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Fundamental theorem for quantum asset pricing

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  • Jinge Bao
  • Patrick Rebentrost

Abstract

Quantum computers have the potential to provide an advantage for financial pricing problems by the use of quantum estimation. In a broader context, it is reasonable to ask about situations where the market and the assets traded on the market themselves have quantum properties. In this work, we consider a financial setting where instead of by classical probabilities the market is described by a pure quantum state or, more generally, a quantum density operator. This setting naturally leads to a new asset class, which we call quantum assets. Under the assumption that such assets have a price and can be traded, we develop an extended definition of arbitrage to quantify gains without the corresponding risk. Our main result is a quantum version of the first fundamental theorem of asset pricing. If and only if there is no arbitrage, there exists a risk-free density operator under which all assets are martingales. This density operator is used for the pricing of quantum derivatives. To prove the theorem, we study the density operator version of the Radon-Nikodym measure change. We provide examples to illustrate the theory.

Suggested Citation

  • Jinge Bao & Patrick Rebentrost, 2022. "Fundamental theorem for quantum asset pricing," Papers 2212.13815, arXiv.org, revised Apr 2023.
  • Handle: RePEc:arx:papers:2212.13815
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    References listed on IDEAS

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    1. Luigi Accardi & Andreas Boukas, 2007. "The Quantum Black-Scholes Equation," Papers 0706.1300, arXiv.org.
    2. Anantya Bhatnagar & Dimitri D. Vvedensky, 2022. "Quantum effects in an expanded Black-Scholes model," Papers 2203.07940, arXiv.org.
    3. Robert C. Merton, 2005. "Theory of rational option pricing," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 8, pages 229-288, World Scientific Publishing Co. Pte. Ltd..
    4. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    5. Orrell, David, 2020. "A quantum model of supply and demand," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    6. Dylan Herman & Cody Googin & Xiaoyuan Liu & Alexey Galda & Ilya Safro & Yue Sun & Marco Pistoia & Yuri Alexeev, 2022. "A Survey of Quantum Computing for Finance," Papers 2201.02773, arXiv.org, revised Jun 2022.
    7. Jeong Yu Han & Patrick Rebentrost, 2022. "Quantum advantage for multi-option portfolio pricing and valuation adjustments," Papers 2203.04924, arXiv.org.
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    Cited by:

    1. Lane P. Hughston & Leandro S'anchez-Betancourt, 2023. "Valuation of a Financial Claim Contingent on the Outcome of a Quantum Measurement," Papers 2305.10239, arXiv.org, revised Oct 2023.

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