Risk Minimization for Insurance Products via F-Doubly Stochastic Markov Chains
Department of Mathematics, University of Munich, Theresienstraße 39, 80333 Munich, Germany
Department of Mathematics, University of Oslo, Boks 1072 Blindern, Norway
Department of Statistics, University of Munich, Akademiestr.1, 80799 Munich, Germany
BMW Financial Services, BMW Bank GmbH, 80787 Munich, Germany
Author to whom correspondence should be addressed.
Academic Editor: Mogens Steffensen
Received: 21 March 2016 / Revised: 27 May 2016 / Accepted: 27 June 2016 / Published: 7 July 2016
We study risk-minimization for a large class of insurance contracts. Given that the individual progress in time of visiting an insurance policy’s states follows an
-doubly stochastic Markov chain, we describe different state-dependent types of insurance benefits. These cover single payments at maturity, annuity-type payments and payments at the time of a transition. Based on the intensity of the
-doubly stochastic Markov chain, we provide the Galtchouk-Kunita-Watanabe decomposition for a general insurance contract and specify risk-minimizing strategies in a Brownian financial market setting. The results are further illustrated explicitly within an affine structure for the intensity.
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MDPI and ACS Style
Biagini, F.; Groll, A.; Widenmann, J. Risk Minimization for Insurance Products via F-Doubly Stochastic Markov Chains. Risks 2016, 4, 23.
Biagini F, Groll A, Widenmann J. Risk Minimization for Insurance Products via F-Doubly Stochastic Markov Chains. Risks. 2016; 4(3):23.
Biagini, Francesca; Groll, Andreas; Widenmann, Jan. 2016. "Risk Minimization for Insurance Products via F-Doubly Stochastic Markov Chains." Risks 4, no. 3: 23.
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