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A Model of Stochastic Liquidity

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  • Masahiro Watanabe

Abstract

This paper proposes a dynamic multi-security model in which liquidity reflects stochastic variation, persistence, and commonality of underlying information variance. Illiquidity, price-change variance, and trading volume all increase in the size of information. Using high frequency data, I perform structural estimation of the model by Bayesian Markov-Chain Monte-Carlo simulation, with the conditional volatility of underlying information modeled as stochastic volatility or realized volatility controlling for microstructure noise. I find that a Dow stock's liquidity decreases in the size of information about not only itself but also about other Dow stocks, demonstrating a significant cross-sectional effect of information on liquidity.

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File URL: http://icfpub.som.yale.edu/publications/2642
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Bibliographic Info

Paper provided by Yale School of Management in its series Yale School of Management Working Papers with number ysm385.

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Date of creation: 01 Jun 2003
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Handle: RePEc:ysm:somwrk:ysm385

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Web page: http://icf.som.yale.edu/
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Related research

Keywords: Kyle model; liquidity; stochastic and realized volatility; Bayesian Markov-Chain Monte-Carlo (MCMC); GARCH; trading volume;

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References

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Cited by:
  1. Kempf, Alexander & Mayston, Daniel, 2006. "Liquidity commonality beyond best prices," CFR Working Papers 06-04, University of Cologne, Centre for Financial Research (CFR).

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