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arxiv: 2008.08669 · v1 · pith:4OE3JEX3new · submitted 2020-08-19 · 💱 q-fin.GN · quant-ph

Portfolio Optimization of 60 Stocks Using Classical and Quantum Algorithms

classification 💱 q-fin.GN quant-ph
keywords d-wavequantumportfolioannealingclassicaloptimaloptimizationportfolios
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We continue to investigate the use of quantum computers for building an optimal portfolio out of a universe of 60 U.S. listed, liquid equities. Starting from historical market data, we apply our unique problem formulation on the D-Wave Systems Inc. D-Wave 2000Q (TM) quantum annealing system (hereafter called D-Wave) to find the optimal risk vs return portfolio. We approach this first classically, then using the D-Wave, to select efficient buy and hold portfolios. Our results show that practitioners can use either classical or quantum annealing methods to select attractive portfolios. This builds upon our prior work on optimization of 40 stocks.

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