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Chasing Noise

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  • Brock Mendel
  • Andrei Shleifer

Abstract

We present a simple model in which rational but uninformed traders occasionally chase noise as if it were information, thereby amplifying sentiment shocks and moving prices away from fundamental values. We fill a theoretical gap in the literature by showing conditions under which noise traders can have an impact on market equilibrium disproportionate to their size in the market. The model offers a partial explanation for the surprisingly low market price of financial risk in the Spring of 2007.

Suggested Citation

  • Brock Mendel & Andrei Shleifer, 2010. "Chasing Noise," NBER Working Papers 16042, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:16042
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    References listed on IDEAS

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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. A Crisis of Beliefs: a review
      by chris in Stumbling and Mumbling on 2018-09-26 10:18:48
    2. On socially influenced preferences
      by chris in Stumbling and Mumbling on 2020-02-02 13:06:32

    Citations

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    Cited by:

    1. 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.
    2. Irresberger, Felix & Mühlnickel, Janina & Weiß, Gregor N.F., 2015. "Explaining bank stock performance with crisis sentiment," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 311-329.
    3. Weihong HUANG & Wanying Wang, 2012. "Price-Volume Relations in Financial Market," Economic Growth Centre Working Paper Series 1209, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    4. Guo, Bin & Zhang, Wei & Chen, Shu-Heng & Zhang, Yongjie, 2015. "The optimal pricing of a market maker in a heterogeneous agent economy," Finance Research Letters, Elsevier, vol. 14(C), pages 178-187.
    5. Li, Jinfang, 2014. "Multi-period sentiment asset pricing model with information," International Review of Economics & Finance, Elsevier, vol. 34(C), pages 118-130.
    6. Robert S. Chirinko & Christopher Curran, 2013. "Greenspan Shrugs: Central Bank Communication, Formal Pronouncements and Bond Market Volatility," CESifo Working Paper Series 4236, CESifo.
    7. Rossi, S & Tinn, K, 2012. "Man or Machine? Rational trading without information about fundamentals," Working Papers 12194, Imperial College, London, Imperial College Business School.
    8. Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018. "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 237-293.
    9. Claußen, Arndt & Löhr, Sebastian & Rösch, Daniel & Scheule, Harald, 2017. "Valuation of systematic risk in the cross-section of credit default swap spreads," The Quarterly Review of Economics and Finance, Elsevier, vol. 64(C), pages 183-195.
    10. Yang, Chunpeng & Li, Jinfang, 2013. "Investor sentiment, information and asset pricing model," Economic Modelling, Elsevier, vol. 35(C), pages 436-442.
    11. Li, Jinfang, 2017. "Investor sentiment, heterogeneous agents and asset pricing model," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 504-512.
    12. Buckley, Winston & Long, Hongwei & Perera, Sandun, 2014. "A jump model for fads in asset prices under asymmetric information," European Journal of Operational Research, Elsevier, vol. 236(1), pages 200-208.
    13. Yang, Chunpeng & Cai, Chuangqun, 2014. "Higher order expectations in sentiment asset pricing model," Economic Modelling, Elsevier, vol. 39(C), pages 95-100.
    14. Yang, Chunpeng & Li, Jinfang, 2014. "Two-period trading sentiment asset pricing model with information," Economic Modelling, Elsevier, vol. 36(C), pages 1-7.

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    More about this item

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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