3 résultats pour « riskanalysis »
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.
"We propose here an analysis of the database of the cyber complaints filed at the Gendarmerie Nationale.We perform this analysis with a new algorithm developed for non-negative asymmetric heavy-tailed data, which could become a handy tool in applied fields. This method gives a good estimation of the full distribution including the tail. Our study confirms the finiteness of the loss expectation, necessary condition for insurability."
"I argue that that conventional risk analysis—meaning risk analysis fixated on controlling risks—should expand to systematically integrate two related principles. The first is prevention, which seeks in the first instance to avoid the risk altogether. The second is resilience, which aims build the capacity to respond to whatever does come to pass."