Insights on the Statistics and Market Behavior of Frequent Batch Auctions

Abstract

This paper extends previous research performed with the SHIFT financial market simulation platform. In our previous work, we show how this order-driven, distributed asynchronous, and multi-asset simulated environment is capable of reproducing known stylized facts of real continuous double auction financial markets. Using the platform, we study a pricing mechanism based on frequent batch auctions (FBA) proposed by a group of researchers from University of Chicago. We demonstrate our simulator’s capability as an environment to experiment with potential rule changes. We present the first side-by-side comparison of frequent batch auctions with a continuous double auction. We show that FBA is superior in terms of market quality measures but we also discover a potential problem in the technical implementation of FBA.