Insights on the Statistics and Market Behavior of Frequent Batch Auctions

Thiago W. Alves, Ionuţ Florescu () and Dragos Bozdog
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Thiago W. Alves: Hanlon Labs, Stevens Institute of Technology, 525 River Street, Babbio Center, Hoboken, NJ 07030, USA
Ionuţ Florescu: Hanlon Labs, Stevens Institute of Technology, 525 River Street, Babbio Center, Hoboken, NJ 07030, USA

Mathematics, 2023, vol. 11, issue 5, 1-26

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.

Keywords: financial engineering; high-frequency trading; market microstructure; continuous double auctions; frequent batch auctions (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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