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Measuring mispricing in experimental markets

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Abstract

Mispricing (the difference between prices and their underlying fundamental values) is an important characteristic of markets. The literature on the topic consists of many different measures. This state of affairs is unsatisfactory, since different measures may produce different results. Stöckl et al. (2010) partially address this problem by proposing (among other things) that measures of mispricing be independent of certain nominal variables: the number of dividend payments and the absolute level of fundamental values. Their conditions rule out all previous measures used in the literature and leads them to propose new measures in response. This paper proposes that mispricing measures be independent of an additional variable: the unit of account. This condition rules out the measures proposed by Stöckl et al. (2010) and serves as the basis for a new measure of market mispricing, the Geometric Average Deviation (GAD). The unit of account condition is relevant to many market settings, and thus calls into question the findings of previous research based on other measures that fail to satisfy this condition. An application illustrates the potential impact of this new measure on previous experimental results.

Suggested Citation

  • Owen Powell, 2014. "Measuring mispricing in experimental markets," Vienna Economics Papers vie1407, University of Vienna, Department of Economics.
    • Handle: RePEc:vie:viennp:vie1407
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    References listed on IDEAS

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    1. Thomas Stöckl & Jürgen Huber & Michael Kirchler, 2010. "Bubble measures in experimental asset markets," Experimental Economics, Springer;Economic Science Association, vol. 13(3), pages 284-298, September.
    2. Stefan Palan, 2013. "A Review Of Bubbles And Crashes In Experimental Asset Markets," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 570-588, July.
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    Cited by:

    1. Baghestanian, Sascha & Gortner, Paul & Massenot, Baptiste, 2015. "Compensation schemes, liquidity provision, and asset prices: An experimental analysis," SAFE Working Paper Series 108, Leibniz Institute for Financial Research SAFE.
    2. Owen Powell & Natalia Shestakova, 2017. "Experimental asset markets: behavior and bubbles," Chapters, in: Morris Altman (ed.), Handbook of Behavioural Economics and Smart Decision-Making, chapter 21, pages 375-391, Edward Elgar Publishing.

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    More about this item

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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