Applied Quantum for Finance

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Sigma Quantum Lab develops and runs quantum and hybrid algorithms on current-generation hardware to address concrete asset-management problems: portfolio optimization, derivatives pricing and risk sensitivities, risk modelling, and scenario generation.

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Objective: Applied quantum, measurable results

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Active research streams

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• Portfolio Optimisation – QAOA, quantum annealing and variational methods on several variable problems.

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• Derivatives Pricing  – Amplitude-estimation and related techniques for option pricing and sensitivities.

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• Risk & Scenario Analysis – Quantum-enhanced Monte Carlo and quantum-inspired generative models for stress and scenario engines.

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• Quantum Machine Learning (QML) – Macro-regime detection and signal processing using quantum and hybrid ML approaches.