174 research outputs found
Automated ANN alerts : one step ahead with mobile support
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
Automated ANN alerts: one step ahead with mobile support
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
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
Assessing customers' value of mobile financial information services: empirical-based measures
TAXONOMY DEVELOPMENT IN INFORMATION SYSTEMS: DEVELOPING A TAXONOMY OF MOBILE APPLICATIONS
The complexity of the information systems field often lends itself to classification schemes, or taxonomies, which provide ways to understand the similarities and differences among objects under study. Developing a taxonomy, however, is a complex process that is often done in an ad hoc way. This research-in-progress paper uses the design science paradigm to develop a systematic method for taxonomy development in information systems. The method we propose uses an indicator or operational level model that combines both empirical to deductive and deductive to empirical approaches. We evaluate this method by using it to develop a taxonomy of mobile applications, which we have chosen because of their ever-increasing number and variety. The resulting taxonomy contains seven dimensions with fifteen characteristics. We demonstrate the usefulness of this taxonomy by analyzing a range of current and proposed mobile applications. From the results of this analysis we identify combinations of characteristics where applications are missing and thus are candidates for new and potentially useful applications.taxonomy, design science, mobile application
What Drives the Helpfulness of Online Product Reviews? From Stars to Facts and Emotions
For consumers, online product reviews have become an important source for product-related information. Furthermore, they represent a beneficial addition to online retailers’ websites. Due to the increasing amount of available product reviews, identifying the most helpful product reviews represents an important task in order to reduce information overload. Therefore, the factors influencing review helpfulness have to be identified. Thus, in order to explain Review helpfulness, we build upon and extend review diagnosticity theory with concepts from marketing research and propose a research model that includes product quality, review sentiment and review uncertainty. Based on a sample of amazon.com product reviews, we evaluate our research model and find that statements about product quality positively influence review helpfulness. Furthermore, we identify that sentiment as well as uncertainty expressed in product reviews have an impact on review helpfulness. Finally, we confirm that the product category has a moderating effect on these relationships
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