Jpmorgan Chase Paper Investigates Quantum Deep Hedging

JPMorgan Chase and QC Ware recently released a paper examining how deep hedging, a data-driven model used to reduce risk for a portfolio, could be improved with quantum computing. The study found that deep hedging on classical frameworks using quantum deep learning enabled models to be trained more efficiently and demonstrated the potential for future computational speed-ups. Additionally, the quantum application could offer improvements for deep hedging in both classical and quantum environments. The results achieved with JPMorgan Chase demonstrate the potential and applicability of quantum machine learning.