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Marking a significant step in the roadmap for quantum advantage for financial applications, Goldman Sachs and QC Ware researchers have designed new, robust quantum algorithms that outperform state-of-the-art classical algorithms for Monte Carlo simulations and can be used on near-term quantum hardware expected to be available in 5 to 10 years.
Monte Carlo methods, used to evaluate risk and simulate prices for a variety of financial instruments, involve complex calculations and consume significant time and computational resources. Typically, these calculations are executed once overnight, which means that in volatile markets, traders are forced to use outdated results. Providing traders, who are always looking for an additional edge in the markets, with a quantum computing approach to perform these risk assessments with far greater speed means that simulations could be executed throughout the day and could transform the way financial markets worldwid
Goldman Sachs and QC Ware Collaboration Brings New Way to Price Risky Assets within Reach of Quantum Computers
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PALO ALTO, Calif., April 29, 2021 /PRNewswire/ Marking a significant step in the roadmap for quantum advantage for financial applications, Goldman Sachs and
QC Ware researchers have designed new, robust quantum algorithms that outperform state-of-the-art classical algorithms for Monte Carlo simulations and can be used on near-term quantum hardware expected to be available in 5 to 10 years.
Monte Carlo Algorithms Comparative Chart
Monte Carlo methods, used to evaluate risk and simulate prices for a variety of financial instruments, involve complex calculations and consume significant time and computational resources. Typically, these calculations are executed once overnight, which means that in volatile markets, traders are forced to use outdated results. Providing traders, who are always looking for an addit