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This paper investigates whether the stock market reacts to unsolicited ratings for a sample of S&P rated firms from January 1996 to December 2005. We first analyze the stock market reaction associated with the assignment of an initial unsolicited rating. We find evidence that this reaction is negative and particularly accentuated for Japanese firms. A comparison between S&P’s initial unsolicited ratings with previously published ratings of two Japanese rating agencies for a Japanese subsample shows that ratings assigned by S&P are systematically worse. Further, we find that the stock market does not react to the transition from an unsolicited to a solicited rating. Comparison of the upgrades in the sample with a matched-sample of upgrades of solicited ratings reveals that the price reactions are no different. In addition, abnormal returns are worse for firms whose rating remained unchanged after the solicitation compared to those for upgraded firms. Finally, we find that Japanese firms are less likely to receive an upgrade. Our findings suggest that unsolicited ratings are biased downwards, that the capital market therefore expects upgrades of formerly unsolicited ratings and punishes firms whose ratings remain unchanged. All these effects seem to be more pronounced for Japanese firms.
In this paper, we propose a model of credit rating agencies using the global games framework to incorporate information and coordination problems. We introduce a refined utility function of a credit rating agency that, additional to reputation maximization, also embeds aspects of competition and feedback effects of the rating on the rated firms. Apart from hinting at explanations for several hypotheses with regard to agencies' optimal rating assessments, our model suggests that the existence of rating agencies may decrease the incidence of multiple equilibria. If investors have discretionary power over the precision of their private information, we can prove that public rating announcements and private information collection are complements rather than substitutes in order to secure uniqueness of equilibrium. In this respect, rating agencies may spark off a virtuous circle that increases the efficiency of the market outcome.
Using data of US domestic mergers and acquisitions transactions, this paper shows that acquirers have a preference for geographically proximate target companies. We measure the ‘home bias’ against benchmark portfolios of hypothetical deals where the potential targets consist of firms of similar size in the same four-digit SIC code that have been targets in other transactions at about the same time or firms that have been listed at a stock exchange at that time. There is a strong and consistent home bias for M&A transactions in the US, which is significantly declining during the observation period, i.e. between 1990 and 2004. At the same time, the average distances between target and acquirer increase articulately. The home bias is stronger for small and relatively opaque target companies suggesting that local information is the decisive factor in explaining the results. Acquirers that diversify into new business lines also display a stronger preference for more proximate targets. With an event study we show that investors react relatively better to proximate acquisitions than to distant ones. That reaction is more important and becomes significant in times when the average distance between target and acquirer becomes larger, but never becomes economically significant. We interpret this as evidence for the familiarity hypothesis brought forward by Huberman (2001): Acquirers know about the existence of proximate targets and are more likely to merge with them without necessarily being better informed. However, when comparing the best and the worst deals, we are able to show a dramatic difference in distances and home bias: The most successful deals display on average a much stronger home bias and distinctively smaller distance between acquirer and target than the least successful deals. Proximity in M&A transactions therefore is a necessary but not sufficient condition for success. The paper contributes to the growing literature on the role of distance in financial decisions.
The paper examines challenges in effectively implementing the lender-of-last-resort function in the EU single financial market. Briefly highlighted are features of the EU financial landscape that could increase EU systemic financial risk. Briefly described are the complexities of the EU’s financial-stability architecture for preventing and resolving financial problems, including lender-of-last-resort operations. The paper examines how the lender-of-last-resort function might materialize during a systemic financial disturbance affecting more than one EU Member State. The paper identifies challenges and possible ways of enhancing the effectiveness of the existing architecture.
Location-based services (LBS) are services that position your mobile phone to provide some context-based service for you. Some of these services – called ‘location tracking’ applications - need frequent updates of the current position to decide whether a service should be initiated. Thus, internet-based systems will continuously collect and process the location in relationship to a personal context of an identified customer. This paper will present the concept of location as part of a person’s identity. I will conceptualize location in information systems and relate it to concepts like privacy, geographical information systems and surveillance. The talk will present how the knowledge of a person's private life and identity can be enhanced with data mining technologies on location profiles and movement patterns. Finally, some first concepts about protecting location information.
Mobile telephony and mobile internet are driving a new application paradigm: location-based services (LBS). Based on a person’s location and context, personalized applications can be deployed. Thus, internet-based systems will continuously collect and process the location in relationship to a personal context of an identified customer. One of the challenges in designing LBS infrastructures is the concurrent design for economic infrastructures and the preservation of privacy of the subjects whose location is tracked. This presentation will explain typical LBS scenarios, the resulting new privacy challenges and user requirements and raises economic questions about privacy-design. The topics will be connected to “mobile identity” to derive what particular identity management issues can be found in LBS.
In this paper, I examine the potential of mobile alerting services empowering investors to react quickly to critical market events. Therefore, an analysis of short-term (intraday) price effects is performed. I find abnormal returns to company announcements which are completed within a timeframe of minutes. To make use of these findings, these price effects are predicted using pre-defined external metrics and different estimation methodologies. Compared to previous research, the results provide support that artificial neural networks and multiple linear regression are good estimation models for forecasting price effects also on an intraday basis. As most of the price effect magnitude and effect delay can be estimated correctly, it is demonstrated how a suitable mobile alerting service combining a low level of user-intrusiveness and timely information supply can be designed.
Multiplayer games have become very popular in the PC market. Almost none of the current games are shipped without some support for multiplayer gaming. At the same time mobile devices are becoming more powerful and popularity of games on these platforms increases. However, there are almost no games that support multiplayer gaming despite the multiple options of these devices to connect with each other and build mobile ad hoc networks. Reasons for this lack of multiplayer support are the high diversity of mobile devices as well as the different protocols and their properties that these devices support. With “SmartBlaster” we developed a multiplayer game for several different platforms that is using several different channels (Bluetooth, IrDa, 802.11 and other networks supporting TCP/IP) to communicate between them.
Die vorliegende Analyse untersucht die Beschäftigungseffekte von Vermittlungsgutscheinen und Personal-Service-Agenturen mit Hilfe einer makroökonometrischen Evaluation. Neben einer mikroökonometrischen Evaluation, welche die Wirkungen auf individueller Ebene untersucht, kann eine makroökonometrische Analyse Aussagen über die gesamtwirtschaftlichen Effekte der Maßnahmen machen. Die strukturellen Multiplikatorwirkungen im makroökonomischen Kreislaufzusammenhang werden jedoch nicht berücksichtigt. Das ökonometrische Modell zur Analyse der beiden Maßnahmen basiert auf einer Matching-Funktion, die den Suchprozess von Firmen und von Arbeitern nach einem Beschäftigungsverhältnis abbildet. Die empirischen Analysen werden getrennt für Ost- und Westdeutschland sowie für die Strategietypen der Bundesagentur für Arbeit durchgeführt. Sie zeigen, dass die Ausgabe von Vermittlungsgutscheinen nur in „großstädtisch geprägten Bezirken vorwiegend in Westdeutschland mit hoher Arbeitslosigkeit“ (Strategietyp II) einen signifikant positiven Effekt auf den Suchprozess hat. Für die Personal-Service-Agenturen zeigen sich signifikant positive Effekte für Ost- als auch für Westdeutschland. Allerdings fehlt für eine abschließende Bewertung der Ergebnisse für die Personal- Service-Agenturen aufgrund der relativ geringen Teilnehmerzahl noch ein Vergleich mit mikroökonometrischen Analysen.
Serial correlation in dynamic panel data models with weakly exogenous regressor and fixed effects
(2005)
Our paper wants to present and compare two estimation methodologies for dynamic panel data models in the presence of serially correlated errors and weakly exogenous regressors. The ¯rst is the ¯rst di®erence GMM estimator as proposed by Arellano and Bond (1991) and the second is the transformed Maximum Likelihood Estimator as proposed by Hsiao, Pesaran, and Tahmiscioglu (2002). Thereby, we consider the ¯xed e®ects case and weakly exogenous regressors. The ¯nite sample properties of both estimation methodologies are analysed within a simulation experiment. Furthermore, we will present an empirical example to consider the performance of both estimators with real data. JEL Classification: C23, J64