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A Theory of Asset Prices Based on Heterogeneous Information

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  • Elias Albagli
  • Christian Hellwig
  • Aleh Tsyvinski

Abstract

With only minimal restrictions on security payoffs and trader preferences, noisy aggregation of heterogeneous information drives a systematic wedge between the impact of fundamentals on the price of a security, and the corresponding impact on cash flow expectations. From an ex ante perspective, this information aggregation wedge leads to a systematic gap between an asset's expected price and its expected dividend. The sign and magnitude of this expected wedge depend on the asymmetry between upside and downside payoff risks and on the importance of information heterogeneity. We consider three applications of our theory. We first show that predictions of our model provide a novel theoretical justification and are quantitatively consistent with documented empirical regularities on negative relationship between returns and skewness. Second, we illustrate how heterogeneous information leads to systematic departures from the Modigliani-Miller theorem and provide a new theory of debt versus equity. Third, we provide conditions under which permanent over- or under-pricing of assets is sustainable in a dynamic version of our model.
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Suggested Citation

  • Elias Albagli & Christian Hellwig & Aleh Tsyvinski, 2012. "A Theory of Asset Prices Based on Heterogeneous Information," Levine's Working Paper Archive 786969000000000347, David K. Levine.
  • Handle: RePEc:cla:levarc:786969000000000347
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    References listed on IDEAS

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    1. Aleh Tsyvinski & Arijit Mukherji & Christian Hellwig, 2006. "Self-Fulfilling Currency Crises: The Role of Interest Rates," American Economic Review, American Economic Association, vol. 96(5), pages 1769-1787, December.
    2. Harrison Hong & Jeremy C. Stein, 2007. "Disagreement and the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 109-128, Spring.
    3. Kathy Yuan, 2005. "Asymmetric Price Movements and Borrowing Constraints: A Rational Expectations Equilibrium Model of Crises, Contagion, and Confusion," Journal of Finance, American Finance Association, vol. 60(1), pages 379-411, February.
    4. Hong, Harrison & Sraer, David, 2013. "Quiet bubbles," Journal of Financial Economics, Elsevier, vol. 110(3), pages 596-606.
    5. Terrance Odean, 1998. "Volume, Volatility, Price, and Profit When All Traders Are Above Average," Journal of Finance, American Finance Association, vol. 53(6), pages 1887-1934, December.
    6. Albagli, Elias & Hellwig, Christian & Tsyvinski, Aleh, 2011. "Information Aggregation, Investment, and Managerial Incentives," CEPR Discussion Papers 8539, C.E.P.R. Discussion Papers.
    7. Masahiro Watanabe, 2008. "Price Volatility and Investor Behavior in an Overlapping Generations Model with Information Asymmetry," Journal of Finance, American Finance Association, vol. 63(1), pages 229-272, February.
    8. Laura L. Veldkamp, 2011. "Information Choice in Macroeconomics and Finance," Economics Books, Princeton University Press, edition 1, number 9621.
    9. T. Clifton Green & Byoung-Hyoun Hwang, 2012. "Initial Public Offerings as Lotteries: Skewness Preference and First-Day Returns," Management Science, INFORMS, vol. 58(2), pages 432-444, February.
    10. Brunnermeier, Markus K., 2001. "Asset Pricing under Asymmetric Information: Bubbles, Crashes, Technical Analysis, and Herding," OUP Catalogue, Oxford University Press, number 9780198296980.
    11. Xavier Vives, 2007. "Information and Learning in Markets," Levine's Bibliography 122247000000001520, UCLA Department of Economics.
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    Citations

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    Cited by:

    1. Vladimir Asriyan & William Fuchs & Brett Green, 2017. "Information Aggregation in Dynamic Markets with Adverse Selection," Working Papers 979, Barcelona Graduate School of Economics.
    2. Barlevy, Gadi, 2014. "A leverage-based model of speculative bubbles," Journal of Economic Theory, Elsevier, vol. 153(C), pages 459-505.
    3. Kenneth Kasa & Todd B. Walker & Charles H. Whiteman, 2014. "Heterogeneous Beliefs and Tests of Present Value Models," Review of Economic Studies, Oxford University Press, vol. 81(3), pages 1137-1163.
    4. Banerjee, Snehal & Green, Brett, 2015. "Signal or noise? Uncertainty and learning about whether other traders are informed," Journal of Financial Economics, Elsevier, vol. 117(2), pages 398-423.
    5. Bianchi, Milo & Jehiel, Philippe, 2015. "Financial reporting and market efficiency with extrapolative investors," Journal of Economic Theory, Elsevier, vol. 157(C), pages 842-878.
    6. Jessica Roldan Pena & Virginia Olivella, 2010. "Re-examining the role of financial constraints in business cycles: is something wrong with the credit multiplier?," 2010 Meeting Papers 377, Society for Economic Dynamics.
    7. Chabakauri, Georgy & Yuan, Kathy & Zachariadis, Konstantinos, 2014. "Multi-asset noisy rational expectations equilibrium with contingent claims," LSE Research Online Documents on Economics 60736, London School of Economics and Political Science, LSE Library.
    8. Jean-Paul L'Huillier & William R. Zame, 2015. "The Flattening of the Phillips Curve and the Learning Problem of the Central Bank," EIEF Working Papers Series 1503, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2014.

    More about this item

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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