Stock price process and the long-range percolation

Koji Kuroda () and Joshin Murai ()
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Koji Kuroda: Nihon University
Joshin Murai: Okayama University

A chapter in Practical Fruits of Econophysics, 2006, pp 163-167 from Springer

Abstract: 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.

Keywords: Stock Price; Stock Return; Trading Strategy; Random Interval; Past Data (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-4-431-28915-9_29

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DOI: 10.1007/4-431-28915-1_29

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