Optimal Broker Pricing to Balance Client Flow and Toxic Flow Losses

Summary

This document models a broker serving both informed and uninformed clients as an infinite-horizon stochastic control problem. It derives a closed-form optimal dealing strategy and uses that result to propose an algorithm intended to work in live trading without calibrating each model parameter individually.

The analysis also characterizes the liquidity discount offered to clients. The broker must balance attracting client orders against losses from trading with informed clients. The document describes theoretical results and a practical algorithm, but the supplied text gives no data, numerical performance evidence, or details on the model assumptions and limits of real-world deployment.

Key ideas

• The broker's interaction with informed and uninformed clients is formulated as a stochastic control problem.
• The optimal dealing strategy is derived in closed form.
• An algorithm is proposed to avoid individual parameter calibration.
• The liquidity discount balances client order flow against adverse selection losses.

Tags

# A Simple Strategy to Deal with Toxic Flow


# A Simple Strategy to Deal with Toxic Flow









We model the trading activity between a broker and her clients (informed and uninformed traders) as an infinite-horizon stochastic control problem. We derive the broker's optimal dealing strategy in closed form and use this to introduce an algorithm that bypasses the need to calibrate individual parameters, so the dealing strategy can be executed in real-world trading environments. Finally, we characterise the discount in the price of liquidity a broker offers clients. The discount strikes the optimal balance between maximising the order flow from the broker's clients and minimising adverse selection losses to the informed traders.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.