Quantum computing delivered better performance than classical computing for this application, but still needs refining before being used in production.
Quantum computing has been described as a solution looking for a problem, and a tie-up between HSBC and IBM is an example of how the emerging technology can be used in the business world. The two companies have combined in a project that could help banks with planning for future trades.
The project is the first example of quantum computing being used in algorithmic trading, according to HSBC and IBM. They used different models to predict how likely bonds would be to trade at a given price, and found that quantum computing performed better than classical computing models — in some cases, 34 percent better.
According to HSBC, algorithmic trading is a good fit for quantum computing due to the highly complex nature of the market conditions that underlie trading. In this trial, it used computer models in a simulated competitive bidding process to price customer inquiries in the automated bond-trading process.
The trial used trading data from Sept. 1, 2023, to Oct. 29, 2024, covering 1 073 926 requests for quotes (RFQs) relating to 5166 bonds and 747 associated tickers. It used IBM’s System 2 quantum machine with the latest Heron processors for the quantum computing involved.
An ideal test market
Jack Jacquier, Professor of Mathematics at Imperial College, London, agreed that it was an ideal market in which to test the technology. “For some time there has been a question of what we can do with quantum computing. This is ideal for quantum as they have big problems to solve.”
Gartner research vice president Matthew Brisse endorsed this view. “The financial industry has been focusing on stochastic modeling, optimization, and machine learning for derivative pricing, risk analysis, portfolio/trade optimization, hedging, swap netting, and anomaly detection to see where quantum computing could have an impact. Adding quantum-enabled algorithmic trading with quantum computing on real industry data is a major step in quantum computing’s evolution to business value,” he said.
One of the scientists involved in the project warned that there was some time to go before companies would be routinely adopting quantum as part of their everyday IT system. Manuel Proissl, IBM’s quantum industry applications lead for financial services, said, “The trial was successful but there are certain questions that we still need to answer.” In the long term, he said, quantum will have a place in the financial world but “it’s complex to move this to a trading environment. The trial worked within a confined time scale. The next step will be working with different periods of time.”
Jacquier agreed. “IBM have been very honest about the limitations of the project. There’s still some way to go. Refining the algorithm will be part classical computing and part quantum but they don’t know how much of each.”
It’s hard to say when quantum computing will become mainstream, he said. “Every case is different. What is clear is that there won’t be a quantum machine that will be able to solve every problem — they will be tied to particular applications.” But, he said, “Financial institutions will be one of the first to adopt the technology. They are already leading the way — HSBC and JP Morgan particularly, although two smaller banks, Standard Chartered and BBVA are also innovating in this field.”
However, don’t expect to see quantum as part of these institutions’ infrastructure for some time. “This is very expensive and I can’t see banks running their own quantum models — not for a very long time at least.”
