Forecasting compositional risk allocations
| Authors |
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| Publication date | 01-2019 |
| Journal | Insurance: Mathematics & Economics |
| Volume | Issue number | 84 |
| Pages (from-to) | 79-86 |
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| Abstract | We analyse models for panel data that arise in risk allocation problems, when a given set of sources are the cause of an aggregate risk value. We focus on the modelling and forecasting of proportional contributions to risk over time. Compositional data methods are proposed and the time-series regression is flexible to incorporate external information from other variables. We guarantee that projected proportional contributions add up to 100%, and we introduce a method to generate confidence regions with the same restriction. An illustration is provided for risk capital allocations. |
| Document type | Article |
| Language | English |
| Related dataset | Data for: Forecasting compositional risk allocations |
| Published at | https://doi.org/10.1016/j.insmatheco.2018.10.002 |
| Downloads |
20181008Compositional_dynamic_allocation
(Accepted author manuscript)
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