Quantum two-sample test for investment strategies
Quantum algorithms display high discriminatory power in the classification of probability distributions
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David Garvin, Oleksiy Kondratyev, Alexander Lipton and Marco Paini demonstrate the benefits of using a quantum algorithm rather than its classical counterpart on one of the most fundamental problems of quantitative finance: the classification of probability distributions. This problem has many direct applications to practical financial use cases, including time series analysis, detection of structural breaks and monitoring of alpha decay. The authors present an
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