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Simulation-based learning using the RIT market simulator and RIT decision cases

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  • Mak, Kevin
  • McCurdy, Thomas H.

Abstract

RIT is a custom-designed product consisting of a market simulator platform and learning-by-doing decision cases that simulate risks and opportunities for various financial securities, investment and risk management strategies. Using the market simulator with custom designed cases, linked in real-time to decision support models applying the relevant theory, participants learn how to make good real-time decisions in complex environments for which there is material uncertainty. The market aggregates participants’ decisions and provides immediate feedback concerning the success of their strategies, allowing them to adapt their strategies after each replication of the case. Besides supporting teaching and training, the decision cases facilitate competitions and events at many different levels. Given the high degree of flexibility and customization that is available to the market administrator, low-friction engagement for participants, and high-resolution data logging, the RIT product is also a valuable resource for investigating research questions across a wide-range of topics.

Suggested Citation

  • Mak, Kevin & McCurdy, Thomas H., 2019. "Simulation-based learning using the RIT market simulator and RIT decision cases," Journal of Behavioral and Experimental Finance, Elsevier, vol. 23(C), pages 12-22.
    • Handle: RePEc:eee:beexfi:v:23:y:2019:i:c:p:12-22
    DOI: 10.1016/j.jbef.2019.05.003
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    References listed on IDEAS

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    1. Brunnermeier, Markus K. & Morgan, John, 2010. "Clock games: Theory and experiments," Games and Economic Behavior, Elsevier, vol. 68(2), pages 532-550, March.
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    3. Nofsinger, John R. & Patterson, Fernando M. & Shank, Corey A., 2018. "Decision-making, financial risk aversion, and behavioral biases: The role of testosterone and stress," Economics & Human Biology, Elsevier, vol. 29(C), pages 1-16.
    4. Eugene F. Fama & Kenneth R. French, 2010. "Luck versus Skill in the Cross‐Section of Mutual Fund Returns," Journal of Finance, American Finance Association, vol. 65(5), pages 1915-1947, October.
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