Ahmet Umur Özsoy, Ömür Uğur, The QLBS Model Within the Presence of Feedback Loops Through the Impacts of a Large Trader, Computational Economics, XX: XX (April 2025).
Abstract
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.
Keywords: Agent-based modeling, Batch-mode reinforcement learning, Market impacts, Fitted Q-iteration, QLBS, FX option pricing, Large trader
The preprint version of the article: The QLBS Model within the Presence of Feedback Loops through the Impacts of a Large Trader, jointly with Ahmet Umur Özsoy, in arXiv (November 2023), DOI: 10.48550/arXiv.2311.06790. PlumX