Towards Automated Event Studies Using High Frequency News and Trading Data

  • Nicolai Bohn
  • Fethi A. Rabhi
  • Dennis Kundisch
  • Lawrence Yao
  • Tobias Mutter
Conference paper

DOI: 10.1007/978-3-642-36219-4_2

Volume 135 of the book series Lecture Notes in Business Information Processing (LNBIP)
Cite this paper as:
Bohn N., Rabhi F.A., Kundisch D., Yao L., Mutter T. (2013) Towards Automated Event Studies Using High Frequency News and Trading Data. In: Rabhi F.A., Gomber P. (eds) Enterprise Applications and Services in the Finance Industry. FinanceCom 2012. Lecture Notes in Business Information Processing, vol 135. Springer, Berlin, Heidelberg

Abstract

Event studies have a long history in academic research and were used in disciplines as diverse as economics, law, information technology, marketing, and finance. One of the main challenges is that the process of undertaking such an event study is complex and many assumptions, trade-offs and design decisions need to be made. Based on Service-Oriented Computing principles, this paper proposes a business process on how to undertake and partly automate complex event studies on effects of (un)scheduled news on stocks prices using high frequency trading and news data. The proposed business process is illustrated using a case study that shows how to identify effects of unscheduled news on stock prices in the German DAX30 index.

Keywords

Event Study Business Process High Frequency Data Unscheduled News Price Jump Detection 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nicolai Bohn
    • 1
  • Fethi A. Rabhi
    • 2
  • Dennis Kundisch
    • 1
  • Lawrence Yao
    • 2
  • Tobias Mutter
    • 1
  1. 1.Faculty of Business Administration and EconomicsUniversity of PaderbornPaderbornGermany
  2. 2.School of Computer Science and EngineeringUniversity of New South WalesSydneyAustralia