Reverse sensitivity testing: What does it take to break the model?
Reverse sensitivity testing: What does it take to break the model? is a scholarly work, published in 2019 in ''European Journal of Operational Research''. The main subjects of the publication include measure, divergence, portfolio, regularization, econometrics, expected shortfall, probability distribution, Monte Carlo method, computer science, uncertainty quantification, mathematical optimization, biological function, robust optimization, risk measure, mathematics, sensitivity, random variable, and stress testing. The authors argue that a substantial change in the distribution of an input factor corresponds to high sensitivity to that input and introduce a novel sensitivity measure to formalise this insight.