Picking Efficient Portfolios from 3,171 US Common Stocks with New Quantum and Classical Solvers
Jeffrey Cohen, Clark Alexander
TL;DR
This paper compares classical and quantum algorithms for constructing efficient stock portfolios from over 3,000 US stocks, introducing new solvers and demonstrating their application in portfolio optimization.
Contribution
It introduces a novel combination of classical and quantum solvers, including a new classical bifurcator and the D-Wave Advantage quantum annealer, for portfolio optimization.
Findings
Quantum annealing offers competitive solutions compared to classical methods.
The new bifurcator classical solver enhances portfolio optimization.
Quantum and classical approaches achieve similar efficiency in portfolio selection.
Abstract
We analyze 3,171 US common stocks to create an efficient portfolio based on the Chicago Quantum Net Score (CQNS) and portfolio optimization. We begin with classical solvers and incorporate quantum annealing. We add a simulated bifurcator as a new classical solver and the new D-Wave Advantage(TM) quantum annealing computer as our new quantum solver.
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum Mechanics and Applications