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CQC Publishes “How Quantum Computing Will Reshape Finance”

By IQT News posted 11 Jun 2020

(CambridgeQuantumComputing) Cambridge Quantum Computing has released a white paper style report “How Quantum Computing Will Reshape Finance”. Authors are Dr. Mark Jackson and Dr. Mattia Fiorentini of Cambridge Quantum Computing. The document can be downloaded in PDF format by clicking on the source URL provided here.
Background information on quantum computing is first provided in this report. Then the authors move to discussing the benefits of quantum computing in finance.
There are a few algorithms which are ubiquitous in the financial industry, and therefore are ripe targets for seeking improvement using quantum computing. A class of interesting programs goes by the name of Monte Carlo, after the famous gambling region in Monaco. Monte Carlo programs are useful to estimate the likelihood of certain outcomes in processes where all the details are too complex to be accounted for exactly.Monte Carlo simulations can be sped up using quantum computing. Classically, doubling the number of simulations doubles the amount of time required to get an improved answer. With a quantum computer, we can do better and reach the same, improved accuracy by generating fewer samples, thus substantially reducing computational costs.

Another use case of quantum computing in finance is of optimization. In many problems we are trying to minimize or maximize an objective function under some constraints, for instance, minimizing risk or maximizing profit. This is achieved by varying the parameters of the system we are constructing to reach the optimum. With a large number of parameters, often depending on each other in complex or unknown ways, it is challenging to devise computational techniques that find the optimum efficiency. As a consequence, we are left with the only option of trying all the possible so-lutions, which is often very computationally costly. In these scenarios, quantum algorithms have been proven to beat classical algorithms making this sort of “parameter searches” much more efficient.

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