Making Big Decisions When Seconds Equal Money
Quantum-driven financial models represent potential competitive edge for investors
In the world of financial services, time can represent both money and opportunity lost. The potential time savings from the use of quantum computing can help investors ensure they accrue more money than regret. Financial giants such as JPMorgan Chase & Co., Goldman Sachs, Wells Fargo, and HSBC are increasingly investing in quantum computing to stay ahead.
A key potential application for quantum computing in finance involves finding optimal solutions to a wide range of problems, including portfolio management, securities settlement, index tracking, pricing financial instruments, and risk analysis. Many optimization problems involve making numerous choices, such as buying at least a minimum amount of an asset, creating a combinatorial optimization problem.
The number of possible combinations of choices involved “grows exponentially with the number of decisions to be made,” said Stefan Woerner, manager of the quantum computational science group at IBM Research Europe. “This can lead to problems that are difficult to solve with a classical computer.”
A quantum computer taps into quantum mechanical properties of superposition, entanglement, and interference to explore compute space inaccessible to classical computers. As quantum technology improves, this could lead to huge benefits in speed. Where a classical computer might need to examine a set of a million choices sequentially to reach a solution, a quantum computer could use probability to reduce the number of choices to a few thousand. Faster analysis would make it possible to respond quickly to changes in financial markets and for investors to make rapid decisions.
The speed at which quantum computers may one day theoretically work would also give them time to investigate more potential solutions with greater accuracy. “If financial models on quantum computers are even 0.1% more accurate, it will be like printing money,” said Mark Jackson, Ph.D., senior quantum evangelist at quantum computing hardware and software firm Quantinuum. “A financial model doesn’t have to be 100% correct — it just needs to be more correct than the other guy’s.”
“Most large banks have been investigating quantum computing for a long time, including making significant investments in some of the first startups in the early 2010s,” says Carl Dukatz, global quantum computing lead at consulting firm Accenture. “They see the disruption this technology may potentially cause and [the risk of] not being among the first movers in a field that could put companies out of business overnight.”
IBM, which possesses a fleet of quantum computers accessible via the cloud, has partnered with many large banks. The company teamed up with JPMorgan Chase to use quantum computing to estimate the price of a European call option, which allows the owner to buy an asset at a fixed price at a specific moment in the future. IBM is also working with Wells Fargo, Goldman Sachs, and HSBC to detect fraud and develop higher-earning investment portfolios.
Most large banks have been investigating quantum computing for a long time...They see the disruption this technology may potentially cause and [the risk of] not being among the first movers in a field that could put companies out of business overnight.
Accenture has similarly worked with BBVA, one of the world’s largest financial institutions, to explore how best to use quantum computing to gain a competitive advantage. In partnership with quantum computing pioneer D-Wave, they constructed quantum algorithms for currency arbitrage, credit scoring, and optimizing trading trajectories. They found quantum computing might show benefits in cases when the number of variables grows to a level that classical computing struggles with — for instance, at least a dozen assets with currency arbitrage.
“We’ve also worked with large insurance companies to minimize reinsurance risk with third parties,” Dukatz said.
Ally Financial has similarly partnered with Spanish quantum software firm Multiverse Computing to optimize investment portfolios automatically with returns that match traditional portfolios using significantly smaller sets of stocks. They employed both quantum and classical computers in a hybrid strategy to construct a Nasdaq 100 fund that was four times smaller than conventional portfolios, and 10 times smaller than the S&P 500 fund.
Multiverse also partnered with BBVA to determine the optimal trading path for an investment portfolio consisting of 52 assets among a sample of 10,382 candidates, using actual fluctuating daily market price data corresponding to an eight-year time frame. Processing such a large amount of data would have taken a classical computer roughly two days, but they found it took a matter of seconds using quantum algorithms.
“We’ve used quantum computing to develop simulations for the Bank of Canada regarding the adoption of cryptocurrencies as a method of payment by nonfinancial players, and for Credit Agricole regarding the valuation of financial products and the assessment of credit risks,” said Esperanza Cuenca, Multiverse’s head of strategy and outreach.
As powerful as quantum computers may theoretically one day be, they are currently so prone to error and relatively limited in scale that their ultimate utility is often questioned. Still, Woerner noted, IBM recently revealed that its Eagle quantum processor achieved “utility” beyond today’s supercomputers in accurately simulating Ising models, an important research tool that simplifies parts of nature that represent interacting atoms — a promising step that could soon also mean breakthroughs in delivering accurate results on useful problems in other domains.
“Now the challenge is on all applications researchers to find algorithms that can leverage such a tool in applications relevant for finance,” he said.
