4 résultats pour « scenarioanalysis »

FIRE CLAIM SIZE ESTIMATION USING MATHEMATICAL METHODS: MONTE CARLO SIMULATION & SCENARIO ANALYSIS

This report uses UK fire statistics to model insurance claims for a company next year. It estimates the total sum of claims by modeling both the number and size of fires as random variables from statistical distributions. Monte Carlo simulations in R are used to predict the probability distribution of total claim costs.

Macroprudential policies and climate risks

"Insights from scenario analysis may help inform the use of ‘hard’ macroprudential tools to foster the robustness and resilience of the banking system against climate-induced shocks. Against the backdrop of the ongoing reform of the EU’s macroprudential framework, the paper explores how the macroprudential toolkit could be adjusted to the reality of climate-related financial risks."

Stressing Dynamic Loss Models

"... we propose a reverse stress testing framework for dynamic models. Specifically, we consider a compound Poisson process over a finite time horizon and stresses composed of expected values of functions applied to the process at the terminal time. We then define the stressed model as the probability measure under which the process satisfies the constraints and which minimizes the KullbackLeibler divergence to the reference compound Poisson model."

Catastrophic Uncertainty and Regulatory Impact Analysis

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"Cost-benefit analysis embodies techniques for the analysis of possible harmful outcomes when the probability of those outcomes can be quantified with reasonable confidence. But when those probabilities cannot be quantified (“deep uncertainty”), the analytic path is more difficult. The problem is especially acute when potentially catastrophic outcomes are involved, because ignoring or marginalizing them could seriously skewing the analysis. Yet the likelihood of catastrophe is often difficult or impossible to quantify because such events may be unprecedented (runaway AI or tipping points for climate change) or extremely rare (global pandemics caused by novel viruses in the modern world). OMB’s current guidance to agencies on unquantifiable risks is now almost twenty years old and in serious need of updating. It correctly points to scenario analysis as an important tool but it fails to give guidance on the development of scenarios."