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GIMS—Software for asset market experiments

Author

Listed:
  • Palan, Stefan

Abstract

In this article we lay out requirements for an experimental market software for financial and economic research. We then discuss existing solutions. Finally, we introduce GIMS, an open source market software which is characterized by extensibility and ease of use, while offering nearly all of the required functionality.

Suggested Citation

  • Palan, Stefan, 2015. "GIMS—Software for asset market experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 5(C), pages 1-14.
    • Handle: RePEc:eee:beexfi:v:5:y:2015:i:c:p:1-14
    DOI: 10.1016/j.jbef.2015.02.001
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    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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    Cited by:

    1. Hubert J. Kiss & Laszlo A. Koczy & Agnes Pinter & Balazs R. Sziklai, 2019. "Does risk sorting explain bubbles?," CERS-IE WORKING PAPERS 1905, Institute of Economics, Centre for Economic and Regional Studies.
    2. Roger, Tristan & Roger, Patrick & Willinger, Marc, 2022. "Number sense, trading decisions and mispricing: An experiment," Journal of Economic Dynamics and Control, Elsevier, vol. 135(C).
    3. Christoph Huber & Julia Rose, 2019. "Do individual attitudes towards imprecision survive in experimental asset markets?," Working Papers 2019-06, Faculty of Economics and Statistics, Universität Innsbruck.
    4. Fink, Josef & Palan, Stefan & Theissen, Erik, 2020. "Earnings autocorrelation and the post-earnings-announcement drift: Experimental evidence," CFR Working Papers 20-10, University of Cologne, Centre for Financial Research (CFR).
    5. Utz Weitzel & Christoph Huber & Jürgen Huber & Michael Kirchler & Florian Lindner & Julia Rose & Lauren Cohen, 2020. "Bubbles and Financial Professionals," The Review of Financial Studies, Society for Financial Studies, vol. 33(6), pages 2659-2696.
    6. Christoph Huber & Parampreet C. Bindra & Daniel Kleinlercher, 2019. "Design-features of bubble-prone experimental asset markets with a constant FV," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(2), pages 197-209, December.
    7. repec:grz:wpsses:2020-03 is not listed on IDEAS
    8. Benndorf, Volker & Rau, Holger A. & Sölch, Christian, 2019. "Minimizing learning in repeated real-effort tasks," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 239-248.
    9. repec:grz:wpsses:2021-01 is not listed on IDEAS
    10. Giamattei, Marcus & Huber, Jürgen & Lambsdorff, Johann Graf & Nicklisch, Andreas & Palan, Stefan, 2020. "Who inflates the bubble? Forecasters and traders in experimental asset markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    11. repec:grz:wpsses:2019-01 is not listed on IDEAS
    12. Marquardt, Philipp & Noussair, Charles N & Weber, Martin, 2019. "Rational expectations in an experimental asset market with shocks to market trends," European Economic Review, Elsevier, vol. 114(C), pages 116-140.
    13. Huber, Jürgen & Palan, Stefan & Zeisberger, Stefan, 2019. "Does investor risk perception drive asset prices in markets? Experimental evidence," Journal of Banking & Finance, Elsevier, vol. 108(C).
    14. Razen, Michael & Kupfer, Alexander, 2023. "The effect of tax transparency on consumer and firm behavior: Experimental evidence," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 104(C).
    15. Hoyer, Karlijn & Zeisberger, Stefan & Breugelmans, Seger M. & Zeelenberg, Marcel, 2023. "A culture of greed: Bubble formation in experimental asset markets with greedy and non-greedy traders," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 32-52.
    16. Kiss, Hubert J. & Kóczy, László Á. & Pintér, Ágnes & Sziklai, Balázs R., 2022. "Does risk sorting explain overpricing in experimental asset markets?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 99(C).

    More about this item

    Keywords

    Asset market; Experiment; Software; Double auction; Call auction;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design

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