Coupled continuous time random walks in finance
Mark M. Meerschaert and
Enrico Scalas
Papers from arXiv.org
Abstract:
Continuous time random walks (CTRWs) are used in physics to model anomalous diffusion, by incorporating a random waiting time between particle jumps. In finance, the particle jumps are log-returns and the waiting times measure delay between transactions. These two random variables (log-return and waiting time) are typically not independent. For these coupled CTRW models, we can now compute the limiting stochastic process (just like Brownian motion is the limit of a simple random walk), even in the case of heavy tailed (power-law) price jumps and/or waiting times. The probability density functions for this limit process solve fractional partial differential equations. In some cases, these equations can be explicitly solved to yield descriptions of long-term price changes, based on a high-resolution model of individual trades that includes the statistical dependence between waiting times and the subsequent log-returns. In the heavy tailed case, this involves operator stable space-time random vectors that generalize the familiar stable models. In this paper, we will review the fundamental theory and present two applications with tick-by-tick stock and futures data.
Date: 2006-08
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Citations: View citations in EconPapers (21)
Published in Physica A, vol. 370, 114-118, 2006
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http://arxiv.org/pdf/physics/0608281 Latest version (application/pdf)
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Journal Article: Coupled continuous time random walks in finance (2006) 
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:physics/0608281
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