Apply Deep Reinforcement Learning with Quantum Computing on the Pricing of American Options

Junzheng Yang

Chapter 50 in Internet Finance and Digital Economy:Advances in Digital Economy and Data Analysis Technology, 2023, pp 675-694 from World Scientific Publishing Co. Pte. Ltd.

Abstract: American options are important financial products traded in enormous volumes across the world. Therefore, accurate and efficient valuation is of paramount importance for global financial markets. Due to the early exercise feature, the pricing of American options is significantly more complicated than European options, and an analytical closed-form solution is unavailable even for simple dynamic models. Practitioners employ various valuation methods to strike the balance: accurate valuation usually suffers inefficiency, while fast valuation likely leads to inaccuracy. In this paper, we provide an innovative solution to address both the accuracy and efficiency issues of pricing American options by applying quantum reinforcement learning. Meanwhile, the quantum part of the new approach would potentially speed up the calculation dramatically.

Keywords: Internet Economy; Online Finance; Financial Engineering; Big Data; Blockchain; Supply Chain; E-commerce (search for similar items in EconPapers)
JEL-codes: G2 O33 (search for similar items in EconPapers)
Date: 2023
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