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.
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Pranke, M., Geyer-Schulz, A., Hoser, B. (2005). Analyzing Trading Behavior in Transaction Data of Electronic Election Markets. In: Baier, D., Decker, R., Schmidt-Thieme, L. (eds) Data Analysis and Decision Support. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28397-8_25
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DOI: https://doi.org/10.1007/3-540-28397-8_25
Publisher Name: Springer, Berlin, Heidelberg
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