Quantum computational finance for martingale asset pricing in incomplete markets.

ABSTRACT: A derivative is a financial asset whose future payoff is a function of underlying assets. Pricing a financial derivative involves setting up a market model, finding a martingale ("fair game") probability measure for the model from the existing asset prices, and using that probability measure to price the derivative. When the number of underlying assets and/or the number of market outcomes in the model is large, pricing can be computationally demanding. In this work, we first formulate the pricing problem in a linear algebra setting, including the realistic setting of incomplete markets where derivatives do not have a unique price. We show that the problem can be solved with a variety of quantum techniques such as quantum linear programming and the quantum linear systems algorithm. While in

SUBMITTER: Rebentrost P 

PROVIDER: S-EPMC11327356 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature