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...
Main Authors: | Nataliya Chukhrova, Arne Johannssen |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-06-01
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Series: | Risks |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-9091/9/6/112 |
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