Nos derniers articles

The paper argues that Shapley allocation is the most suitable risk allocation method for financial institutions, balancing theoretical properties, accuracy, and practicality. It overcomes perceived computational intractability by replacing the exponential analytical approach with an efficient Monte Carlo algorithm that scales linearly and becomes preferable for ≥10-14 units. The study proposes solutions for negative allocations, a consistent multi-level hierarchical framework (PTD, CTD, BU approaches), and demonstrates applicability to large trading portfolios under Basel 2.5 and FRTB regimes, showing Shapley better captures diversification and hedging effects compared to simpler methods.

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.

The paper proposes a novel approach using Monte Carlo Simulation to quantitatively prioritize project risks based on their impact on project duration and cost, addressing limitations of traditional risk matrices and enabling project managers to differentiate critical risks according to their specific impact on time or cost objectives.