Next Issue
Volume 3, June
Previous Issue
Volume 2, December
 
 

Risks, Volume 3, Issue 1 (March 2015) – 6 articles , Pages 1-102

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Select all
Export citation of selected articles as:
330 KiB  
Article
Portability, Salary and Asset Price Risk: A Continuous-Time Expected Utility Comparison of DB and DC Pension Plans
by An Chen and Filip Uzelac
Risks 2015, 3(1), 77-102; https://doi.org/10.3390/risks3010077 - 13 Mar 2015
Cited by 3 | Viewed by 5746
Abstract
This paper compares two different types of private retirement plans from the perspective of a representative beneficiary: a defined benefit (DB) and a defined contribution (DC) plan. While salary risk is the main common risk factor in DB and DC pension plans, one [...] Read more.
This paper compares two different types of private retirement plans from the perspective of a representative beneficiary: a defined benefit (DB) and a defined contribution (DC) plan. While salary risk is the main common risk factor in DB and DC pension plans, one of the key differences is that DB plans carry portability risks, whereas DC plans bear asset price risk. We model these tradeoffs explicitly in this paper and compare these two plans in a utility-based framework. Our numerical analysis focuses on answering the question of when the beneficiary is indifferent between the DB and DC plan. Most of our results confirm the findings in the existing literature, among which, e.g., portability losses considerably reduce the relative attractiveness of the DB plan. However, we also find that the attractiveness of the DB plan can decrease in the level of risk aversion, which is inconsistent with the existing literature. Full article
(This article belongs to the Special Issue Life Insurance and Pensions)
Show Figures

Figure 1

669 KiB  
Article
Double Crowding-Out Effects of Means-Tested Public Provision for Long-Term Care
by Christophe Courbage and Peter Zweifel
Risks 2015, 3(1), 61-76; https://doi.org/10.3390/risks3010061 - 25 Feb 2015
Cited by 2 | Viewed by 5128
Abstract
Publicly provided long-term care (LTC) insurance with means-tested benefits is suspected to crowd out either private saving or informal care. This contribution predicts crowding-out effects for both private saving and informal care for policy measures designed to relieve the public purse from LTC [...] Read more.
Publicly provided long-term care (LTC) insurance with means-tested benefits is suspected to crowd out either private saving or informal care. This contribution predicts crowding-out effects for both private saving and informal care for policy measures designed to relieve the public purse from LTC expenditure such as more stringent means testing and increased taxation of inheritance. These effects result from the interaction of a parent who decides on the amount of saving in retirement and a caregiver who decides on the effort devoted to informal care which lowers the probability of admission to a nursing home. Double crowding-out effects are also found to be the consequence of exogenous influences, notably a higher opportunity cost of caregiving. Full article
(This article belongs to the Special Issue Information and market efficiency)
1325 KiB  
Article
Safety Margins for Systematic Biometric and Financial Risk in a Semi-Markov Life Insurance Framework
by Andreas Niemeyer
Risks 2015, 3(1), 35-60; https://doi.org/10.3390/risks3010035 - 19 Jan 2015
Cited by 3 | Viewed by 5235
Abstract
Insurance companies use conservative first order valuation bases to calculate insurance premiums and reserves. These valuation bases have a significant impact on the insurer’s solvency and on the premiums of the insurance products. Safety margins for systematic biometric and financial risk are in [...] Read more.
Insurance companies use conservative first order valuation bases to calculate insurance premiums and reserves. These valuation bases have a significant impact on the insurer’s solvency and on the premiums of the insurance products. Safety margins for systematic biometric and financial risk are in practice typically chosen as time-constant percentages on top of the best estimate transition intensities. We develop a risk-oriented method for the allocation of a total safety margin to the single safety margins at each point in time and each state. In a case study, we demonstrate the suitability of the proposed method in different frameworks. The results show that the traditional method yields an unwanted variability of the safety level with respect to time, whereas the variability can be significantly reduced by the new method. Furthermore, the case study supports the German 60 percent rule for the technical interest rate. Full article
(This article belongs to the Special Issue Life Insurance and Pensions)
Show Figures

Figure 1

173 KiB  
Article
Paradox-Proof Utility Functions for Heavy-Tailed Payoffs: Two Instructive Two-Envelope Problems
by Michael R. Powers
Risks 2015, 3(1), 26-34; https://doi.org/10.3390/risks3010026 - 19 Jan 2015
Cited by 1 | Viewed by 4701
Abstract
We identify restrictions on a decision maker’s utility function that are both necessary and sufficient to preserve dominance reasoning in each of two versions of the Two-Envelope Paradox (TEP). For the classical TEP, the utility function must satisfy a certain recurrence inequality. For [...] Read more.
We identify restrictions on a decision maker’s utility function that are both necessary and sufficient to preserve dominance reasoning in each of two versions of the Two-Envelope Paradox (TEP). For the classical TEP, the utility function must satisfy a certain recurrence inequality. For the St. Petersburg TEP, the utility function must be bounded above asymptotically by a power function, which can be tightened to a constant. By determining the weakest conditions for dominance reasoning to hold, the article settles an open question in the research literature. Remarkably, neither constant-bounded utility nor finite expected utility is necessary for resolving the classical TEP; instead, finite expected utility is both necessary and sufficient for resolving the St. Petersburg TEP. Full article
40 KiB  
Editorial
Acknowledgement to Reviewers of Risks in 2014
by Risks Editorial Office
Risks 2015, 3(1), 24-25; https://doi.org/10.3390/risks3010024 - 8 Jan 2015
Viewed by 4088
Abstract
The editors of Risks would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2014:[...] Full article
305 KiB  
Article
Inhomogeneous Long-Range Percolation for Real-Life Network Modeling
by Philippe Deprez, Rajat Subhra Hazra and Mario V. Wüthrich
Risks 2015, 3(1), 1-23; https://doi.org/10.3390/risks3010001 - 6 Jan 2015
Cited by 26 | Viewed by 5536
Abstract
The study of random graphs has become very popular for real-life network modeling, such as social networks or financial networks. Inhomogeneous long-range percolation (or scale-free percolation) on the lattice Zd, d ≥ 1, is a particular attractive example of a random [...] Read more.
The study of random graphs has become very popular for real-life network modeling, such as social networks or financial networks. Inhomogeneous long-range percolation (or scale-free percolation) on the lattice Zd, d ≥ 1, is a particular attractive example of a random graph model because it fulfills several stylized facts of real-life networks. For this model, various geometric properties, such as the percolation behavior, the degree distribution and graph distances, have been analyzed. In the present paper, we complement the picture of graph distances and we prove continuity of the percolation probability in the phase transition point. We also provide an illustration of the model connected to financial networks. Full article
Show Figures

Figure 1

Previous Issue
Next Issue
Back to TopTop