FirstQFM Demonstrates Quantum Reservoir Computing on Rigetti’s 108-Qubit Processor to Outperform Classical Financial Benchmarks
AI-summarised brief · reviewed before publication
Stockholm-based quantum software firm FirstQFM, together with London research house SW7 Group and Rigetti Computing, demonstrated a financial forecasting pilot using quantum reservoir computing (QRC) on Rigetti’s 108‑qubit Cepheus‑1 processor. In a blinded out‑of‑sample test covering 43 anonymized assets over 600 trading days, the hybrid QRC pipeline surpassed standard machine learning and classical time‑series models in directional accuracy, macro‑F1, cumulative gross profit, and risk‑adjusted Sharpe ratios. The system leveraged 61‑84 physical qubits to generate hardware‑stabilized reservoir embeddings, achieving 2.12× the gross P&L of the best classical baseline and a Sharpe ratio of 1.22 on an equally weighted portfolio.
💡 Why It Matters
- · The results show that a latency‑efficient quantum approach can outperform classical models on real market data, suggesting a practical pathway for near‑term quantum advantage in finance.
