Trade-throughs in European cross-traded equities after transaction costs – empirical evidence for the EURO STOXX 50

This paper investigates the accuracy and heterogeneity of output growth and inflation forecasts during the current and the four preceding NBER-dated U.S. recessions. We generate forecasts from six different models of the U.S. economy and compare them to professional forecasts from the Federal Reserve’s Greenbook and the Survey of Professional Forecasters (SPF). The model parameters and model forecasts are derived from historical data vintages so as to ensure comparability to historical forecasts by professionals. The mean model forecast comes surprisingly close to the mean SPF and Greenbook forecasts in terms of accuracy even though the models only make use of a small number of data series. Model forecasts compare particularly well to professional forecasts at a horizon of three to four quarters and during recoveries. The extent of forecast heterogeneity is similar for model and professional forecasts but varies substantially over time. Thus, forecast heterogeneity constitutes a potentially important source of economic fluctuations. While the particular reasons for diversity in professional forecasts are not observable, the diversity in model forecasts can be traced to different modeling assumptions, information sets and parameter estimates. JEL Classification: G14, G15, G2

Mutual information based clustering of market basket data for profiling users

Attraction and commercial success of web sites depend heavily on the additional values visitors may find. Here, individual, automatically obtained and maintained user profiles are the key for user satisfaction. This contribution shows for the example of a cooking information site how user profiles might be obtained using category information provided by cooking recipes. It is shown that metrical distance functions and standard clustering procedures lead to erroneous results. Instead, we propose a new mutual information based clustering approach and outline its implications for the example of user profiling

IT-Driven Execution Opportunities in Securities Trading: Insights into the Innovation Adoption of Institutional Investors

Technological innovations change the intermediation relationships within securities trading. Thus, thequestion arises which factors drive or hinder their adoption. This paper develops a model to evaluateinstitutional investors\u27 intentions to adopt the meta-technology we call non-delegated order handling.It focuses on the usage of IT-driven trading systems which enable investors to control the choice oftrading venue, order slicing, and timing themselves instead of delegating the execution of stocktrading to an intermediary. Therefore the theory of task-technology-fit is integrated into thetechnology acceptance model. Further, it was successfully tested on data from the largest Europeaninstitutional investors. The results outline that the perceived fit among the system‟s capabilities andindividual trading requirements is the main driver for adoption. Secondly, performance expectationsfuel the intention to use trading innovations. Thirdly, for the expected efforts only a weak effect couldbe shown. Finally, factors like contractual barriers and competitive pressure which investors cannotcontrol do not substantially affect their adoption decision

Assessing IT-Supported Securities Trading: A Benchmarking Model and Empirical Analysis

Information technology plays a major role to support the process of securities trading. Tactical trading decisions can be implemented more efficiently by gaining access to alternative trading systems, which provide access to additional liquidity and potentially better execution prices. This paper explores the business value provided by to so-called dark pools of liquidity, which can be accessed by adjusting the trading process and adopting new IT. With limited access to large investors, dark pools represent alternative trading systems with a focus on very large volumes between selected institutions. We aim at exploring the potential business value provided to investors deciding to implement the necessary requirements. Therefore, a benchmarking approach is presented to compare dark pool executions with prices which were available at traditional stock exchanges. The empirical results provide evidence for significant price improvements which can be realized when gaining access to darks pools, especially when trading very large orders

An Order-Channel Management Framework for Institutional Investors

Efficient Order-Channel Management, i.e. the process of information gathering, evaluation, decision and control regarding the setup of the overall trading infrastructure and the actual order routing implementation plays a crucial role for trading success as well as the competitiveness of Institutional Investors. This article introduces a framework intended to support Institutional Investors in establishing an individual Order-Channel Management (OCM). For this overall goal, OCM is decomposed into its strategic and operational constituents and the involved key entities, parameters, processes and their interdependencies are outlined. Based on the identified properties, a framework is derived that aims at identifying a suitable mapping from order characteristics to execution venues.

The Impact of a Millisecond: Measuring Latency Effects in Securities Trading

In the course of technological evolution security markets offer low-latency access to their customers. Although latency figures are used as marketing instruments, only little research sheds light on the means of those figures. This paper provides a performance measure on the effect of latency in the context of the competitive advantage of IT. Based on a historical dataset of Deutsche Börse’s electronic trading system Xetra an empirical analysis is applied. That way we quantify and qualify the impact of latency from a customer’s point of view

Order-channel management in institutional equity trading: a framework for IT-driven trading innovations

IT-driven trading innovations offer institutional investors alternative trading channels to broker delegated order handling. Motivated by the impact on intermediation relationships in securities trading and the adoption rate of such trading channels, the new option of self-directed order handling is analyzed. To capture the prerequisites for institutional investors to insource their order handling, an order-channel management (OCM) framework is introduced. It is based on a structural approach to account for the increasing complexity in comparison to traditional intermediary services. Drivers for the adoption of an OCM framework are investigated from the strategic perspective. Operational OCM is based on the business value of IT analysis of distinct trading innovations. It includes smart order router technology, low latency technology as an upgrade for existing IT-driven trading channels as well as negotiation dark pools, representing alternative trading venues. Evidence that all investigated IT-driven trading innovations generate additional business value is provided as one result. However, it is also shown that they exhibit entry barriers tightly related to investor size. Further, Task-Technology Fit is proven to be the major driver for the adoption decision. Consequently, IT-driven trading innovations should increase trading control, satisfy high anonymity and varying urgency demands.IT-getriebene Handelsinnovationen eröffnen institutionellen Investoren neben der Delegation ihrer Handelsaufträge an Broker alternative Ausführungskan.le. Diese Arbeit untersucht die neue Möglichkeit einer selbstbestimmten Auftragsbearbeitung. Die Analyse ist durch den starken Einfluss auf die Intermediationsbeziehungen im Wertpapierhandel sowie die weite Verbreitung neuer IT-getriebener Handelskanäle motiviert. Um die notwendigen Voraussetzungen für das Einlagern (engl. Insourcing) des Handels institutioneller Investoren zu erfassen, wird ein Order-Channel Management (OCM) Framework vorgestellt. Im Vergleich zu traditionellen Intermediärsdiensten wächst dessen Komplexität. Um dem Rechnung zu tragen, wird ein strukturierter Ansatz verfolgt. Für die strategische Betrachtung werden Treiber für die Implementierung eines OCM Frameworks untersucht. Operationales OCM basiert auf einer Analyse des IT-Geschäftswertes ausgewählter Handelsinnovationen. Diese umfasst Technologien wie Smart Order Router, Niedriglatenztechnologie als Erweiterung von bereits existierenden elektronischen Handelskanälen sowie Negotiation Dark Pools als Repräsentanten von alternativen Handelsplattformen. Für alle genannten Handelsinnovationen wird deren Potential zur Schaffung zusätzlichen Geschäftswertes aufgezeigt. Dabei wird deutlich, dass Eintrittsbarrieren bestehen, die eng mit der Größe des Investors verbunden sind. Des Weiteren wird Task-Technology Fit als Haupttreiber für die Einführung identifiziert. Dementsprechend sollen IT-getriebene Handelsinnovationen die Ausführungskontrolle steigern, hohe Anonymität gewährleisten und Flexibilität gegenüber variierenden Dringlichkeiten aufweisen