The QLBS Model Within the Presence of Feedback Loops Through the Impacts of a Large Trader

Date

2025-01-01

Author

Özsoy, Ahmet Umur
Uğur, Ömür

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We extend the QLBS model by considering a large trader whose transactions leave a permanent impact on the exchange rate process and therefore affect the price of contingent claims on such processes. Through a hypothetical limit order book we quantify the exchange rate altered by such transactions. We therefore define the quoted exchange rate process, for which we assume the existence of a postulated hedging strategy. Given the quoted exchange rate and postulated hedging strategy, we find an optimal hedging strategy through batch-mode reinforcement learning given the trader alters the course of the exchange rate process. We assume that the trader has its own concept of fair price and we define our problem as finding the hedging strategy with much lower transaction costs yet delivering a price that well converges to the fair price of the trader. We show our contribution results in an optimal hedging strategy with much lower transaction costs and convergence to the fair price is obtained assuming sensible parameters.

Subject Keywords

Agent-based modeling, Batch-mode reinforcement learning, Fitted Q-iteration, FX option pricing, Large trader, Market impacts, QLBS

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105002351573&origin=inward
https://hdl.handle.net/11511/114394

Collections

Graduate School of Applied Mathematics, Article