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Quantum Algorithms for Portfolio Optimization

By IQT News posted 26 Aug 2019

(Finadium) Researchers from the lab of the Institute on the Foundations of Computer Science at Universite Paris Diderot develop the first quantum algorithm for the constrained portfolio optimization problem. The algorithm has running time where variables are the number of: positivity and budget constraints, assets in the portfolio, desired precision, and problem-dependent parameters related to the well-conditioning of the intermediate solutions.
Mathematical finance is an application area where quantum computers could potentially offer groundbreaking speedups. This is a very recent research area for quantum algorithms and is important in terms of applications as even modest speedups for computational financial problems can have enormous real world impact. It has been suggested that quantum techniques like Feynman integrals could be useful for option pricing. There has also been experimental work where IBM quantum computers have been used to explore quadratic speedups for option pricing and using Monte Carlo methods.

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