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We derive a general multiple state model for critical illness insurances. In contrast to the classical model, we take into account that the probability of death for a dread disease sufferer may depend on the duration of the disease, and the…

Applications · Statistics 2016-03-01 Joanna Dȩbicka , Beata Zmyślona

Convergence of order $O(1/\sqrt{n})$ is obtained for the distance in total variation between the Poisson distribution and the distribution of the number of fixed size cycles in generalized random graphs with random vertex weights. The…

Probability · Mathematics 2024-05-31 Sergey G. Bobkov , Maria A. Danshina , Vladimir V. Ulyanov

Analysing dependent risks is an important task for insurance companies. A dependency is reflected in the fact that information about one random variable provides information about the likely distribution of values of another random…

Applications · Statistics 2021-03-22 Sen Hu , Adrian O'Hagan

We provide a new algorithm for solving Risk Sensitive Partially Observable Markov Decisions Processes, when the risk is modeled by a utility function, and both the state space and the space of observations is finite. This algorithm is based…

Optimization and Control · Mathematics 2022-07-19 Arsham Afsardeir , Andreas Kapetanis , Vaios Laschos , Klaus Obermayer

Motivated by disease progression-related studies, we propose an estimation method for fitting general non-homogeneous multi-state Markov models. The proposal can handle many types of multi-state processes, with several states and various…

Methodology · Statistics 2024-07-22 Alessia Eletti , Giampiero Marra , Rosalba Radice

Computing the probability of evidence even with known error bounds is NP-hard. In this paper we address this hard problem by settling on an easier problem. We propose an approximation which provides high confidence lower bounds on…

Artificial Intelligence · Computer Science 2012-06-26 Vibhav Gogate , Bozhena Bidyuk , Rina Dechter

This paper explores an optimal investment and reinsurance problem involving both ordinary and catastrophe insurance businesses. The catastrophic events are modeled as following a compound Poisson process, impacting the ordinary insurance…

Optimization and Control · Mathematics 2023-11-01 Bohan Li , Junyi Guo , Xiaoqing Liang

We describe a Markov-Chain-Monte-Carlo algorithm which can be used to generate naturally labeled n-element posets at random with a probability distribution of one's choice. Implementing this algorithm for the uniform distribution, we…

Combinatorics · Mathematics 2015-04-23 Joe Henson , David P. Rideout , Rafael D. Sorkin , Sumati Surya

This work is entirely devoted to compare the largest claims from two heterogeneous portfolios. It is assumed that the claim amounts in an insurance portfolio are nonnegative absolutely continuous random variables and belong to a general…

Risk Management · Quantitative Finance 2021-04-20 Sangita Das , Suchandan Kayal

We study optimal proportional reinsurance and investment strategies for an insurance company which experiences both ordinary and catastrophic claims and wishes to maximize the expected exponential utility of its terminal wealth. We propose…

Portfolio Management · Quantitative Finance 2021-05-18 Claudia Ceci , Katia Colaneri , Alessandra Cretarola

We propose a penalized pseudo-likelihood criterion to estimate the graph of conditional dependencies in a discrete Markov random field that can be partially observed. We prove the convergence of the estimator in the case of a finite or…

Methodology · Statistics 2022-09-05 Florencia Leonardi , Rodrigo R. S. Carvalho

In this manuscript we propose a method for pricing insurance products that cover not only traditional risks, but also unforeseen ones. By considering the Poisson process parameter to be a mixed random variable, we capture the heterogeneity…

General Finance · Quantitative Finance 2020-08-10 Weihong Ni , Corina Constantinescu , Alfredo Egídio dos Reis , Véronique Maume-Deschamps

Data on count processes arise in a variety of applications, including longitudinal, spatial and imaging studies measuring count responses. The literature on statistical models for dependent count data is dominated by models built from…

Methodology · Statistics 2013-10-08 Antonio Canale , David B. Dunson

In a dual risk model, the premiums are considered as the costs and the claims are regarded as the profits. The surplus can be interpreted as the wealth of a venture capital, whose profits depend on research and development. In most of the…

Risk Management · Quantitative Finance 2024-12-02 Lingjiong Zhu

In this paper, we present a probabilistic adaptation of an Assume/Guarantee contract formalism. For the sake of generality, we assume that the extended state machines used in the contracts and implementations define sets of runs on a given…

Performance · Computer Science 2009-04-20 Benoît Delahaye , Benoît Caillaud

Recently, a marked Poisson process (MPP) model for life catastrophe risk was proposed in [6]. We provide a justification and further support for the model by considering more general Poisson point processes in the context of extreme value…

Risk Management · Quantitative Finance 2013-11-01 Matias Leppisaari

Accurate modelling of the joint extremal dependence structure within a stationary time series is a challenging problem that is important in many applications.\ Several previous approaches to this problem are only applicable to certain types…

Methodology · Statistics 2023-03-09 Graeme Auld , Ioannis Papastathopoulos

The paper introduces an approach to telematics devices data application in automotive insurance. We conduct a comparative analysis of different types of devices that collect information on vehicle utilization and driving style of its…

Applications · Statistics 2019-10-07 Konstantin Korishchenko , Ivan Stankevich , Nikolay Pilnik , Daria Petrova

We are studying long term sequence prediction (forecasting). We approach this by investigating criteria for choosing a compact useful state representation. The state is supposed to summarize useful information from the history. We want a…

Machine Learning · Computer Science 2012-02-10 Peter Sunehag , Marcus Hutter

We study the optimal excess-of-loss reinsurance problem when both the intensity of the claims arrival process and the claim size distribution are influenced by an exogenous stochastic factor. We assume that the insurer's surplus is governed…

Mathematical Finance · Quantitative Finance 2019-04-12 Matteo Brachetta , Claudia Ceci
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