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.

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Author:Jan MuntermannORCiDGND
Document Type:Report
Date of Publication (online):2006/01/18
Year of first Publication:2005
Publishing Institution:Universit├Ątsbibliothek Johann Christian Senckenberg
Release Date:2006/01/18
Tag:Artificial Neural Networks (ANN); Automated Mobile Customer Alerts; Event Study; Financial Decision Support; Financial Forecasting
GND Keyword:Mobile Telekommunikation / Electronic Commerce; Neuronales Netz; Informationssystem
Institutes:Wirtschaftswissenschaften / Wirtschaftswissenschaften
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
Licence (German):License LogoDeutsches Urheberrecht