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Analyzing Trading Behavior in Transaction Data of Electronic Election Markets

  • Markus Pranke
  • Andreas Geyer-Schulz
  • Bettina Hoser
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Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

In this article we apply the analysis of eigensystems in Hilbert space for analyzing transaction data in real-time double auction markets. While this method is well known in quantum physics, its application for the analysis of financial markets is new. We show that transaction data from a properly designed financial accounting system of a market place completely reflect all market information and that this transaction data can be represented as Hermitian adjacency matrices without information loss.

In this article we apply the analysis of the resulting eigensystem to detect and investigate market-making behavior. We show how some of the stylized facts about trading behavior can be recognized in the eigensystem of the market. We demonstrate the method in a small case study for a political stock market for the 2004 elections for the European Parliament in Germany.

Keywords

Election Market Market Maker Market Transaction Transaction Data Star Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin · Heidelberg 2005

Authors and Affiliations

  • Markus Pranke
    • 1
  • Andreas Geyer-Schulz
    • 1
  • Bettina Hoser
    • 1
  1. 1.Information Services and Electronic Markets, Institute for Information Engineering and ManagementUniversität Karlsruhe (TH)KarlsruheGermany

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