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How do investors react under uncertainty?

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  • Bird, Ron
  • Yeung, Danny

Abstract

It has long been accepted that risk plays an important role in determining valuation where risk reflects that investors are unsure of future returns but are able to express their prior expectations by a probability distribution of these returns. Knight (1921) introduced the concept of uncertainty where investors possess incomplete knowledge about this distribution and so are unable to formulate priors over all possible outcomes. One common approach for making uncertainty tractable is to assume that investors faced with uncertainty will base their decisions on the worst case scenario (i.e. follow maxmin expected utility). As a consequence it is postulated that investors will become more pessimistic as uncertainty increases, upgrading bad news and downgrading good news. Using Australian data, we find evidence that investors react to bad news at times of high market uncertainty but largely ignore good news which is consistent with them taking on a pessimistic bias. However, we also find evidence of the reverse when market uncertainty is low with investors taking on an optimistic stance by ignoring bad news but reacting to good news. We also find that the impact that market uncertainty has on the reaction of investors to new information is modified by the prevailing market sentiment at the time of the announcement. Besides throwing light on the question of how uncertainty impacts on investor behaviour, our findings seriously challenge the common assumption made that investors consistently deal with uncertainty by applying maxmin expected utility.

Suggested Citation

  • Bird, Ron & Yeung, Danny, 2012. "How do investors react under uncertainty?," Pacific-Basin Finance Journal, Elsevier, vol. 20(2), pages 310-327.
  • Handle: RePEc:eee:pacfin:v:20:y:2012:i:2:p:310-327
    DOI: 10.1016/j.pacfin.2011.10.001
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Qi Nan Zhai, 2015. "Asset Pricing Under Ambiguity and Heterogeneity," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 16.
    2. Kiran Thapa, 2013. "Stock Message Board Recommendations and Share Trading Activity," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 10.
    3. Ron Bird & Daniel Choi & Danny Yeung, 2014. "Market uncertainty, market sentiment, and the post-earnings announcement drift," Review of Quantitative Finance and Accounting, Springer, vol. 43(1), pages 45-73, July.
    4. Dutt, Tanuj & Humphery-Jenner, Mark, 2013. "Stock return volatility, operating performance and stock returns: International evidence on drivers of the ‘low volatility’ anomaly," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 999-1017.
    5. Ron Bird & Krishna Reddy & Danny Yeung, 2014. "The relationship between uncertainty and the market reaction to information: Is it influenced by stock-specific characteristics?," International Journal of Behavioural Accounting and Finance, Inderscience Enterprises Ltd, vol. 4(2), pages 113-132.
    6. Dakhlaoui, Imen & Aloui, Chaker, 2016. "The interactive relationship between the US economic policy uncertainty and BRIC stock markets," International Economics, Elsevier, vol. 146(C), pages 141-157.
    7. repec:bla:acctfi:v:57:y:2017:i::p:3-43 is not listed on IDEAS
    8. Laakkonen, Helinä, 2015. "Relevance of uncertainty on the volatility and trading volume in the US Treasury bond futures market," Research Discussion Papers 4/2015, Bank of Finland.
    9. Mai, Van Anh (Vivian) & Ang, Tze Chuan ‘Chewie’ & Fang, Victor, 2016. "Aggregate volatility risk and the cross-section of stock returns: Australian evidence," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 134-149.
    10. Jeffrey J. Coulton & Tami Dinh & Andrew B. Jackson & Tom Smith, 2016. "The impact of sentiment on price discovery," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(3), pages 669-694, September.
    11. Javier Giner & Sandra Morini & Rafael Rosillo, 2016. "Optimal Prediction Periods for New and Old Volatility Indexes in USA and German Markets," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 527-549, April.
    12. Kang, Wensheng & Ratti, Ronald A., 2013. "Oil shocks, policy uncertainty and stock market return," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 305-318.
    13. Amandha Ganegoda & John Evans, 2014. "A framework to manage the measurable, immeasurable and the unidentifiable financial risk," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 5-34, February.
    14. Guerello, Chiara, 2016. "The effect of investors’ confidence on monetary policy transmission mechanism," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 248-266.

    More about this item

    Keywords

    Uncertainty; Ambiguity; Earnings announcement; Asymmetric response;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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