Quantum Computing Is Forecasting Financial Risk

What this episode covers

Lucas and Luna explore how quantum computers are beginning to model portfolio risk and market scenarios in ways classical systems can't match. They focus on a real 2025 Monte Carlo simulation run by JPMorgan Chase on an IBM superconducting processor—2 million scenarios in under three minutes versus hours on a classical cluster. The episode digs into why path-dependent options, mortgage-backed securities, and systemic tail risks are natural targets for quantum advantage. Lucas explains the math: amplitude amplification and Grover-style search speedup for sampling rare events. Luna asks whether the noise in today's NISQ devices ruins the results, and Lucas walks through error mitigation strategies that made the 2025 run statistically valid. They close on the open question: will fault-tolerant machines arrive before the next financial crisis? #QuantumComputing #FinancialRisk #MonteCarlo #JPMorgan #IBM #PortfolioOptimization #AmplitudeAmplification #GroverAlgorithm #NISQ #ErrorMitigation #DerivativesPricing #TailRisk #Qiskit #Technology #FexingoBusiness #BusinessPodcast #QuantumFinance #RiskModeling Keep every episode free: buymeacoffee.com/fexingo

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