Insider Brief
- A collaboration of companies demonstrated how a new algorithm run on a quantum annealing system can optimize investment portfolios automatically with returns that match traditional portfolios.
- Multiverse Computing, Protiviti and Ally Financial worked together on the project.
- The researchers used hybrid classical-quantum approaches to build investment portfolios for companies in the Nasdaq 100 and the S&P 500 and used daily returns over the course of a year. The quantum-built portfolios significantly outperformed the risk profile of the target index by up to 2x.
PRESS RELEASE — Researchers from Multiverse Computing, a global leader in delivering value-based quantum computing solutions, and Protiviti, a global consulting firm, working with Ally Financial, an industry leader in digital financial services, have released a study demonstrating how a new algorithm run on a quantum annealing system (technology for finding optimal solutions) can optimize investment portfolios automatically with returns that match traditional portfolios.
The joint team of quantum computing engineers and financial analysts developed a hybrid quantum-classical approach to financial index tracking portfolios that maximizes returns and minimizes risk. The paper about the study, titled, “Financial Index Tracking via Quantum Computing with Cardinality Constraints” can be found here.
“Together, we have broken new ground, advancing a quantum-based solution to a portfolio optimization problem that remains challenging for classical computers. As quantum hardware performance improves, there will be increased opportunities to provide even better returns with less market risk,” said Ally Financial’s Chief Information, Data and Digital Officer Sathish Muthukrishnan. “I’m proud of the quantum team in continuing to explore various use cases that benefit our customers and help Ally to see around corners.”
Leveraging previous hybrid classical-quantum approaches, the researchers built investment portfolios for companies in the Nasdaq 100 and the S&P 500 and used daily returns over the course of a year.
The team then used the algorithm to build investment portfolios that can generate the same financial returns as traditional portfolios with significantly smaller groups of stocks. Replicating financial indexes using a limited subset of assets, known as cardinality constraints, has historically been an extremely difficult challenge. The number of stocks in the team’s Nasdaq 100 fund was four times smaller than traditional portfolios and 10 times smaller in the S&P 500 fund.
The research team also built an enhanced tracking portfolio as part of the project, which showed that the quantum-built portfolios significantly outperformed the risk profile of the target index by up to 2x.
“Financial managers can use the algorithm today to meet specific investing goals or other customized requirements for clients,” said Mehdi Bozzo-Rey, Chief Revenue Officer at Multiverse Computing. “Once the hardware achieves quantum advantage, we will be able to solve this problem instantaneously and solve it exactly.”
“For example, this new algorithm can be used for managing ETF funds, reducing overhead costs for financial managers while helping keep fees low for customers,” according to Konstantinos Karagiannis, Protiviti’s director of Quantum Computing Services. “It’s a major step forward in placing Ally Financial at the forefront of quantum computing research in the financial industry.”
Sam Palmer, head of Financial Engineering at Multiverse Computing, co-authored the research paper along with Karagiannis and Adam Florence, Director of Data Science at Ally Financ
For more market insights, check out our latest quantum computing news here.
