<scp>K</scp>alman Filter

Barnett, Glen; Zehnwirth, Ben

doi:10.1002/9780470012505.tak001

Cited by 2 publications

(2 citation statements)

References 28 publications

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“…2. ABC is the run-off triangle of a workers' compensation portfolio of a large company, see [9], including an in-depth analysis of the data array. We emphasise that the statistical analysis of these triangles is not in scope of the dissertation.…”

Section: Data and Simulation Of Scenariosmentioning

confidence: 99%

Experience rating and stochastic reserving in general insurance

Martinek¹

2019

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I thank so much my mother Edit for her love, encouragement, support and patience over the years. She has dedicated so much energy and time to me to ensure I can study and do research at the university. I also thank my father Péter for his support, as well as my brother Péter for constantly inquiring about the progress of my PhD. My grandparents, Edit and Sándor also deserve my gratitude, and especially Kati mama, who would arguably be the happiest to see this dissertation.Finally, I am tremendously grateful to Évi for all that she has done to help me complete papers and this dissertation. Her support is not limited to loving patience, but also meant active review of all my draft articles. I have written this dissertation in Amsterdam, Budapest and Tokyo -she has been present in all these locations and has facilitated the progress, not only by uplifting words, linguistic and numeric advice, but also by complaining relatively little about me working until 2 in the morning. I dedicate this work to her. CRun-off triangles .

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Section: Data and Simulation Of Scenariosmentioning

confidence: 99%

Experience rating and stochastic reserving in general insurance

Martinek¹

2019

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“…The chain-ladder algorithm to compute the unpaid claim requirement in an insurance financial statement is the most well-known reservation methodology in actuarial practice. This algorithm has been widely examined by many researchers in the last three decades, such as Kremer (1982), Taylor (1986Taylor ( , 2000, Renshaw (1989), Verrall (1990), Mack (1993), Murphy (1994), Schmidt & Schnaus (1996), Barnett & Zehnwirth (1998), England & Verrall (1999) and .…”

Section: Introductionmentioning

confidence: 99%

Unbiased estimator for the ultimate claim prediction error in the chain-ladder model of Mack

Siegenthaler

2022

Ann. actuar. sci.

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We propose a new estimator for the ultimate prediction uncertainty within the famous Mack’s distribution-free chain-ladder model, which can be proved to be unbiased (conditionally given the first triangle column) under some additional technical assumptions. A peculiar behaviour of the unbiased estimator is given by its possible negativity. This is a drawback which might be worth trading off for the unbiasedness property, since there is empirical evidence that the likelihood of a negative realisation is extremely low. This offers an alternative to the well-known Mack and BBMW formulas since the latters can be proved to be biased. However, we also show that this novel estimator, as well as the Mack and BBMW formulas, can (with non-negligible probability) materially fail to estimate the true uncertainty.

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Kalman Filter

Cited by 2 publications

References 28 publications

Experience rating and stochastic reserving in general insurance

Experience rating and stochastic reserving in general insurance

Unbiased estimator for the ultimate claim prediction error in the chain-ladder model of Mack

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