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arXiv:quant-ph/0112158

Quantum Finance: The Finite Dimensional Case

Zeqian Chen

Published Dec 26, 2001• 8 citations
arXivHTMLPDF

Abstract

In this paper, we present a quantum version of some portions of Mathematical Finance, including theory of arbitrage, asset pricing, and optional decomposition in financial markets based on finite dimensional quantum probability spaces. As examples, the quantum model of binomial markets is studied. We show that this quantum model ceases to pose the paradox which appears in the classical model of the binomial market. Furthermore, we re-deduce the Cox-Ross-Rubinstein binomial option pricing formula by considering multi-period quantum binomial markets.

DOI
10.48550/arxiv.quant-ph/0112158

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In this paper, we present a quantum version of some portions of Mathematical Finance, including theory of arbitrage, asset pricing, and optional decomposition in financial markets based on finite dimensional quantum probability spaces. As examples, the quantum model of binomial markets is studied. We show that this quantum model ceases to pose the paradox which appears in the classical model of the binomial market. Furthermore, we re-deduce the Cox-Ross-Rubinstein binomial option pricing formula by considering multi-period quantum binomial markets.
In this paper, a quantum model for the binomial market in finance is proposed. We show that its risk-neutral world exhibits an intriguing structure as a disk in the unit ball of R3,{\bf R}^3,R3, whose radius is a function of the risk-free interest rate with two thresholds which prevent arbitrage opportunities from this quantum market. Furthermore, from the quantum mechanical point of view we re-deduce the Cox-Ross-Rubinstein binomial option pricing formula by considering Maxwell-Boltzmann statistics of the system of NNN distinguishable particles.
In this paper, a quantum model for the binomial market in finance is proposed. We show that its risk-neutral world exhibits an intriguing structure as a disk in the unit ball of R^3, whose radius is a function of the risk-free interest rate with two thresholds which prevent arbitrage opportunities from this quantum market. Furthermore, from the quantum mechanical point of view we re-deduce the Cox-Ross-Rubinstein binomial option pricing formula by considering Maxwell-Boltzmann statistics of the system of N distinguishable particles.
Options are financial derivatives on an underlying security. The Schrodinger and\nHeisenberg approach to the quantum mechanics together with the Dirac matrix\napproaches are applied to derive the Black-Scholes formula and the quantum Cox-\nRubinstein formula.\nThe quantum mechanics approach to option pricing is based on the interpretation\nof the option price as the Schrodinger wave function of a certain quantum mechanics\nmodel determined by Hamiltonian H. We apply this approach to continuous\ntime market models generated by Levy processes.\nIn the discrete time formulization, we construct both self-adjoint and non selfadjoint\nquantum market. Moreover, we apply the discrete time formulization\nand analyse the quantum version of the Cox-Ross-Rubinstein Binomial Model.\nWe find the limit of the N-period bond market, which convergences to planar\nBrownian motion and then we made an application to option pricing in planar\nBrownian motion compared with Levy models by Fourier techniques and Monte\nCarlo method.\nFurthermore, we analyse the quantum conditional option price and compare for\nthe conditional option pricing in the quantum formulization. Additionally, we\nestablish the limit of the spectral measures proving the convergence to the geometric\nBrownian motion model. Finally, we found Binomial Model formula and\nPath integral formulization gave are close to the Black-Scholes formula.
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.
The Quantum Binomial Options Pricing Model is a novel approach to pricingderivatives. It serves as a quantum analogue to the classical binomial optionspricing model, using concepts from quantum mechanics like the Pauli matricesand Bloch sphere to represent the derivatives market. Through usage of a den-sity matrix and mixed states, the model can potentially price derivatives moreaccurately. However, at this time there exist no clear formulae and methodsfor hedging derivatives through this model. This paper numerically tests theperformance of the hedging framework corresponding to the model as comparedto the classical model using a year of historical S&P 500 data. The simulationreveals that the Quantum Binomial Options Pricing model is, at least in itscurrent state, not viable for usage in actually hedging derivatives. This is dueto numerical instabilities, particularly in the Quantum Theta and QuantumVega, the former of which ends up negative, betraying fundamental financialpostulates, and the latter of which is blown out of scale due to the short termnature of the simulation. We conclude that the Quantum Binomial OptionsPricing Model is currently unsuitable for practical applications and that ourfindings reveal the necessity of rigorously testing new financial models againstbenchmark models like the Classical Binomial Options Pricing Model.
A new paradigm based on quantum probability that can model stock markets and price options—and also upends classical quantitative finance. In The Quantum Stock Market, David Orrell combines theory and new empirical findings to argue for a new approach to finance based on quantum probability. The main finding, a property called q-variance, may be unique in finance in that it was discovered as the result of a prediction, affects financial markets in general, has no tunable parameter, and has important consequences for a range of topics including the pricing of financial options. The property, which somehow eluded detection for over a century, has been verified by experts in the field. And the fact that it is incompatible with classical finance—which is perhaps why it went undetected—suggests that the field must be reinvented. Orrell argues for nothing less than a paradigm shift in finance. As with any new work that challenges existing methods the ideas have already received pushback, from leaders in the field of finance to physicists skeptical of applying quantum probability outside its traditional domain. Written in an interdisciplinary style that mixes mathematical equations, data analysis, and informed comments on the field of finance, The Quantum Stock Market should be read by anyone who wants to be on the right side of a paradigm shift.