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A theory of asset prices based on heterogeneous information

Author

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  • Christian Hellwig

    (Toulouse School of Economics)

  • Aleh Tsyvinski

    (Yale University)

  • Elias Albagli

    (University of Southern California)

Abstract

We propose a theory of asset prices that emphasizes heterogeneous information as the main element determining prices of different securities. 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 an asset price, 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, whose sign and magnitude depend on the asymmetry between upside and downside payoff risks, and on the importance of information heterogeneity. Moreover, when information frictions are sufficiently severe, the model is consistent with arbitrarily high levels of excess price variability as well as low return predictability. Importantly, these results do not rely on traders' risk aversion and thus offer an alternative theory of expected asset returns and price volatility. As applications of our theory, we first highlight how heterogeneous information leads to systematic departures from the Modigliani-Miller theorem and provide a new theory of debt versus equity. Second, in a dynamic extension we provide conditions under which price bubbles are sustainable.

Suggested Citation

  • Christian Hellwig & Aleh Tsyvinski & Elias Albagli, 2012. "A theory of asset prices based on heterogeneous information," 2012 Meeting Papers 394, Society for Economic Dynamics.
  • Handle: RePEc:red:sed012:394
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    References listed on IDEAS

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    1. 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.
    2. Hong, Harrison & Sraer, David, 2013. "Quiet bubbles," Journal of Financial Economics, Elsevier, vol. 110(3), pages 596-606.
    3. 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.
    4. Albagli, Elias & Hellwig, Christian & Tsyvinski, Aleh, 2011. "Information Aggregation, Investment, and Managerial Incentives," CEPR Discussion Papers 8539, C.E.P.R. Discussion Papers.
    5. 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.
    6. Laura L. Veldkamp, 2011. "Information Choice in Macroeconomics and Finance," Economics Books, Princeton University Press, edition 1, number 9621.
    7. Brunnermeier, Markus K., 2001. "Asset Pricing under Asymmetric Information: Bubbles, Crashes, Technical Analysis, and Herding," OUP Catalogue, Oxford University Press, number 9780198296980.
    8. Xavier Vives, 2007. "Information and Learning in Markets," Levine's Bibliography 122247000000001520, UCLA Department of Economics.
    9. 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.
    10. 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.
    11. 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.
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    Citations

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    Cited by:

    1. Barlevy, Gadi, 2014. "A leverage-based model of speculative bubbles," Journal of Economic Theory, Elsevier, vol. 153(C), pages 459-505.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Vladimir Asriyan & William Fuchs & Brett Green, 2017. "Information Aggregation in Dynamic Markets with Adverse Selection," Working Papers 979, Barcelona Graduate School of Economics.
    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. Bianchi, Milo & Jehiel, Philippe, 2015. "Financial reporting and market efficiency with extrapolative investors," Journal of Economic Theory, Elsevier, vol. 157(C), pages 842-878.

    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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