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FirstQFM reports that a quantum reservoir computing system on Rigetti's 108-qubit Cepheus-1-108Q hardware outperformed benchmarks in a single vendor-run pilot, with 52.02% directional accuracy and a 1.22 Sharpe ratio. A 52% hit rate is close to chance, and the results come from company-reported metrics on one 600-date test without independent verification or disclosed statistical significance. Readers should treat this as an early hybrid quantum-AI experiment rather than evidence of a practical quantum advantage in finance.
Surse care acoperăQuantum Zeitgeist, arXiv

Quantum Reservoir Computing forecasts 600 days of market data using FirstQFM’s system

Quantum Zeitgeist8 min de cititArticolul și perspectiva sunt în engleză.

FirstQFM’s system leverages controlled quantum dynamics, a technique called Quantum Reservoir Computing (QRC), on Rigetti’s Cepheus-1-108Q.

FirstQFM’s quantum reservoir computing system achieved top performance in a pilot program with SW7 Group, forecasting market data across 43 assets for a period of 600 out-of-sample dates, the company says. The system ran on Rigetti’s Cepheus-1-108Q, a gate-based superconducting quantum processor, and was evaluated using metrics including accuracy, macro-F1, portfolio PnL and Sharpe ratio. FirstQFM extends standard QRC with a proprietary foundation model trained on the Leonardo supercomputer and fine-tuned on the quantum processor, constructing problem-aware reservoirs adapted to the hardware. The company reports that classical simulation was not used to generate the quantum features or forecasts. FirstQFM’s quantum reservoir computing system achieved 52.02% accuracy in forecasting the direction of 43 anonymized assets, a figure the company reports is the highest observed among evaluated models during a 600-date out-of-sample test. This performance, measured using a regression-to-sign approach, also translated to a macro-F1 score of 0.5176 and a cumulative gross portfolio PnL of 513,473. The annualized Sharpe ratio reached 1.22. FirstQFM…

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