Goldman Sachs claim quantum trading algorithm breakthrough

Goldman Sachs and QC Ware researchers claim to have created quantum algorithms that outperform the most advanced classical algorithms for Monte Carlo simulations.

A Monte Carlo algorithm is a randomised algorithm - which uses randomness as part of its reasoning process - whose output may be incorrect.

These types of algorithms are commonly used by traders at investment banks seeking an edge over the competition, evaluating risk and simulating prices for a variety of different financial instruments.

The companies claimed that since these calculations are executed overnight, traders are forced made decisions based on outdated results in volatile markets.

Using a quantum computing approach to perform these risk assessments faster means that simulations could be executed throughout the day, which could change the way financial markets operate according to the companies.

The companies said these can be used on hardware expected to be available in 5 to 10 years.

Monte Carlo algorithms are also commonly used in industries outside of finance, such as aeronautical engineering, biology, and 3D computer graphics.

The news as comes BigTech companies, particularly Google, IBM, and Microsoft, are pouring significant resources into developing quantum computing
In June 2019, Theresa May’s administration announced plans to invest £153 million in quantum computing to position the UK as a leader emerging sector.

“Our team at Goldman Sachs is focused on developing the best technology for the firm and our clients,” said William Zeng, head of quantum research at Goldman Sachs. “Quantum computing could have a significant impact on financial services, and our new work with QC Ware brings that future closer.”

“To do this, we introduced new extensions to a core technique in quantum algorithms.”

He added: “This exemplifies the fundamental contributions that our group looks to make in the field of quantum technology.”

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