Tag: Monte Carlo Simulation
Sensitivity Analysis quantifies the impact of variable changes on a specific outcome within a model. Employed across various disciplines, it aids in risk assessment, model validation, and decision-making, offering metrics to represent sensitivity.
Utilizing statistical sampling, Monte Carlo Simulation offers insights into risk and uncertainty within predictive models. By generating a spectrum of outcomes from random inputs, it finds applications in fields like finance and engineering. Its precision is contingent on the accuracy of the underlying model and inputs.