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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

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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 & 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.
    4. Josef Fink & Stefan Palan & Erik Theissen, 2020. "Earnings Autocorrelation and the Post-Earnings-AnnouncementDrift – Experimental Evidence," Working Paper Series, Social and Economic Sciences 2020-03, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    5. 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.
    6. 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).
    7. 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.
    8. Josef Fink & Stefan Palan & Erik Theissen, 2021. "Trading Frictions and the Post-Earnings-Announcement Drift," Working Paper Series, Social and Economic Sciences 2021-01, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    9. 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).
    10. Stefan Palan & Jürgen Huber & Larissa Senninger, 2020. "Aggregation mechanisms for crowd predictions," Experimental Economics, Springer;Economic Science Association, vol. 23(3), pages 788-814, September.
    11. 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).
    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. Utz Weitzel & Christoph Huber & Jürgen Huber & Michael Kirchler & Florian Lindner & Julia Rose & Lauren Cohen, 2020. "Bubbles and Financial Professionals [Margin, short sell, and lotteries in experimental asset markets]," The Review of Financial Studies, Society for Financial Studies, vol. 33(6), pages 2659-2696.
    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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