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Limit Distribution of Evolving Strategies in Financial Markets

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In this paper we model a financial market composed of agents with heterogeneous beliefs who change their strategy over time. We propose two different solution methods which lead to two different types of endogenous dynamics. The first makes use of the maximum entropy approach to obtain an exponential type probability function for strategies, analogous to the well known Brock and Hommes (1997) model, but with the endogenous specification for the intensity of choice parameter, which varies over time as a consequence of the relative performances of each strategy. The second type of dynamics is obtained by setting up a master equation and solving it using recently developed asymptotic solution techniques, which yield a system of differential equations describing the evolution of the share of each strategy in the market. The performance sof the two solutions are then compared and contrasted with the empirical evidence.

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Paper provided by Quantitative Finance Research Centre, University of Technology, Sydney in its series Research Paper Series with number 294.

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Length: 28
Date of creation: 01 Aug 2011
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Handle: RePEc:uts:rpaper:294

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Cited by:
  1. Corrado Di Guilmi & Xue-Zhong He & Kai Li, 2013. "Herding, Trend Chasing and Market Volatility," Research Paper Series 337, Quantitative Finance Research Centre, University of Technology, Sydney.

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