Quantum Monte Carlo simulations for financial risk analytics: scenario generation for equity, rate, and credit risk factors

Understand

Monte Carlo (MC) simulations are widely used in financial risk management, from estimating value-at-risk (VaR) to pricing over-the-counter derivatives.

• However, they come at a significant computational cost due to the number of scenarios required for convergence.
• If a probability distribution is available, Quantum Amplitude Estimation (QAE) algorithms can provide a quadratic speed-up in measuring its properties as compared to their classical counterparts.
• Recent studies have explored the calculation of common risk measures and the optimisation of QAE algorithms by initialising the input quantum states with pre-computed probability distributions.