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Option Pricing using Quantum Computers

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Nikitas Stamatopoulos1, Daniel J. Egger2, Yue Sun1, Christa Zoufal2,3, Raban Iten2,3, Ning Shen1, and Stefan Woerner2

1Quantitative Research, JPMorgan Chase & Co., New York, NY, 10017
2IBM Quantum, IBM Research – Zurich
3ETH Zurich

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Abstract

We present a methodology to price options and portfolios of options on a gate-based quantum computer using amplitude estimation, an algorithm which provides a quadratic speedup compared to classical Monte Carlo methods. The options that we cover include vanilla options, multi-asset options and path-dependent options such as barrier options. We put an emphasis on the implementation of the quantum circuits required to build the input states and operators needed by amplitude estimation to price the different option types. Additionally, we show simulation results to highlight how the circuits that we implement price the different option contracts. Finally, we examine the performance of option pricing circuits on quantum hardware using the IBM Q Tokyo quantum device. We employ a simple, yet effective, error mitigation scheme that allows us to significantly reduce the errors arising from noisy two-qubit gates.

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[2] Dmitry Grinko, Julien Gacon, Christa Zoufal, and Stefan Woerner, “Iterative Quantum Amplitude Estimation”, arXiv:1912.05559.

[3] Lee Braine, Daniel J. Egger, Jennifer Glick, and Stefan Woerner, “Quantum Algorithms for Mixed Binary Optimization applied to Transaction Settlement”, arXiv:1910.05788.

[4] Julia E. Rice, Tanvi P. Gujarati, Tyler Y. Takeshita, Joe Latone, Mario Motta, Andreas Hintennach, and Jeannette M. Garcia, “Quantum Chemistry Simulations of Dominant Products in Lithium-Sulfur Batteries”, arXiv:2001.01120.

[5] Juan José García-Ripoll, “Quantum-inspired algorithms for multivariate analysis: from interpolation to partial differential equations”, arXiv:1909.06619.

[6] Iordanis Kerenidis, Anupam Prakash, and Dániel Szilágyi, “Quantum Algorithms for Portfolio Optimization”, arXiv:1908.08040.

[7] Christa Zoufal, Aurélien Lucchi, and Stefan Woerner, “Variational Quantum Boltzmann Machines”, arXiv:2006.06004.

[8] Filipe Fontanela, Antoine Jacquier, and Mugad Oumgari, “A Quantum algorithm for linear PDEs arising in Finance”, arXiv:1912.02753.

[9] Adam Holmes and A. Y. Matsuura, “Efficient Quantum Circuits for Accurate State Preparation of Smooth, Differentiable Functions”, arXiv:2005.04351.

[10] Almudena Carrera Vazquez and Stefan Woerner, “Efficient State Preparation for Quantum Amplitude Estimation”, arXiv:2005.07711.

[11] Austin Gilliam, Stefan Woerner, and Constantin Gonciulea, “Grover Adaptive Search for Constrained Polynomial Binary Optimization”, arXiv:1912.04088.

[12] Koichi Miyamoto and Kenji Shiohara, “Reduction of Qubits in Quantum Algorithm for Monte Carlo Simulation by Pseudo-random Number Generator”, arXiv:1911.12469.

[13] Ikko Hamamura and Takashi Imamichi, “Efficient evaluation of quantum observables using entangled measurements”, arXiv:1909.09119.

[14] Sergi Ramos-Calderer, Adrián Pérez-Salinas, Diego García-Martín, Carlos Bravo-Prieto, Jorge Cortada, Jordi Planagumà, and José I. Latorre, “Quantum unary approach to option pricing”, arXiv:1912.01618.

[15] Daniel J. Egger, Claudio Gambella, Jakub Marecek, Scott McFaddin, Martin Mevissen, Rudy Raymond, Andrea Simonetto, Stefan Woerner, and Elena Yndurain, “Quantum computing for Finance: state of the art and future prospects”, arXiv:2006.14510.

[16] Julien Gacon, Christa Zoufal, and Stefan Woerner, “Quantum-Enhanced Simulation-Based Optimization”, arXiv:2005.10780.

[17] Xavier Vasques, “The data center of tomorrow is made up of heterogeneous accelerators”, arXiv:2003.10950.

[18] Samuel Mugel, Carlos Kuchkovsky, Escolastico Sanchez, Samuel Fernandez-Lorenzo, Jorge Luis-Hita, Enrique Lizaso, and Roman Orus, “Dynamic Portfolio Optimization with Real Datasets Using Quantum Processors and Quantum-Inspired Tensor Networks”, arXiv:2007.00017.

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The above citations are from SAO/NASA ADS (last updated successfully 2020-07-06 15:48:27). The list may be incomplete as not all publishers provide suitable and complete citation data.

Could not fetch Crossref cited-by data during last attempt 2020-07-06 15:48:26: Could not fetch cited-by data for 10.22331/q-2020-07-06-291 from Crossref. This is normal if the DOI was registered recently.

Source: https://quantum-journal.org/papers/q-2020-07-06-291/

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