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Asset Prices in a Time Series Model with Perpetually Disparately Informed, Competitive Traders

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Author Info

  • Kenneth Kasa

    ()
    (Simon Fraser University)

  • Todd B. Walker

    ()
    (Indiana University Bloomington)

  • Charles H. Whiteman

    ()
    (University of Iowa)

Abstract

This paper develops a dynamic asset pricing model with persistent heterogeneous beliefs. The model features competitive traders who receive idiosyncratic signals about an underlying fundamentals process. We adapt Futia’s (1981) frequency domain methods to derive conditions on the fundamentals that guarantee noninvertibility of the mapping between observed market data and the underlying shocks to agents’ information sets. When these conditions are satisfied, agents must ‘forecast the forecasts of others’. The paper provides an explicit analytical characterization of the resulting higher-order belief dynamics. These additional dynamics can explain apparent violations of variance bounds and rejections of cross-equation restrictions.

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File URL: http://www.iub.edu/~caepr/RePEc/PDF/2006/CAEPR2006-010.pdf
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Bibliographic Info

Paper provided by Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington in its series Caepr Working Papers with number 2006-010.

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Length: 34 pages
Date of creation: Sep 2006
Date of revision:
Handle: RePEc:inu:caeprp:2006010

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Related research

Keywords: Asymmetric Information; Blaschke Factors;

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Cited by:
  1. Lanne, Markku & Saikkonen, Pentti, 2009. "Noncausal vector autoregression," Research Discussion Papers 18/2009, Bank of Finland.
  2. Lanne, Markku & Saikkonen, Pentti, 2010. "Noncausal autoregressions for economic time series," MPRA Paper 32943, University Library of Munich, Germany.
  3. Philippe Bacchetta & Eric Van Wincoop, 2008. "Higher Order Expectations in Asset Pricing," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(5), pages 837-866, 08.
  4. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2007. "A Review of Nonfundamentalness and Identification in Structural VAR Models," LEM Papers Series 2007/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

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