INTRODUCTION

In securities trading, different trading intentions are aggregated at exchanges to discover prices. Until the late 1980s, this process has been conducted by direct human interaction at exchange floors. Then, new trading concepts originated from an IT-driven transformation of trading (Schwartz and Francioni 2004). Following Hitt and Brynjolfsson (1996) we measure the potential to generate value of one such IT concept called Smart Order Router (SOR).

The focus of our analysis is the entire securities trading value chain. Starting from the investment decision it includes all required stages up to the legal transfer of ow-nership of traded securities (cf. upper horizontal flow path in figure 10): Trading is a traditionallyintermediated business (Harris 2003). Thus,investors (step 1) commu-nicate their trade interests to human brokers (step 2) who search for counterparties at exchanges to complete trades (step 3). Trade confirmations are communicated to post-trading infrastructure providers: In the clearing stage (step 4) settlement obligations are determined for each market participant towards all counterparties.

That way, clearing provides a risk management function and for efficiency reasons a pooling of multiple trades among counterparties to determine the surplus obligations (netting).Settlement (step 5) is “...the act of crediting and debiting the transferee’s and transferor’s accounts respectively, with the aim of completing a transaction in securities” (CESAME 2005, p. 5). It takes place at a Central Securities Deposito-ry (CSD). Custody (step 6) of shares as well as ownership information is provided by a CSD. For domestic settlement each country typically possesses its own CSD whereas International CSDs (ICSDs) enable access to foreign CSDs for international transactions.

1 INTRODUCTION

The focus of this paper relates to securities trading: here exchanges are places where different trade interests are aggregated to discover prices. Until the late 1980s trading has been conducted by direct human interaction on the floors of national stock exchanges. But within the last decades floor-based trading has undergone an IT-driven transformation towards fully automated electronic systems (Schwartz and Francioni, 2004). Many new trading strategies and concepts arose from this change.

According to Hitt and Brynjolfsson (1996) we concentrate on one IT concept called Smart Order Router (SOR) and measure its potential to generate value.

As SOR is intended to improve the trading process efficiency we draw attention to the entire securities trading value chain: starting from the investment decision it includes all required stages up to the legal transfer of ownership of the traded securities (cf. upper horizontal flow path in figure 1): trading is a traditionally intermediated business. Thus, investors (step 1) communicate their trade interests to human brokers (step 2) who are members at an exchange (Harris 2003). There, the broker searches for an adequate counterparty to complete a trade (step 3). Then, trade confirmations are communicated to a post-trading infrastructure provider supporting the three stages of clearing (step 4), settlement (step 5) and custody (step 6): in the clearing stage settlement obligations are determined for each market participant towards all counterparties. That way it provides a risk management function and for efficiency reasons a pooling of multiple trades among counterparties to determine the surplus obligations concerning share delivery and cash payments (netting). Settlement is “…the act of crediting and debiting the transferee’s and transferor’s accounts respectively, with the aim of completing a transaction in securities” (CESAME Sub-Group, 2005, p. 5) taking place at a Central Securities Depository (CSD). The custody of the traded shares as well as ownership information is provided by a CSD. For domestic settlement each country possesses its own CSD whereas International CSDs (ICSDs) enable access to foreign CSDs for international transactions.

Figure 1: Traditional securities value chain and changes induced by a SOR

The choice of security markets has become a US phenomenon when alternative trading systems (so called electronic communication networks) have been introduced at the end of the last century there (Schwartz and Francioni 2004). To enforce best (order) execution current US regulation (RegNMS) requires mandatory routing of orders from the market receiving the order initially to the one offering the best price. In contrast such obligations have not been in place in Europe. Before the Market in Financial Directive (MiFID) was introduced in November 2007 stock trading has been obligated to take place at national stock exchanges (concentration rule) in various European states. Thus, nearly all trading activity in a security has been conducted in its home market (home markets principle) (Schwartz and Francioni 2004). To foster competition and take advantage of technological developments, MiFID abolished these concentration rules. Besides traditional exchanges, this enables new markets like Chi-X, BATS or Turquoise, so called multilateral trading facilities (MTFs). Relevant market share gains of MTFs (Fidessa 2009) in European securities document increasing market

Figure 10: Traditional Securities Value Chain and Changes Induced by a SOR In the US, alternative trading systems have been introduced at the end of the last century, leading to a fragmentation of markets (Schwartz and Francioni 2004). To enforce best (order) execution, current US regulation (RegNMS) requires mandatory routing of orders from the market initially receiving the order to the one offering the best price. In Europe, no such obligations are in place. Before the Markets in Finan-cial Instrument Directive (MiFID) was introduced in November 2007, stock trading had to take place at national stock exchanges (concentration rule) in various

Euro-pean states. Thus, nearly all trading activity in a security was conducted in its home market (Schwartz and Francioni 2004). To foster competition and to take advantage of technological developments, MiFID abolished these concentration rules. Besides traditional exchanges, this enables the emerge of so-called multilateral trading faci-lities (MTFs) like Chi-X, BATS or Turquoise. Relevant market share gains of MTFs (Fidessa 2009) in European securities document increasing market fragmentation. To strengthen customer requirements for best execution, MiFID obliges intermediaries to execute customer orders on terms most favorable to the client, i.e. the investor.

Within the post-trading stages the European commission aims at fostering competi-tion as it has identified multiple cross-system barriers for cost efficiency (Giovannini Group 2001).

To implement best execution by intermediaries, two alternatives prevail: either to rely on pre-defined static order routing rules, mostly targeting only one market per security (e.g.: the national stock exchange or the respective security’s home market) or to employ a dynamic routing by an IT concept calledSOR (cf. appendix A.2 for a description of a SOR). Gomber et al. (2008) reveal best execution implementations to rely mostly on predefined, static routing rules and only a very low usage of real-time SOR solutions up to now. One reason might be the access to post-trading infrastructures: large institutions apply direct access (cf. step 6a in figure 10 whereas smaller ones require intermediaries to the foreign infrastructure by e.g. ICSDs (cf.

step 6b in figure 10) incurring high transfer costs. Therefore, the general question for the business value of SOR arises (Kohli and Grover 2008) and the two related research questions for this paper are:

(1) Is a static routing process efficient in fragmented European equity markets?

(2) Does SOR technology enable for relevant efficiency improvements within the trading process?

To answer these questions, we develop a general simulation framework for identifying sub-optimal order executions. It can be applied to public data and accounts for explicit costs associated with switching a trade from the original to a different market in European cross-system trading. To infer cost boundaries, two model users are assumed: One user for an intermediated high-cost scenario and another acting in a low-cost scenario with direct access to the respective post-trade infrastructures. Our framework is then validated on a sample of EURO STOXX 50 constituents.

Applied on a continuous basis our framework provides threefold insights: Firstly, intermediaries (brokers and trading desks of institutional investors) can assess the value generation potential of SOR systems on a net basis, i.e. including transaction costs. Secondly, investors can judge the relevance of SOR services for their interme-diary choice. Thirdly, regulators can evaluate the effectiveness of the MiFID best

execution provisions relative to the RegNMS regime. By comparing the gross (i.e.

excluding transaction costs) with the net results the impact of transaction costs, specifically those for clearing and settlement, on the order routing decision is shown.

The remainder of this paper is structured as follows: section 2 reviews related litera-ture, section 3 elaborates on the employed methodology and presents assumptions for the applied transaction cost scenarios. In section 4 the data set is described, followed by our results in section 5. Section 6 concludes.

2 Related Literature

Beside the particular perspective of electronic securities trading, this paper exhibits multiple cross-domain relations in information systems research:

We evaluate the business value of an IT concept with a focus on potential vs. realized value as defined by Chircu and Kauffman (2000). These value categories are used to analyze process-driven and market-driven value flows as well as unrealized value flows caused by barriers and limits affecting these processes. Davern and Kauffman (2000) differentiate between ex ante project selection and ex post investment evaluation in analyzing IT values. The potential value is construed as “business payoff expected from an ideal technology solution” (p. 133). As this perspective implies a corporate point of view Mooney et al. (1996) argue to“move away from firm-level output mea-sures, particularly financial meamea-sures, of business value in favour of process-oriented measures” (p. 77). This is substantiated by the limitation incurred by directly mea-suring at firm-level (but not at process-level) how and where business value is created by IT.

Weyland and Engiles (2003) highlight the ability of simulations to serve as a basis for business process optimization. Their results are backed by Yen (2008), who illustrate the impact of integrated process optimization for multi-criteria stakeholder process views. Amongst others, direct measurements and computer simulations are described.

Energy cost simulations of globally distributed computer centres by Qureshi et al.

(2009) prove possible economic gains of smart routing even outside financial markets.

Their results outline potential savings of 40% for data centers which dynamically route their workload to regions with low energy costs. For reliable smart routing simulations, Qureshi et al.’s (2009) analysis shows also the demand for a market scope instead of a firm perspective. At firm-level it is impossible to measure process efficiency for the entire market. On top, firms try to conceal their process strategies to retain their comparative advantages.

Regarding SOR technology in particular, Foucault and Menkveld (2008) argue sub-optimal trade executions on security markets to be induced by a lack of automated routing decisions. Empirical studies by Prix et al. (2007) as well as Gsell and Gomber (2009) investigate the impact of automated order flow on markets. They underline the high percentage of order flow originating from algorithmic trading. Further, Do-mowitz and Yegerman (2005) show the business value of algorithms by comparing

their overall trading costs with those of human brokers. On top, Bakos et al. (1999) highlight the importance of overall transaction costs.

This paper’s contribution to the existing literature is twofold: Firstly, it introduces a potential vs. realized value framework for order routing in fragmented markets.

Secondly, to the knowledge of the authors it is the first paper which empirically analyzes the trading process efficiency after the introduction of MiFID. That way, it includes switching costs (i.e. transactions costs), which are relevant for the European case.