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Volume 1, September
 
 

Risks, Volume 1, Issue 1 (June 2013) – 4 articles , Pages 1-44

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102 KiB  
Editorial
Surrounding Risks
by Mogens Steffensen
Risks 2013, 1(1), 43-44; https://doi.org/10.3390/risks1010043 - 30 May 2013
Cited by 2 | Viewed by 4757
Abstract
Research in insurance and finance was always intersecting although they were originally and generally viewed as separate disciplines. Insurance is about transferring risks between parties such that the burdens of risks are borne by those who can. This makes insurance transactions a beneficial [...] Read more.
Research in insurance and finance was always intersecting although they were originally and generally viewed as separate disciplines. Insurance is about transferring risks between parties such that the burdens of risks are borne by those who can. This makes insurance transactions a beneficial activity for the society. It calls on detection, modelling, valuation, and controlling of risks. One of the main sources of control is diversification of risks and in that respect it becomes an issue in itself to clarify diversifiability of risks. However, many diversifiable risks are not, by nature or by contract design, separable from non-diversifiable risks that are, on the other hand, sometimes traded in financial markets and sometimes not. A key observation is that the economic risk came before the insurance contract: Mother earth destroys and kills incidentally and mercilessly, but the uncertainty of economic consequences can be more or less cleverly distributed by the introduction of an insurance market. [...] Full article
175 KiB  
Article
Understanding the “Black Box” of Employer Decisions about Health Insurance Benefits: The Case of Depression Products
by Kathryn Rost, Airia Papadopoulos, Su Wang and Donna Marshall
Risks 2013, 1(1), 34-42; https://doi.org/10.3390/risks1010034 - 29 May 2013
Cited by 2 | Viewed by 5179
Abstract
In a randomized trial of two interventions on employer health benefit decision-making, 156 employers in the evidence-based (EB) condition attended a two hour presentation reviewing scientific evidence demonstrating depression products that increase high quality treatment of depression in the workforce provide the employer [...] Read more.
In a randomized trial of two interventions on employer health benefit decision-making, 156 employers in the evidence-based (EB) condition attended a two hour presentation reviewing scientific evidence demonstrating depression products that increase high quality treatment of depression in the workforce provide the employer a return on investment. One-hundred sixty-nine employers participating in the usual care (UC) condition attended a similar length presentation reviewing scientific evidence supporting healthcare effectiveness data and information set (HEDIS) monitoring. This study described the decision-making process in 264 (81.2%) employers completing 12 month follow-up. The EB intervention did not increase the proportion of employers who discussed depression products with others in the company (29.2% versus 32.1%, p > 0.10), but it did significantly influence the content of the discussions that occurred. Discussion in EB companies promoted the capacity of a depression product to realize a return on investment (18.4% versus 4.7%, p = 0.05) and to improve productivity (47.4% versus 25.6%, p = 0.06) more often than discussions in UC companies. Almost half of EB and UC employers reported that return on investment has a large impact on health benefit decision-making. These results demonstrate the difficulty of influencing employer decisions about health benefits using group presentations. Full article
278 KiB  
Article
Evaluating Risk Measures and Capital Allocations Based on Multi-Losses Driven by a Heavy-Tailed Background Risk: The Multivariate Pareto-II Model
by Alexandru V. Asimit, Raluca Vernic and Riċardas Zitikis
Risks 2013, 1(1), 14-33; https://doi.org/10.3390/risks1010014 - 5 Mar 2013
Cited by 29 | Viewed by 5890
Abstract
Evaluating risk measures, premiums, and capital allocation based on dependent multi-losses is a notoriously difficult task. In this paper, we demonstrate how this can be successfully accomplished when losses follow the multivariate Pareto distribution of the second kind, which is an attractive model [...] Read more.
Evaluating risk measures, premiums, and capital allocation based on dependent multi-losses is a notoriously difficult task. In this paper, we demonstrate how this can be successfully accomplished when losses follow the multivariate Pareto distribution of the second kind, which is an attractive model for multi-losses whose dependence and tail heaviness are influenced by a heavy-tailed background risk. A particular attention is given to the distortion and weighted risk measures and allocations, as well as their special cases such as the conditional layer expectation, tail value at risk, and the truncated tail value at risk. We derive formulas that are either of closed form or follow well-defined recursive procedures. In either case, their computational use is straightforward. Full article
269 KiB  
Article
Early Warning to Insolvency in the Pension Fund: The French Case
by Noël Bonneuil
Risks 2013, 1(1), 1-13; https://doi.org/10.3390/risks1010001 - 18 Jan 2013
Cited by 2 | Viewed by 4792
Abstract
The financial equilibrium of pension funds relies on the appropriate computation of retirement benefits, taking account of future payments and discount rates. Short-term errors in the commitment for retirement benefits, ill-suited investment in the stock market, or improper mixture with pay-as-you-go payments have [...] Read more.
The financial equilibrium of pension funds relies on the appropriate computation of retirement benefits, taking account of future payments and discount rates. Short-term errors in the commitment for retirement benefits, ill-suited investment in the stock market, or improper mixture with pay-as-you-go payments have long-term consequences and may lead the pension fund to insolvency. The differential equation governing the current assets shows the respective weights associated with the error on the interest rate, the error on the extra bonus, and the error made in forecasting mortality. These weights are estimated through simulations. A short follow-up is sufficient to estimate the three errors. A threshold for the extra interest rate to be earned on the financial market is given to counter-balance the extra bonus when mortality is forecast correctly. Full article
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