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A Theory of Asset Pricing Based on Heterogeneous Information

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  • Elias Albagli
  • Christian Hellwig
  • Aleh Tsyvinski

Abstract

We propose a theory of asset prices that emphasizes heterogeneous information as the main element determining prices of different securities. Our main analytical innovation is in formulating a model of noisy information aggregation through asset prices, which is parsimonious and tractable, yet flexible in the specification of cash flow risks. We show that the noisy aggregation of heterogeneous investor beliefs drives a systematic wedge between the impact of fundamentals on an asset price, and the corresponding impact on cash flow expectations. The key intuition behind the wedge is that the identity of the marginal trader has to shift for different realization of the underlying shocks to satisfy the market-clearing condition. This identity shift amplifies the impact of price on the marginal trader's expectations. We derive tight characterization for both the conditional and the unconditional expected wedges. Our first main theorem shows how the sign of the expected wedge (that is, the difference between the expected price and the dividends) depends on the shape of the dividend payoff function and on the degree of informational frictions. Our second main theorem provides conditions under which the variability of prices exceeds the variability for realized dividends. We conclude with two applications of our theory. First, we highlight how heterogeneous information can lead to systematic departures from the Modigliani-Miller theorem. Second, in a dynamic extension of our model we provide conditions under which bubbles arise.

Suggested Citation

  • Elias Albagli & Christian Hellwig & Aleh Tsyvinski, 2011. "A Theory of Asset Pricing Based on Heterogeneous Information," NBER Working Papers 17548, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:17548
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    References listed on IDEAS

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

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    Cited by:

    1. Pasten, Ernesto & Schoenle, Raphael, 2016. "Rational inattention, multi-product firms and the neutrality of money," Journal of Monetary Economics, Elsevier, vol. 80(C), pages 1-16.
    2. Tarek A. Hassan & Thomas M. Mertens, 2015. "Information Aggregation in a Dynamic Stochastic General Equilibrium Model," NBER Macroeconomics Annual, University of Chicago Press, vol. 29(1), pages 159-207.
    3. Marta Areosa & Waldyr Areosa, 2012. "Asset Prices and Monetary Policy – A sticky-dispersed information model," Working Papers Series 285, Central Bank of Brazil, Research Department.
    4. Briana Chang & Harrison Hong, 2017. "Assignment of Stock Market Coverage," NBER Working Papers 23115, National Bureau of Economic Research, Inc.
    5. Christian Hellwig & Aleh Tsyvinski & Elias Albagli, 2014. "Dynamic Dispersed Information and the Credit Spread Puzzle," 2014 Meeting Papers 808, Society for Economic Dynamics.
    6. Hassan, Tarek & Mertens, Thomas M., 2014. "Information Aggregation in a DSGE Model," CEPR Discussion Papers 10020, C.E.P.R. Discussion Papers.
    7. Iachan, Felipe S. & Nenov, Plamen T., 2015. "Information quality and crises in regime-change games," Journal of Economic Theory, Elsevier, vol. 158(PB), pages 739-768.
    8. Orlik, Anna & Veldkamp, Laura, 2014. "Understanding Uncertainty Shocks and the Role of Black Swans," CEPR Discussion Papers 10147, C.E.P.R. Discussion Papers.
    9. Benhabib, Jess & Wang, Pengfei, 2015. "Private information and sunspots in sequential asset markets," Journal of Economic Theory, Elsevier, vol. 158(PB), pages 558-584.

    More about this item

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • 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
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General

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