearing and Settlement Frankfurt Floor 18 Figure 21: Marks reg. Clearing and Settlement 19 Figure 22: Price Information Efficiency 19 Figure 23: Information Efficiency on Xetra 20 Figure 24: Information Efficiency Frankfurt Floor 20 Figure 25: Marks reg. Information Efficiency 21 Figure 26: Transparency 22 Figure 27: Votes reg. Information Speed Xetra 23 Figure 28: Votes reg. Information Speed Frankfurt Floor 23 Figure 29: Marks reg. Information Speed 23 Figure 30: Transaction Costs 24 Figure 31: Votes reg. Transaction Costs Xetra 24 Figure 32: Votes reg. Transaction Costs Floor 24 Figure 33: Marks reg. Transaction Costs 25 Figure 34: Liquidity 26 Figure 35: Total Turnover Equities Xetra, Floor and Other Floor Exchanges 27 Figure 36: Assessment of Liquidity 27 Figure 37: Trading Process 28 Figure 38: Votes reg. Information on Xetra 29 Figure 39: Votes reg. Order Execution Xetra 29 IV

7 Figure 40: Votes reg. Clearing and Settlement Xetra 30 Figure 41: Votes reg. Information Frankfurt Floor 30 Figure 42: Votes reg. Order Execution Frankfurt Floor 30 Figure 43: Votes reg. Clearing and Settlement Frankfurt Floor 30 Figure 44: Marks reg. Trading Process 31 Figure 45: Result Survey Xetra and Frankfurt Floor 32 V

8 1 Introduction The most liquid German Floor Exchange (Frankfurt) faced severe changes in the organisation of the trading process as well as in the organisation of the stock market itself. In May 2011 the price fixing left the Frankfurt Floor Exchange and was transmitted to the automated Xetra Frankfurt Specialist Trading Platform (price fixing: continuous auction with specialist). The trading floor changed considerably during the more than 400 years of its existence. Derived from a bill exchange in the 15th century 1 the Frankfurt Floor Exchange was the leading floor exchange in Germany. Securities were traded with open-outcry, via phone or computer systems. Prices on the floor were fixed by brokers using the BOSS BOEGA computer system provided by Deutsche Börse AG. In the recent past, to keep up with Xetra s speed, brokers used quote machines that issued quotes and were able to fix prices automatically. The development of an electronic market started in 1991 when IBIS (Integriertes Boersenhandels- und Informationssystem) was launched with a reduced range of shares. 2 Following IBIS was Xetra (Exchange Electronic Trading) in 1997, a computerised trading platform that works purely order driven (bid and ask limits determine the price when they correspond, without an intermediary who steps in between). The basic targets for Deutsche Börse AG to develop Xetra were: high liquidity, transparency, locationindependent market access and frictionless trading. 3 After only four years Xetra had taken over according to market share and since then has continued to increase its importance for the German Stock market. One could have expected that once a supposedly superior electronic trading system had been introduced, floor trading would run out relatively near-term automatically (due to market participants choice) or by stock exchange decision. This however was not the case. Instead parallel trading on Xetra and Frankfurt Floor lasted for 13 years. In this context several questions appear that this study tries to answer: How efficient are the two equity trading platforms? Was it appropriate to end Frankfurt Floor trading? Why did investors still trade on Frankfurt Floor long after Xetra had been introduced? The reason might be that there are aspects where Frankfurt Floor is better or at least equal to Xetra. The question is in what aspects? For instance the Quote (bid and ask limit with volume) on Frankfurt Floor might be better than the best bid and ask limit on Xetra and for big size trades the maximum costs are lower. Splitting a big size order and placing it on several market places can reduce the market impact and might be another reason Cf. Lorenz, O. (2004): p. 17 f. Cf. Claussen, C. (1996): p. 245 ff. Cf. Bosch, R. (2001): p

9 Figure 1: Market Share Xetra, Frankfurt Floor and Other Floor Exchanges (Databasis: Deutsche Börse Group Factbook ) 4 Xetra s influence is not only visible in its market share but also in the absence of traders on the Frankfurt Floor Exchange trading floor. Figure 1 gives an overview concerning the development of the market shares of the existing Platforms. Floor brokers were the only human beings left on the former place of physical gathering where traders came together to make the market. Their role had been reduced to liquidity providers who support the electronic price fixing. The efficiency of Xetra had become a role model for the Frankfurt Floor and was often discussed during the meetings between Deutsche Börse AG, legal body of the Frankfurt Floor Exchange, and the broker houses assigned with price fixing on Frankfurt Floor. The transformation (May 2011) of floor trading with men-made price fixing onto the computerised platform under the proposition of efficiency was the central aspect of a survey for this paper that took place from December 2010 to January 2011 on a platform especially provided for this purpose. So the survey took place in the highly developed end phase of Frankfurt Floor Trading. On that website professional investors were asked to share their point of view concerning the efficiency of equity trading platforms and answer various questions to figure out what platform they prefer and for what reason. Although private investors were able to participate in the survey in a special section, they were asked different questions since commonly private investors cannot directly access the trading platforms in question. Due to that their votes were not taken into account for the outcome of the survey. More detailed information on the survey will be served in chapter 4 of this script. Throughout the world computerised trading is on the advance and most stock exchanges have become partially or fully computerised markets where former floor brokers have become market makers and the price fixing is done by computer systems (e. g. the London Stock Exchange with the Stock Exchange Automated Quotation System). The end of floor trading in Frankfurt might just provide a glance on a possible future for all floor brokers 4 Cf. Deutsche Börse Group (2000): p. 34; (2001): p. 16; (2002): p. 13; (2003): p. 15; (2004): p. 15; (2005): p. 14; (2006): p. 14; (2007): p. 14; (2008): p. 14; (2009): p

10 and floor traders left on stock exchanges in Germany and for all floor brokers on stock exchanges worldwide (most prominently the NYSE (New York Stock Exchange)). Presumably not only equity but also commodity exchanges may face these changes in price fixing processes in the future. There might not only be positive aspects to that development. The drawbacks of partially and entirely computerised markets flashed on the 6 th of May 2010 on the NYSE. The Dow Jones Index was about to face the biggest drop (according to points) in its history. The Dow Jones Index dropped from about 10,900 to 9,875 points. The downward trend ended after several minutes and the Dow Jones recovered to 10,510 points. Unique to the more of one hundred years of the existence of the Dow Jones Index about 1,000 billion $ market value were burned on the computerised trading systems in 15 minutes for no visible reason. Despite the crisis in Greece etc. and the concerns about the stability of the Euro, computerised trading systems were soon in the focus of critique. By selling positions or betting on further dropping prices they forced the prices down. Second to that the speed difference in price building between the trades at NYSE and the computerised trading led to a collapse of the price building system. The pressure to sell was increased due to orders that were transferred to other trading platforms. At third algorithmic traders left the market because of the instability. The resulting sudden shortage on liquidity led the market further downward. 5 This development particularly questions the peak load reliability of different equity trading platforms. 5 Cf. Bräuer, S. (2010): p

11 2 Brief Theoretical Background The term efficiency usually stands for reaching a high grade of target achievement with a given input or reaching a given target achievement with minimum input. 6 Besides allocating capital 7, stock markets have an important transformative function. The needs of capital demanders are transformed according to the needs of capital providers. Securitization transforms the needed capital according to temporal, risk and budget preferences (term transformation, risk transformation, lot-size transformation). 8 In order to understand how stock markets work, price building is an issue. Generally, the price fixing works order driven by supply and demand meeting. 9 A share price therefore can be described as the striving for a temporary equilibrium. Next to that different theories exist that try to describe influencing factors on the evaluation of securities, portfolio selection and stock price movement such as the Portfolio Selection Model 10, the CAPM (Capital Asset Pricing Model) 11, the APT (Arbitrage Pricing Theory) 12, the EMH (Efficient Market Hypothesis) 13, the Random Walk Hypothesis 14 and Behavioural Finance 15. Looking at the motivation to participate on a stock market commonly three kinds of motives can be described: hedging, speculation and arbitrage. Hedging means to secure oneself against losses. This is done by building a second position that partially or entirely covers eventual losses in the primary position. 16 Speculation aims at entering a position (in absence of a pre-existing position) to profit by anticipating price changes. 17 Arbitrage means that price differences in the same security at different markets or different time Cf. Bienert, H. (1996): p. 13 f. Cf. Stobbe, A. (1991): p. 278 ff. Cf. Schulte, J. (2001): p. 16 f. Cf. Mankiw, N. G. (2004): p. 69 ff. Cf. Perridon, L.; Steiner, M. (2004): p. 265 ff.; The Portfolio Selection Model / Theory was elaborated by H. Markowitz in It shows that the risk of a single investment can be reduced through diversification via investments in additional assets that are not perfectly correlated to each other. The Portfolio Selection Model laid the basis for the modern capital market theory (CAPM; see below). Cf. Perridon, L.; Steiner, M. (2004): p. 22; the CAPM is a capital market model based on the Portfolio Selection Theory. According to the CAPM the (expected) return of a risky asset (e.g. a share) can be explained with the return of a risk-free investment possibility, the (expected) market return and the market risk. The relative risk of a risky asset in relation to the market is expressed through a beta-factor. The CAPM can be used to build efficient portfolios. Cf. Ross, S. A. (1976): p. 341 ff.; as an alternative to the CAPM the APT explains the return of risky assets as a linear function of various micro- and/or macroeconomic risk factors. Cf. Yusopov, T. (2008): p. 6 ff.; The EMH is a theory that deals with information efficiency. According to Fama three levels of efficiency can be distinguished: weak (only historical information is reflected in prices), semi-strong (prices reflect information from past, present and future estimations, but only for public data) and strong efficiency (like semi-strong but including non-public information). If a market is strong efficient nobody can earn (ongoing) above market returns. Cf. Perridon, L.; Steiner, M. (2004): p. 221 f.; The Random Walk Hypothesis goes back to mathematicians Pascal, Fermat and Bernoulli and is based on the assumption of (strong) efficient markets. It describes that past events (like the results of tossing a coin) cannot be of help to predict the future. The result is that e.g. stock prices follow a random walk and price changes are caused through new information only. The Random Walk Theory is questioned by those claiming market inefficiencies. Cf. Vogt, S. (2008): p. 3 f.; Behavioural financial theory (e.g. Kahnemann, Tversky, Simon) questions the homo oeconomicus is taking into consideration psychological, emotional and social factors to understand and describe human (investment) decisions. Cf. Beilner, T.; Mathes, H. D. (1990): p Cf. Steinmann, G. (1970): p. 4. 4

12 lines are used to gain a profit at theoretically no or close to no risk. These motives can be combined and all of them can occur even in a single trade. Special market participants are market makers (who provide liquidity in certain stocks for a reduction of trading fees they pay for trading on that market) 18, designated sponsors (who provide liquidity on illiquid papers on Xetra and receive payment for that service) 19 and brokers (who fix prices and provide liquidity on floor exchanges and receive a broker's fee for that). 20 Furthermore market participants can be divided into private and institutional investors. Institutional investors are usually corporate bodies with at least some persons experienced in investing and managing portfolios. In Germany there exist seven floor exchanges: Berlin (B), Düsseldorf (D), Frankfurt am Main (F), Hamburg (H), Hannover (Hn), Munich (M), Stuttgart (S). Further Xetra, a computerised trading platform and, since MiFID (Markets in Financial Instruments Directive), several MTFs (Multilateral Trading Facilities) are most often bank driven alternative trading platforms) such as Turquoise 21, Chi-X 22, Tradegate 23 or Bats 24. In this context of stock market functions, price building, portfolio theory, market participants, their trading motives and competing stock exchanges / stock trading platforms, the investigation and survey reg. efficiency criteria on Frankfurt Floor and Xetra was undertaken Cf. Theissen, E. (2002) : p. 4. Cf. Bosch, R. (2001): p. 45. Cf. 27 and 28 BörsG (Börsengesetz). Cf. Turquoise Launches Derivatives Platform (w/o y.): w/o p., last access: Turquoise is a UK based multilateral trading facility that offers trading in mainly dark- pool order books for selected equities and derivatives (about 2,000 securities are currently tradable). Cf. Chi-X Europe (w/o y.): w/o p., last access: Chi-X Europe was launched in 2007 as a pan-european equity multilateral trading facility. It was designed to offer its members trading in equities, ETFs (Exchange Traded Funds), ETCs (Exchange Traded Commodities and IDRs (International Depositary Receipts) in both visible and non-displayed order books. Cf. Tradegate Exchange (w/o y.): w/o p., last access: Tradegate started in 2001 as a multilateral trading facility. In 2009 Tradegate became an official Stock Exchange. The focus is on private investors. Tradable securities there are equities, ETFs, bonds and selected investment funds. Cf. BATS US Stock Exchanges (w/o y.): w/o p., last access: Bats Exchange is currently the third largest US Securities Exchange with about 10 % market share in US Equities. Further Bats operates a multilateral trading facility based in London, UK covering about 5 % of the overall Europe market. 5

13 3 Functions and Efficiency Criteria of Equity Trading Platforms Three primary functions of stock exchanges consist in the allocation function, the informative function and the operative function. From these functions different efficiency criteria were derived as can be seen on the following figure: Figure 2: Functions and Efficiency Criteria of Equity Trading Platforms The allocation of capital is regarded as efficient when the money reaches those who provide the highest return. 25 The information level is fully considered as efficient when prices reflect all public and non-public information at all times. 26 Stock markets achieve a bundling of information into prices. The assumption is that information is spread under the market participants, and by pricing, this information is aggregated and made known to all market participants. The operative function of stock markets deals with the transformative abilities of securitization that is the foundation of any equity trading platform. Further it makes trading possible at low costs due to the organisation of the trading process Cf. Bienert, H. (1996): p. 15. Cf. Fama, E. F. (1970): p Cf. O Hara, M. (1997): p. 268 f. 6

14 The investigation on efficiency criteria starts with the Allocation Tree, shown on figure 3: Figure 3: Allocation Tree At first price building is compared with the result that it works slightly different (Xetra is purely order driven whereas on Frankfurt Floor the broker influences the price by his quote). Xetra works a bit faster but Frankfurt Floor has smaller spreads at least in less liquid shares due to the performance criteria for floor brokers. Risk allocation works on both platforms and is not further pursued in the investigation and in the survey since it deals with the ability of an investor to place his capital according to his risk preference. On both platforms a wide variety of shares and securities is traded so that the majority of investors will be able to allocate its funds according to its risk profile. Reliability on Order Execution deals with the risks an investor faces until the order is executed and settled. The investor has basically three risks: an information risk, an execution risk and an operational risk. The information risk describes price impacts due to incomplete, outdated or wrong information. 28 The execution risk refers to improper handling of the order for instance caused by the commission agent. 29 The operational risk refers to technical errors (independently from the commission agent), like wrong transmissions or wrong matching. 30 Trade execution efficiency, the remaining part of the tree, deals with the speed and safety of clearing and settlement systems. 31 A quick process reduces uncertainty and shortens the commitment period. 32 The safety of order settlement splits in the trustworthiness of the counterparty and an operational risk that comes from functional errors during the settlement process Cf. Peiseler, E. (1990): p. 139 f. Cf. Peiseler, E. (1990): p. 144 ff. Cf. Bittner, C. (2001): p. 44 ff. Cf. Securities and Exchange Commission; Division of Market Regulation (1988): p. 10. Cf. Brealey, R. Ireland, J. (1995): p. 9 ff. Cf. Alfes, A. (2005): p. 60 f. 7

15 Following the allocation function the next figure shows the information tree with price information efficiency and transparency: Figure 4: Information Tree Price information efficiency stands for the level and detail of information that is reflected by the prices. According to the EMH (Efficient Market Hypothesis) the level of information efficiency can be weak, semi-strong and strong. A weak level means that only public data from the past are reflected in the prices. On the semi-strong level the prices reflect information from past, present and even future estimations but only for public data. A strong level of information efficiency means that public and non-public data are priced in from all three time levels (past, present and future). 34 Transparency is a measure for quantity and quality of trading information the system provides. 35 It splits in ex ante transparency (information about orders that are not yet executed) 36 and ex post transparency (information about orders already executed) Cf. Fama, E. F. (1970): p. 385 ff. Cf. Rudolph, B. (1994): p Cf. Madhavan, A. (2000): p. 33. Cf. Schwartz, R. A. (1993): p

16 The third and last function is represented by the Operation tree: Figure 5: Operation Tree The selective function depends on the investor. As long as a certain variety of different securities is traded on an equity trading platform an investor should be able to select and invest in the securities with the highest possible return. This was not tested within this survey because both platforms provide this variety. The transformative functions (risk, lot-size and term transformation) are not dependent on the trading platform but on the securitization. Therefore these functions are not further pursued in the investigation or in the survey either. 38 Transaction costs stand for the costs an investor is confronted with doing a trade. 39 They are split in direct and indirect costs. 40 Direct costs consist of costs occurring for accepting and executing orders (e. g. commission fees, floor broker fees, clearing fees and taxes). Direct costs can be further divided into fixed and variable components. 41 Fixed components are taxes, broker fees and clearing and settlement fees 42 whereas commission fees are most often variable. 43 Indirect costs refer to the spread between actual price and hypothetical equilibrium price Cf. Von Rosen, R. (2001) : p. 356 f. Cf. Picot, A. (1982): p Cf. Gerke, W.; Rapp, H. W. (1994): p. 12. Cf. Schwartz, R. A. (1993): p. 732 ff. Cf. Schiereck, D. (1995): p. 21. Cf. Hansch, O.; Neuberger, A. J. (1995): p Cf. Scheffrahn, R. (1992): p. 49 f. 9

17 Liquidity means the ability to transform assets in cash. 45 Liquidity in the context of stock trading means the possibility to buy or sell a security at any given time and with any given size, without paying a premium to the market price. 46 Based on the Trading Process the following phases can be derived: initiation, order routing, execution, clearing and settlement. The initiation phase (before the order has been issued) stands for gathering and assessing information to evaluate a security. Today usually special information systems like Reuters or Bloomberg provide this information. Display panels, tickers and the talk with other traders and brokers can be considered as more traditional sources of information. 47 In the order routing phase bid and ask limits are directed to the place of execution. This can be done by typing the order into a computer, face-to-face or via notes. 48 In the execution phase the price fixing takes place. 49 In the clearing and settlement phase the transaction is verified and settled. Clearing means determining the obligations of the involved parties. Settlement stands for the regulation of transferring the shares and the money Cf. Peridon, L.; Steiner, M. (2004): p. 10 f. Cf. Hasbrouck, J. (1990) p.232; Black, F. (1971): p. 29 f. Cf. Bortenlänger, C. (1996): p. 66 ff. Cf. Bortenlänger, C. (1996): p. 79 f. Cf. Deubel, A. (2009): p. 18. Cf. Abel, K. (1998): p

18 4 Expected Results versus Survey 4.1 Structure of the Empirical Study The survey took place from December 2010 to January 2011 on the platform (exclusively provided for this survey) with a total of 131 professional investors who answered the questions in order to assess the researched efficiency criteria. Where possible the participants ranked their answers according to the German school marks (ranging from 1 = excellent to 6 = poor). The results formed an average school mark for each category. In the case of a criterion consisting of several questions like for example the Trading Process, the average school marks from all criteria involved were taken to form an overall average. Further the authors weigh investigative arguments that argue for or against a platform and rank the platform with a plus (+) if it is supposed to perform better than the other platform, with a minus (-) if it is supposed to perform less well and with a zero (0) if pros and cons should even out. 4.2 The Allocation Function Price building is the first point being looked at under the allocation tree. Price Building: Figure 6: Price Building Price building works different on both platforms. Therefore prices and temporal market equilibriums may differ on them. Xetra is strictly order driven with a semi-open order book (that means the ten best bid and ask limits can be seen by the market participants) and Frankfurt Floor relies on quotes issued by brokers (closed order book: only the broker sees the order book whereas other market participants only see the quote). Price building on Xetra is faster since there is no human intermediary who needs to check the situation first before fixing the price. In Frankfurt brokers have to stick to performance criteria (according to FSE (Frankfurt Stock Exchange) rules to measure the broker s quality) including spread sizes. Therefore spreads can be smaller on Frankfurt Floor. Prices usually differ not that much because Frankfurt quotes according to the market with the biggest liquidity, that usually is Xetra. Hence, prices on Xetra and Frankfurt Floor usually do not 11

19 differ to a great extent (reasons for that are arbitrage, prevention from arbitrage and the guidance that comes from Xetra as the most liquid market). As shown in figures 7 and 8 Xetra received most voting on the good and satisfactory marks. For Frankfurt Floor the voting was more widespread, ranging from Excellent to Poor. Thus, Xetra leads with an overall mark of Xetra: Frankfurt Floor: Figure 7: Pricing Quality Xetra (Survey Data) Figure 8: Pricing Quality Frankfurt Floor (Survey Data) There are several assumptions that could explain the gap of almost one full mark between Xetra and Frankfurt Floor as shown in figure 9: Figure 9: Marks reg. Price Building First, because the broker sees who inserts limits in his order book he can guess on an order. Guessing means: if for instance a bank inserts limits and orders only on one side, 12

20 the floor broker will be in a position to draw assumptions reg. the intentions behind these limits and may estimate further future orders. Second, the broker may change the quote and thus not stick to the first offer he made. Third, the investor has no insight in the order book on Frankfurt Floor. He has to rely on the correctness of the broker s quote. Reliability on order execution is the second point being looked at under the allocation tree: Reliability on Order Execution: Figure 10: Reliability on Order Execution Executing an order is a process full of uncertainties for every investor from the point when the investor places the order to the point when he receives the legally valid affirmation. These order execution risks can influence the target achievements of the investor both positively and negatively. Negative influences may result in losses or in higher costs of opportunity. Therefore it is of key importance for providers of security trading systems to have an execution and settlement system that provides the highest security along with a maximum of reliability. 51 Security means in this case the absence of risk or being sure of the occurrence of certain aspects. 52 Transferring this to the settlement of security trades means handling the transaction as ordered with as few uncertainties as possible. Reliability on order execution basically offers three risks: an information risk, an execution risk and an operational risk. Due to the semi open order book Xetra offers advantages in terms of information risk. A quote can be accidentally wrong (mistyped) or wrong on purpose (to give a wrong impression of the actual order book situation). Furthermore being able to see several limits on Xetra the investor is provided with more information and is enabled to do a better assessment of the situation Cf. Schüller, B. (1991): p. 558 ff. Cf. Perridon, L.; Steiner, M. (2004): p. 98 ff. 13