Kalman Filter Learning Algorithms and State Space Representations for Stochastic Claims Reserving

Kalman Filter Learning Algorithms and State Space Representations for Stochastic Claims Reserving

In stochastic claims reserving, state space models have been used for almost 40 years to forecast loss reserves and to compute their mean squared error of prediction. Although state space models and the associated Kalman filter learning algorithms are very powerful and flexible tools, comparatively...

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Bibliographic Details
Main Authors: Nataliya Chukhrova, Arne Johannssen
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Risks
Subjects:
adaptive learning
dependence modeling
evolutionary models
insurance
Kalman filter
machine learning
Online Access:https://www.mdpi.com/2227-9091/9/6/112

Internet

https://www.mdpi.com/2227-9091/9/6/112

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