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Imperial College London and HSBC demonstrate a practical application of Gaussian Boson Sampling for asset clustering in statistical arbitrage, showing superior alpha generation during high volatility compared to classical methods like Spectral analysis. By addressing photon loss through coherent displacement, the research establishes that heuristic quantum advantages are viable on current imperfect hardware without requiring full fault tolerance. This work marks a significant step toward integrating specialized photonic algorithms into quantitative finance workflows for identifying dense subgraphs in market data.

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Imperial College London And HSBC Uses Quantum Sampling for Asset Trading

Quantum ZeitgeistAugust 3, 20265 min read

Imperial College London & HSBC are exploring Gaussian Boson Sampling, a novel approach to asset clustering within statistical arbitrage portfolios.

HSBC Holdings Plc. is applying a highly experimental form of quantum computing, Gaussian Boson Sampling, to the complex problem of asset clustering within statistical arbitrage portfolios. Researchers at the Blackett Laboratory and Centre for Quantum Engineering, Science and Technology (QuEST) at Imperial College London collaborated with HSBC to map data and benchmark algorithms. Simulations reveal that quantum clustering generates superior alpha during periods of high volatility, effectively isolating structural market idiosyncrasies, and establishing a quantum foundation for broader quantitative finance applications. This application, detailed in recent research, focuses on a specific, high-frequency trading strategy, seeking to…

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