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Insider Trading, Stochastic Liquidity and Equilibrium Prices

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  • Pierre Collin-Dufresne
  • Vyacheslav Fos
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    Abstract

    We extend Kyle's (1985) model of insider trading to the case where liquidity provided by noise traders follows a general stochastic process. Even though the level of noise trading volatility is observable, in equilibrium, measured price impact is stochastic. If noise trading volatility is mean-reverting, then the equilibrium price follows a multivariate 'stochastic bridge' process, which displays stochastic volatility. This is because insiders choose to optimally wait to trade more aggressively when noise trading activity is higher. In equilibrium, market makers anticipate this, and adjust prices accordingly. More private information is revealed when volatility is higher. In time series, insiders trade more aggressively, when measured price impact is lower. Therefore, execution costs to uninformed traders can be higher when price impact is lower.

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    Bibliographic Info

    Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18451.

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    Date of creation: Oct 2012
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    Handle: RePEc:nbr:nberwo:18451

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    1. Madhavan, Ananth & Richardson, Matthew & Roomans, Mark, 1997. "Why Do Security Prices Change? A Transaction-Level Analysis of NYSE Stocks," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 10(4), pages 1035-64.
    2. Back, Kerry, 1992. "Insider Trading in Continuous Time," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 5(3), pages 387-409.
    3. Masahiro Watanabe, 2008. "Price Volatility and Investor Behavior in an Overlapping Generations Model with Information Asymmetry," Journal of Finance, American Finance Association, American Finance Association, vol. 63(1), pages 229-272, 02.
    4. Brunnermeier, Markus K., 2001. "Asset Pricing under Asymmetric Information: Bubbles, Crashes, Technical Analysis, and Herding," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780198296980, October.
    5. Baruch, Shmuel, 2002. "Insider trading and risk aversion," Journal of Financial Markets, Elsevier, Elsevier, vol. 5(4), pages 451-464, October.
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    7. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    8. RenĂˆ Caldentey & Ennio Stacchetti, 2010. "Insider Trading With a Random Deadline," Econometrica, Econometric Society, Econometric Society, vol. 78(1), pages 245-283, 01.
    9. Foster, F Douglas & Viswanathan, S, 1993. " Variations in Trading Volume, Return Volatility, and Trading Costs: Evidence on Recent Price Formation Models," Journal of Finance, American Finance Association, American Finance Association, vol. 48(1), pages 187-211, March.
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    13. Foster, F Douglas & Viswanathan, S, 1990. "A Theory of the Interday Variations in Volume, Variance, and Trading Costs in Securities Markets," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 3(4), pages 593-624.
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    Cited by:
    1. Pasquariello, Paolo, 2014. "Prospect Theory and market quality," Journal of Economic Theory, Elsevier, Elsevier, vol. 149(C), pages 276-310.
    2. Shino Takayama, 2013. "Price Manipulation, Dynamic Informed Trading and Tame Equilibria: Theory and Computation," Discussion Papers Series 492, School of Economics, University of Queensland, Australia.

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