Summary
Using a Gibbs distribution developed in the theory of statistical physics and a long-range percolation theory, we present a new model of a stock price process for explaining the fat tail in the distribution of stock returns.
We consider two types of traders, Group A and Group B: Group A traders analyze the past data on the stock market to determine their present trading positions. The way to determine their trading positions is not deterministic but obeys a Gibbs distribution with interactions between the past data and the present trading positions. On the other hand, Group B traders follow the advice reached through the long-range percolation system from the investment adviser. As the resulting stock price process, we derive a Lévy process.
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© 2006 Springer-Verlag Tokyo
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Kuroda, K., Murai, J. (2006). Stock price process and the long-range percolation. In: Takayasu, H. (eds) Practical Fruits of Econophysics. Springer, Tokyo. https://doi.org/10.1007/4-431-28915-1_29
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DOI: https://doi.org/10.1007/4-431-28915-1_29
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-28914-2
Online ISBN: 978-4-431-28915-9
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