HSBC and IBM achieve 34% trading advantage with quantum computing

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🚀 Quantum Finance in Action: HSBC validates what we explored in Qubit-Lab Big news this week: HSBC and IBM reported the world’s first real trading advantage using quantum computing — applying quantum feature maps on IBM’s Heron processor to bond market data. The result: a 34 % improvement in predicting whether trades would be executed at quoted prices. What struck me: this is exactly the approach I recently demonstrated in my Qubit-Lab video on Quantum Machine Learning — encoding classical data into Hilbert space with a quantum circuit, then training a classical model on those enriched features. HSBC’s experiment shows: 🌐 Hybrid QML (quantum + classical) is already delivering measurable value. ⚡ Noise isn’t just a limitation — in this case, it even improved results by diversifying features. 📈 Finance is moving from “quantum theory” to empirical advantage. For me, it’s encouraging to see a global bank validate the same ideas we explore here on Qubit-Lab: quantum computing isn’t just academic anymore — it’s becoming a business reality. 👉 If you want to understand the method behind the headlines, check out my Qubit-Lab video on QML — the principles are the same, just scaled up to 150 qubits on IBM Heron. Here the link to the QML video #9 with Python Notebook: http://qubit-lab.ch/9 #QuantumComputing #Finance #QML #QubitLab #IBMQuantum #HSBC

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