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A Limit Theorem for Financial Markets with Inert Investors

  • Erhan Bayraktar
  • Ulrich Horst
  • Ronnie Sircar

We study the effect of investor inertia on stock price fluctuations with a market microstructure model comprising many small investors who are inactive most of the time. It turns out that semi-Markov processes are tailor made for modelling inert investors. With a suitable scaling, we show that when the price is driven by the market imbalance, the log price process is approximated by a process with long range dependence and non-Gaussian returns distributions, driven by a fractional Brownian motion. Consequently, investor inertia may lead to arbitrage opportunities for sophisticated market participants. The mathematical contributions are a functional central limit theorem for stationary semi-Markov processes, and approximation results for stochastic integrals of continuous semimartingales with respect to fractional Brownian motion.

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Paper provided by in its series Papers with number math/0703831.

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Date of creation: Mar 2007
Date of revision:
Publication status: Published in Mathematics of Operations Research, 2006, Volume 31 (4), 789-810
Handle: RePEc:arx:papers:math/0703831
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  1. Brad M. Barber & Terrance Odean, 2002. "Online Investors: Do the Slow Die First?," Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 455-488, March.
  2. Haliassos, Michael & Bertaut, Carol C, 1995. "Why Do So Few Hold Stocks?," Economic Journal, Royal Economic Society, vol. 105(432), pages 1110-29, September.
  3. Sergio Bianchi, 2005. "Pathwise Identification Of The Memory Function Of Multifractional Brownian Motion With Application To Finance," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 255-281.
  4. Erhan Bayraktar & H. Vincent Poor & Ronnie Sircar, 2007. "Estimating the Fractal Dimension of the S&P 500 Index using Wavelet Analysis," Papers math/0703834,
  5. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
  6. Lux, T. & M. Marchesi, . "Volatility Clustering in Financial Markets: A Micro-Simulation of Interacting Agents," Discussion Paper Serie B 437, University of Bonn, Germany, revised Jul 1998.
  7. Cont, Rama & Bouchaud, Jean-Philipe, 2000. "Herd Behavior And Aggregate Fluctuations In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(02), pages 170-196, June.
  8. Brock, W.A. & Hommes, C.H., 1996. "A Rational Route to Randomness," Working papers 9530r, Wisconsin Madison - Social Systems.
  9. Ulrich Horst, 2005. "Financial price fluctuations in a stock market model with many interacting agents," Economic Theory, Springer, vol. 25(4), pages 917-932, 06.
  10. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
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