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       Department of Systems Engineering and Engineering Management

                           The Chinese University of Hong Kong

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Date: Tuesday, November 26, 2024, 11:00 am to 11:55 am HKT

Venue: ERB 513, The Chinese University of Hong Kong

Title: Anonymity, Signaling, and Collusion in Limit Order Books

Speaker: Patrick Chang, Oxford-Man Institute, University of Oxford



Abstract:

A key feature of a limit order book is the anonymity of limit orders. We use a proprietary dataset with trader identification and find that market makers break the anonymity of limit orders. Market makers signal themselves by posting limit orders with large volumes and their response to the arrival of limit orders depends on whether the orders include the volume signal. Limit orders with volume signals help market makers to avoid trading with each other and to snipe retail limit orders. We present a model of the limit order book that considers competitive and collusive equilibria. The model shows that the behavior of market makers we observe in the data is consistent with the collusive equilibrium. In the collusive equilibrium, market makers use signals that identify each other to avoid sniping each other's limit orders in an otherwise anonymous book. Signaling enables market makers to share the profitable and benign flow from retail limit orders, and to share the additional flow from impatient investors who otherwise would have traded with a retail investor's limit order.



Biography:

Patrick Chang is a PhD student at the Oxford-Man Institute under the supervision of Professor Álvaro Cartea. His research aims to understand the interaction of multiple autonomous agents, and the impact and risk these interactions have on the broader economy and financial markets. Of particular interest, is whether the agents learn to collude or manipulate markets, and whether we can detect and prevent these unintended consequences to protect social welfare and improve market efficiency.



Everyone is welcome to attend the talk!

SEEM-5201 Website: https://seminar.se.cuhk.edu.hk

Email: seem5201@se.cuhk.edu.hk