Developing a Framework for Real-Time Trading in a Laboratory Financial Market

One of the challenges that economic experiments that use artificial financial markets to explore high-frequency trading face, is the development of a sufficiently sophisticated software. Moreover, it is not trivial to adequately communicate the complex financial market rules to non-experts. The present paper is part of an ongoing project with Peter Cramton, Daniel Friedman, Kristian Lopez Vargas, and Axel Ockenfels in which a novel framework enabling algorithmic real-time trading at millisecond speeds is being developed. This novel framework provides a more accurate laboratory replication of the financial market mechanisms relevant to high-frequency trading than has been achieved up to this point. This will provide a basis for comparing the current financial market design with new, exciting market design approaches, both under normal and stressful market conditions. The ongoing project includes the development of the theoretical foundations, as well as the experimental design and the analysis of the corresponding data. The contribution of the present study consists of deriving parameters for the replication of short-lived financial market crashes that can be adopted by the new framework for real-time trading; to provide means for an adequate communication of complex financial market rules to non-experts; and to provide solutions to technical and conceptual difficulties encountered in the preparation for the realization of the experiment. In addition, a thorough review of the literature most relevant to the new framework for real-time trading is provided.