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 abnor
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.
show moreshow less

Download full text files

Export metadata

  • Export Bibtex
  • Export RIS

Additional Services

    Share in Twitter Search Google Scholar
Metadaten
Author:Jan Muntermann
URN:urn:nbn:de:hebis:30-23932
Document Type:Working Paper
Language:English
Date of Publication (online):2006/01/18
Year of first Publication:2005
Publishing Institution:Univ.-Bibliothek Frankfurt am Main
Release Date:2006/01/18
SWD-Keyword:Informationssystem; Mobile Telekommunikation / Electronic Commerce ; Neuronales Netz
HeBIS PPN:135288096
Institutes:Wirtschaftswissenschaften
Dewey Decimal Classification:330 Wirtschaft
Sammlungen:Universitätspublikationen
Licence (German):License Logo Veröffentlichungsvertrag für Publikationen

$Rev: 11761 $