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arxiv: 2012.01121 · v1 · pith:GOSVTKK6new · submitted 2020-11-13 · 💱 q-fin.PM · math.OC· quant-ph

Portfolio Optimisation Using the D-Wave Quantum Annealer

classification 💱 q-fin.PM math.OCquant-ph
keywords d-waveoptimisationproblemquantumannealerinstancesportfolioproblems
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The first quantum computers are expected to perform well at quadratic optimisation problems. In this paper a quadratic problem in finance is taken, the Portfolio Optimisation problem. Here, a set of assets is chosen for investment, such that the total risk is minimised, a minimum return is realised and a budget constraint is met. This problem is solved for several instances in two main indices, the Nikkei225 and the S\&P500 index, using the state-of-the-art implementation of D-Wave's quantum annealer and its hybrid solvers. The results are benchmarked against conventional, state-of-the-art, commercially available tooling. Results show that for problems of the size of the used instances, the D-Wave solution, in its current, still limited size, comes already close to the performance of commercial solvers.

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