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Chasing Noise

Author

Listed:
  • 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. In the model, 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. Copyright 2011 Elsevier B.V. All rights reserved.

Suggested Citation

  • Brock Mendel & Andrei Shleifer, "undated". "Chasing Noise," Working Paper 19517, Harvard University OpenScholar.
    • Handle: RePEc:qsh:wpaper:19517
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    File URL: http://scholar.harvard.edu/shleifer/node/19517
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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

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    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. 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.
    4. Yang, Chunpeng & Li, Jinfang, 2013. "Investor sentiment, information and asset pricing model," Economic Modelling, Elsevier, vol. 35(C), pages 436-442.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Li, Jinfang, 2014. "Multi-period sentiment asset pricing model with information," International Review of Economics & Finance, Elsevier, vol. 34(C), pages 118-130.
    11. 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.
    12. Robert S. Chirinko & Christopher Curran, 2013. "Greenspan Shrugs: Central Bank Communication, Formal Pronouncements and Bond Market Volatility," CESifo Working Paper Series 4236, CESifo.
    13. Rossi, S & Tinn, K, 2012. "Man or Machine? Rational trading without information about fundamentals," Working Papers 12194, Imperial College, London, Imperial College Business School.
    14. Yang, Chunpeng & Cai, Chuangqun, 2014. "Higher order expectations in sentiment asset pricing model," Economic Modelling, Elsevier, vol. 39(C), pages 95-100.
    15. Yang, Chunpeng & Li, Jinfang, 2014. "Two-period trading sentiment asset pricing model with information," Economic Modelling, Elsevier, vol. 36(C), pages 1-7.

    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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