Quantum Computational Finance: Quantum Algorithm for Portfolio Optimization
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13218_2024_870_ReferencePDF.pdf
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404.56 KB
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Author(s)
Rebentrost, Patrick
Lloyd, Seth
Date Issued
August 12, 2024
Journal
KI - Künstliche Intelligenz
Publisher
Springer Berlin Heidelberg
Citation
Rebentrost, P., Lloyd, S. Quantum Computational Finance: Quantum Algorithm for Portfolio Optimization. Künstl Intell 38, 327–338 (2024).
Version
Author's final manuscript
Abstract
We present a quantum algorithm for portfolio optimization. We discuss the market data input of asset prices, the processing of such data via quantum operations, and the output of financially relevant results. Given quantum access to a historical record of asset returns, the algorithm determines the optimal risk-return tradeoff curve and allows one to sample from the optimal portfolio. The algorithm can in principle attain a run time of poly ( log ( N ) ) , where N is the number of assets. Direct classical algorithms for determining the risk-return curve and other properties of the optimal portfolio take time poly ( N ) and we discuss potential quantum speedups in light of efficient classical sampling approaches.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Research Laboratory of Electronics
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Creative Commons Attribution-Noncommercial-ShareAlike
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DOI of Published Version
https://doi.org/10.1007/s13218-024-00870-9
