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Risks, Volume 2, Issue 1 (March 2014), Pages 1-88

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Editorial

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Open AccessEditorial Publishing Risks
Risks 2014, 2(1), 1-2; doi:10.3390/risks2010001
Received: 17 February 2014 / Accepted: 17 February 2014 / Published: 21 February 2014
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Abstract
“What is complicated is not necessarily insightful and what is insightful is not necessarily complicated: Risks welcomes simple manuscripts that contribute with insight, outlook, understanding and overview”—a quote from the first editorial of this journal [1]. Good articles are
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“What is complicated is not necessarily insightful and what is insightful is not necessarily complicated: Risks welcomes simple manuscripts that contribute with insight, outlook, understanding and overview”—a quote from the first editorial of this journal [1]. Good articles are not characterized by their level of complication but by their level of imagination, innovation, and power of penetration. Creativity sessions and innovative tasks are most elegant and powerful when they are delicately simple. This is why the articles you most remember are not the complicated ones that you struggled to digest, but the simpler ones you enjoyed swallowing. [...] Full article

Research

Jump to: Editorial

Open AccessArticle Catastrophe Insurance Modeled by Shot-Noise Processes
Risks 2014, 2(1), 3-24; doi:10.3390/risks2010003
Received: 6 November 2013 / Revised: 28 January 2014 / Accepted: 29 January 2014 / Published: 21 February 2014
Cited by 2 | PDF Full-text (343 KB) | HTML Full-text | XML Full-text
Abstract
Shot-noise processes generalize compound Poisson processes in the following way: a jump (the shot) is followed by a decline (noise). This constitutes a useful model for insurance claims in many circumstances; claims due to natural disasters or self-exciting processes exhibit similar features. We
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Shot-noise processes generalize compound Poisson processes in the following way: a jump (the shot) is followed by a decline (noise). This constitutes a useful model for insurance claims in many circumstances; claims due to natural disasters or self-exciting processes exhibit similar features. We give a general account of shot-noise processes with time-inhomogeneous drivers inspired by recent results in credit risk. Moreover, we derive a number of useful results for modeling and pricing with shot-noise processes. Besides this, we obtain some highly tractable examples and constitute a useful modeling tool for dynamic claims processes. The results can in particular be used for pricing Catastrophe Bonds (CAT bonds), a traded risk-linked security. Additionally, current results regarding the estimation of shot-noise processes are reviewed. Full article
(This article belongs to the Special Issue Application of Stochastic Processes in Insurance)
Open AccessArticle An Academic Response to Basel 3.5
Risks 2014, 2(1), 25-48; doi:10.3390/risks2010025
Received: 25 November 2013 / Revised: 9 February 2014 / Accepted: 17 February 2014 / Published: 27 February 2014
Cited by 33 | PDF Full-text (375 KB) | HTML Full-text | XML Full-text
Abstract
Recent crises in the financial industry have shown weaknesses in the modeling of Risk-Weighted Assets (RWAs). Relatively minor model changes may lead to substantial changes in the RWA numbers. Similar problems are encountered in the Value-at-Risk (VaR)-aggregation of risks. In this article, we
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Recent crises in the financial industry have shown weaknesses in the modeling of Risk-Weighted Assets (RWAs). Relatively minor model changes may lead to substantial changes in the RWA numbers. Similar problems are encountered in the Value-at-Risk (VaR)-aggregation of risks. In this article, we highlight some of the underlying issues, both methodologically, as well as through examples. In particular, we frame this discussion in the context of two recent regulatory documents we refer to as Basel 3.5. Full article
(This article belongs to the Special Issue Risk Management Techniques for Catastrophic and Heavy-Tailed Risks)
Open AccessArticle Modeling and Performance of Bonus-Malus Systems: Stationarity versus Age-Correction
Risks 2014, 2(1), 49-73; doi:10.3390/risks2010049
Received: 30 September 2013 / Revised: 17 February 2014 / Accepted: 18 February 2014 / Published: 11 March 2014
Cited by 2 | PDF Full-text (460 KB) | HTML Full-text | XML Full-text
Abstract
In a bonus-malus system in car insurance, the bonus class of a customer is updated from one year to the next as a function of the current class and the number of claims in the year (assumed Poisson). Thus the sequence of classes
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In a bonus-malus system in car insurance, the bonus class of a customer is updated from one year to the next as a function of the current class and the number of claims in the year (assumed Poisson). Thus the sequence of classes of a customer in consecutive years forms a Markov chain, and most of the literature measures performance of the system in terms of the stationary characteristics of this Markov chain. However, the rate of convergence to stationarity may be slow in comparison to the typical sojourn time of a customer in the portfolio. We suggest an age-correction to the stationary distribution and present an extensive numerical study of its effects. An important feature of the modeling is a Bayesian view, where the Poisson rate according to which claims are generated for a customer is the outcome of a random variable specific to the customer. Full article
(This article belongs to the Special Issue Application of Stochastic Processes in Insurance)
Open AccessArticle Modeling Cycle Dependence in Credit Insurance
Risks 2014, 2(1), 74-88; doi:10.3390/risks2010074
Received: 31 December 2013 / Revised: 12 February 2014 / Accepted: 20 February 2014 / Published: 14 March 2014
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Abstract
Business and credit cycles have an impact on credit insurance, as they do on other businesses. Nevertheless, in credit insurance, the impact of the systemic risk is even more important and can lead to major losses during a crisis. Because of this, the
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Business and credit cycles have an impact on credit insurance, as they do on other businesses. Nevertheless, in credit insurance, the impact of the systemic risk is even more important and can lead to major losses during a crisis. Because of this, the insurer surveils and manages policies almost continuously. The management actions it takes limit the consequences of a downturning cycle. However, the traditional modeling of economic capital does not take into account this important feature of credit insurance. This paper proposes a model aiming to estimate future losses of a credit insurance portfolio, while taking into account the insurer’s management actions. The model considers the capacity of the credit insurer to take on less risk in the case of a cycle downturn, but also the inverse, in the case of a cycle upturn; so, losses are predicted with a more dynamic perspective. According to our results, the economic capital is over-estimated when not considering the management actions of the insurer. Full article

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