Researchers have demonstrated that usable results for financial modelling are achievable even on current noisy quantum computersIn a groundbreaking collaboration, HSBC, quantum middleware developer Haiqu, and a team of academic researchers have pioneered an efficient method to run financial models on commercially available quantum computing hardware. This joint research, published in Physical Review Research, presents a novel approach to encoding real-world probability distributions into quantum circuits.
As quantum computing evolves into commercially viable products, financial institutions like HSBC are exploring ways to secure financial transactions. One such method is the use of post-quantum cryptography to protect financial systems. Quantum computers also provide banks with the ability to run more powerful financial market simulations, a capability that HSBC is keen to leverage.
The research team, comprising experts from HSBC, Haiku, Czech Technical University, University of Zurich, the Akhiezer Institute for Theoretical Physics, Karazin Kharkiv National University in Ukraine, and Greece’s Athena Research Center, focused on Lévy distributions. These are commonly used in modelling extreme variations of stock market indexes worldwide.
The researchers stated in their paper, “By developing methods to efficiently work with Lévy distributions on a quantum computer, we pave the way for more precise modeling of market behaviours, particularly in capturing heavy tails, skewness, and volatility clustering.”
Haiqu points out that while quantum computing can be used in derivative pricing, portfolio optimisation, fraud detection, and machine learning, these applications require realistic financial distributions. This necessitates the loading of data into a quantum computer. The process of encoding classical data into quantum states is widely recognised as a significant bottleneck when implementing many quantum algorithms on hardware. This challenge is particularly relevant for applications such as financial risk modelling and simulation, where complex probability distributions must be loaded onto quantum devices.
The number of required quantum operations in conventional algorithms can scale exponentially with the number of qubits, according to Haiqu. This presents a significant bottleneck on today’s noisy, depth-limited hardware. To address this issue, Haiqu has developed compact quantum circuits with linear, rather than exponential, scaling.
Mykola Maksymenko, co-founder and CTO of Haiqu, said, “One of the biggest practical barriers is getting realistic financial data onto today’s quantum hardware. This work shows a scalable path around that barrier and helps move quantum finance workflows from theory toward execution.”
The researchers used matrix product state (MPS) methods to construct shallow quantum circuits that encode smooth functions, including probability distributions, directly into quantum states. Using a 25 qubit IBM quantum computer, the research paper stated that the accuracy of the machine was sufficient to pass quantitative statistical tests.
This collaboration between HSBC, Haiqu, and the academic researchers represents a significant step forward in the field of quantum finance. By developing an efficient method to run financial models on quantum computing hardware, they have opened up new possibilities for more precise market behaviour modelling. This could potentially revolutionise the way financial institutions operate, offering them a powerful tool to secure transactions and run more robust financial market simulations.
