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Liquidity Constraints in Production-Based Asset-Pricing Models

In: Asymmetric Information, Corporate Finance, and Investment

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  • William A. Brock
  • Blake LeBaron

Abstract

This paper explores the time series implications of introducing credit constraints into a production based asset pricing model. Simulations are performed choosing parameter values which generate reasonable values for aggregate fluctuations. These results show that mean reversion in simulated returns series, measured by variance ration tests, is enhanced with the introduction of binding credit constraints. Without these constraints there is very little evidence of mean reversion. This is consistent with financial market data where the weak evidence for mean reversion is stronger in small firm returns. Other tests are run on the simulated series including checking the standard deviation, skewness, and kurtosis. These other tests do not show strong differences between the constrained and unconstrained firms in the model.

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  • R. Glenn Hubbard, 1990. "Asymmetric Information, Corporate Finance, and Investment," NBER Books, National Bureau of Economic Research, Inc, number glen90-1.
    This item is provided by National Bureau of Economic Research, Inc in its series NBER Chapters with number 11474.

    Handle: RePEc:nbr:nberch:11474

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    1. Robert B. Barsky & Jeffrey A. Miron, 1988. "The Seasonal Cycle and the Business Cycle," NBER Working Papers 2688, National Bureau of Economic Research, Inc.
    2. De Bondt, Werner F M & Thaler, Richard H, 1987. " Further Evidence on Investor Overreaction and Stock Market Seasonalit y," Journal of Finance, American Finance Association, vol. 42(3), pages 557-81, July.
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    4. Steven M. Fazzari & R. Glenn Hubbard & BRUCE C. PETERSEN, 1988. "Financing Constraints and Corporate Investment," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 19(1), pages 141-206.
    5. Myung Jig Kim & Charles R. Nelson & Richard Startz, 1988. "Mean Reversion in Stock Prices? A Reappraisal of the Empirical Evidence," NBER Working Papers 2795, National Bureau of Economic Research, Inc.
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    7. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    8. Lucas, Robert E, Jr, 1978. "Asset Prices in an Exchange Economy," Econometrica, Econometric Society, vol. 46(6), pages 1429-45, November.
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    12. Irwin Friend & Larry Lang, . "The Size Effect on Stock Returns: It is a Simply a Risk Effect not Adequately Reflected by the Usual Measures?," Rodney L. White Center for Financial Research Working Papers 24-87, Wharton School Rodney L. White Center for Financial Research.
    13. Brock, W.A. & Dechert, W.D. & LeBaron, B. & Scheinkman, J.A., 1995. "A Test for Independence Based on the Correlation Dimension," Working papers 9520, Wisconsin Madison - Social Systems.
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    Cited by:
    1. Van Norden, S. & Schaller, H., 1996. "Speculative Behaviour, Regime-Switching and Stock Market Crashes," Working Papers 96-13, Bank of Canada.
    2. Alan J. Marcus, 1989. "An Equilibrium Theory of Excess Volatility and Mean Reversion in Stock Market Prices," NBER Working Papers 3106, National Bureau of Economic Research, Inc.
    3. Simon van Norden & Huntley Schaller & ), 1995. "Fads or Bubbles?," Econometrics 9502004, EconWPA, revised 06 Jun 1995.
    4. Calomiris, Charles W. & Love, Inessa & Martínez Pería, María Soledad, 2012. "Stock returns’ sensitivities to crisis shocks: Evidence from developed and emerging markets," Journal of International Money and Finance, Elsevier, vol. 31(4), pages 743-765.

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