Important: Quantum Fira does not provide financial advice. We are a portfolio analysis tool for educational purposes only. Not regulated by the FCA. Read Full Disclaimer

Fira Software Ltd and QuantumFira

Company details, platform purpose and portfolio optimisation approach

Company Information

Company Name

Fira Software Ltd

Registered Office

49 Station Road
Polegate, East Sussex
BN26 6EA
United Kingdom

Contact

info@firasoftware.com
quantumfira.com


Fira Software Ltd is registered in England & Wales. We are not regulated by the Financial Conduct Authority (FCA) and do not provide financial advice. Quantum Fira is a research and analytical platform.

Explore QuantumFira from Fira Software Ltd

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Fira Software Ltd's portfolio research approach

QuantumFira is Fira Software Ltd's portfolio research tool. It compares a quantum algorithm for selecting assets with a classical Markowitz baseline, helping users examine allocation methods and risk metrics.

The asset-selection problem is expressed as a QUBO (quadratic unconstrained binary optimisation). QAOA, the Quantum Approximate Optimisation Algorithm, searches for candidate selections on Amazon Braket's SV1 quantum circuit simulator. A classical optimisation step then assigns portfolio weights.

Read how QAOA portfolio optimisation works, including how it differs from quantum annealing.

How QuantumFira compares allocations

1. Select assets

QAOA evaluates candidate asset selections using a QUBO that combines expected return, covariance and a selection-size penalty.

2. Allocate weights

A classical maximum Sharpe ratio step assigns weights to the selected assets. The quantum circuit does not determine the final weights.

3. Compare methods

Review the allocation alongside a classical Markowitz portfolio. Compare risk metrics and assumptions without treating either result as a forecast.

Research validated on IBM Quantum hardware

Fira Software Ltd's separate portfolio research has run quantum reinforcement learning agents for portfolio rebalancing on IBM Quantum hardware using Qiskit Runtime. This research is distinct from the self-serve optimiser.

QuantumFira's QAOA optimiser, including paid runs, uses Amazon Braket's SV1 simulator. Hardware research does not establish quantum advantage or guarantee improved investment returns.

Explore the IBM Quantum hardware research context

Interpreting portfolio results

Results depend on the selected assets, historical data and modelling assumptions. Compare methods on the same inputs, and review risk as well as expected return. A higher historical Sharpe ratio does not guarantee future performance.

View the quantum portfolio optimisation demo for an illustrative allocation, or explore the quantum portfolio optimiser to examine the tool.

QuantumFira is for education and research. It does not provide financial advice.

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