Encode stock selection as a QUBO, solve it with the Quantum Approximate Optimisation Algorithm (QAOA) on Amazon Braket's SV1 quantum circuit simulator, and compare every result with a classical Markowitz mean-variance portfolio.
Understand this sample: learn about the Sharpe ratio and portfolio risk metrics, or explore how QAOA portfolio optimisation works.
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A quick guide to the method, who operates the platform and how to try it safely.
Quantum portfolio optimisation writes the choice of which assets to hold as a QUBO (quadratic unconstrained binary optimisation) problem and searches it with a quantum algorithm such as QAOA, or with quantum annealing. QuantumFira shows each quantum result beside a classical mean-variance portfolio.
QuantumFira encodes asset selection as a QUBO, samples it with QAOA on Amazon Braket's SV1 quantum circuit simulator, allocates weights classically within the best selections and reports the result beside a classical Markowitz baseline. Read how QAOA portfolio optimisation works.
Yes. Fira Software's quantum portfolio research has run portfolio circuits on IBM Quantum hardware through Qiskit Runtime, on ibm_fez, a 156-qubit IBM Heron r2 processor, and compared them with the same circuits on a simulator. The self-serve optimiser runs QAOA on Amazon Braket's SV1 simulator for fast, repeatable results. How portfolio circuits run on IBM Quantum hardware.
QuantumFira is a web platform from Fira Software Ltd for portfolio optimisation using QAOA quantum methods, risk analytics and comparison with classical allocation results.
You can start free, inspect sample optimisation results, review pricing and run a small portfolio before choosing a paid quantum optimisation.
No. QuantumFira is a research and analytical platform. It helps compare portfolio optimisation outputs, but investment decisions remain your responsibility.
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