Auto-balanced common shock claim models
Greg Taylor, Phuong Anh Vu

TL;DR
This paper introduces 'auto-balanced' common shock claim models ensuring proportional contributions of shocks and idiosyncratic components across observations, with simple conditions for auto-balance and numerical demonstrations.
Contribution
It proposes a new class of auto-balanced models that maintain constant proportional contributions, addressing unbalanced issues in traditional shock models.
Findings
Conditions for auto-balance are simple and widely applicable.
Numerical illustrations demonstrate the effectiveness of the proposed models.
Addresses over- and under-contribution issues in claim triangle models.
Abstract
The paper is concerned with common shock models of claim triangles. These are usually constructed as a linear combinations of shock components and idiosyncratic components. Previous literature has discussed the unbalanced property of such models, whereby the shocks may over- or under-contribute to some observations. The literature has also introduced corrections for this. The present paper discusses 'auto-balanced' models, in which all shock and idiosyncratic components contribute to observations such that their proportionate contributions are constant from one observation to another. The conditions for auto-balance are found to be simple and applicable to a wide range of model structures. Numerical illustrations are given.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsProbability and Risk Models · Statistical Distribution Estimation and Applications
