E Brinkman and MP Wellman

Proceedings of the 18th ACM Conference on Economics and Computation, pages 205–221, June 2017.


Several recent authors have advocated for financial markets to move from continuous clearing to discrete or batched clearing, as a way to defeat the latency arms race: the never-ending quest for small advantages in time to access markets. How frequently should such a modern batch auction clear? We conduct a systematic simulation-based investigation on the relationship between clearing frequency and metrics of market quality, such as allocative efficiency, comparing the performance of discrete and continuous auction mechanisms under empirical equilibrium behavior of all participating traders. In effect we perform empirical mechanism design on frequent batch auctions. We find that in a wide array of environments, equilibrium efficiency is improved for small positive intervals but falls off dramatically when there are too few opportunities to trade. The result is a large range of batch frequencies that are near optimally efficient; this range is wider in thick markets.



ACM DL Author-ize serviceEmpirical Mechanism Design for Optimizing Clearing Interval in Frequent Call Markets

Erik Brinkman, Michael P. Wellman
EC ’17 Proceedings of the 2017 ACM Conference on Economics and Computation, 2017