Subjects -> BUSINESS AND ECONOMICS (Total: 3844 journals)
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INSURANCE (26 journals)

Showing 1 - 27 of 27 Journals sorted alphabetically
Annals of Actuarial Science     Full-text available via subscription   (Followers: 2)
Asia-Pacific Journal of Risk and Insurance     Hybrid Journal   (Followers: 7)
Assurances et gestion des risques     Full-text available via subscription  
Astin Bulletin     Full-text available via subscription   (Followers: 1)
Banks in Insurance Report     Hybrid Journal   (Followers: 1)
Blätter der DGVFM     Hybrid Journal   (Followers: 2)
British Actuarial Journal     Full-text available via subscription   (Followers: 1)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 14)
Geneva Risk and Insurance Review     Hybrid Journal   (Followers: 8)
Health Affairs     Full-text available via subscription   (Followers: 82)
Insurance Markets and Companies     Open Access   (Followers: 1)
Insurance: Mathematics and Economics     Hybrid Journal   (Followers: 10)
International Journal of Business Continuity and Risk Management     Hybrid Journal   (Followers: 28)
International Journal of Forensic Engineering     Hybrid Journal   (Followers: 3)
International Journal of Forensic Engineering and Management     Hybrid Journal   (Followers: 3)
International Journal of Health Economics and Management     Hybrid Journal   (Followers: 12)
International Social Security Review     Hybrid Journal   (Followers: 8)
Journal for Labour Market Research     Open Access   (Followers: 10)
Journal of Derivatives & Hedge Funds     Hybrid Journal   (Followers: 9)
Journal of Risk and Insurance     Hybrid Journal   (Followers: 18)
Journal of Risk Finance     Hybrid Journal   (Followers: 6)
Risk Management     Hybrid Journal   (Followers: 15)
Risk Management & Insurance Review     Hybrid Journal   (Followers: 11)
Scandinavian Actuarial Journal     Hybrid Journal   (Followers: 2)
SourceOECD Finance & Investment/Insurance & Pensions     Full-text available via subscription   (Followers: 3)
The Geneva Reports     Free   (Followers: 2)
Zeitschrift für die gesamte Versicherungswissenschaft     Hybrid Journal   (Followers: 1)
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Journal Cover
Astin Bulletin
Journal Prestige (SJR): 0.878
Citation Impact (citeScore): 1
Number of Followers: 1  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 0515-0361 - ISSN (Online) 1783-1350
Published by Cambridge University Press Homepage  [398 journals]
  • ASB volume 51 issue 2 Cover and Front matter

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      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.15
      Issue No: Vol. 51, No. 2 (2021)
       
  • ASB volume 51 issue 2 Cover and Back matter

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      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.16
      Issue No: Vol. 51, No. 2 (2021)
       
  • A DOUBLE COMMON FACTOR MODEL FOR MORTALITY PROJECTION USING
           BEST-PERFORMANCE MORTALITY RATES AS REFERENCE

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      Authors: Jackie Li; Maggie Lee, Simon Guthrie
      Pages: 349 - 374
      Abstract: We construct a double common factor model for projecting the mortality of a population using as a reference the minimum death rate at each age among a large number of countries. In particular, the female and male minimum death rates, described as best-performance or best-practice rates, are first modelled by a common factor model structure with both common and sex-specific parameters. The differences between the death rates of the population under study and the best-performance rates are then modelled by another common factor model structure. An important result of using our proposed model is that the projected death rates of the population being considered are coherent with the projected best-performance rates in the long term, the latter of which serves as a very useful reference for the projection based on the collective experience of multiple countries. Our out-of-sample analysis shows that the new model has potential to outperform some conventional approaches in mortality projection.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2020.44
      Issue No: Vol. 51, No. 2 (2021)
       
  • GEOGRAPHICAL DIVERSIFICATION AND LONGEVITY RISK MITIGATION IN ANNUITY
           PORTFOLIOS

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      Authors: Clemente De Rosa; Elisa Luciano, Luca Regis
      Pages: 375 - 410
      Abstract: This paper provides a method to assess the risk relief deriving from a foreign expansion by a life insurance company. We build a parsimonious continuous-time model for longevity risk that captures the dependence across different ages in domestic versus foreign populations. We calibrate the model to portray the case of a UK annuity portfolio expanding internationally toward Italian policyholders. The longevity risk diversification benefits of an international expansion are sizable, in particular when interest rates are low. The benefits are judged based on traditional measures, such as the Risk Margin or volatility reduction, and on a novel measure, the Diversification Index.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.12
      Issue No: Vol. 51, No. 2 (2021)
       
  • PRICING LONGEVITY-LINKED SECURITIES IN THE PRESENCE OF MORTALITY TREND
           CHANGES

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      Authors: Arne Freimann
      Pages: 411 - 447
      Abstract: Even though the trend in mortality improvements has experienced several permanent changes in the past, the uncertainty regarding future mortality trends is often left unmodeled when pricing longevity-linked securities. In this paper, we present a stochastic modeling framework for the valuation of longevity-linked securities which explicitly considers the risk of random future changes in the long-term mortality trend. We construct a set of meaningful probability distortions which imply equivalent risk-adjusted pricing measures under which the basic model structure is preserved. Inspired by risk-based capital requirements for (re)insurers, we also establish a cost-of-capital pricing approach which then serves as the appropriate reference framework for finding a reasonable range for the market price of longevity risk. In a numerical application, we demonstrate that our model produces plausible risk loadings and show that a greater proportion of the risk loading is allocated to longer maturities when the risk of random future mortality trend changes is adequately modeled.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.5
      Issue No: Vol. 51, No. 2 (2021)
       
  • DYNAMIC ASSET ALLOCATION FOR TARGET DATE FUNDS UNDER THE BENCHMARK
           APPROACH

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      Authors: Jin Sun; Dan Zhu, Eckhard Platen
      Pages: 449 - 474
      Abstract: Target date funds (TDFs) are becoming increasingly popular investment choices among investors with long-term prospects. Examples include members of superannuation funds seeking to save for retirement at a given age. TDFs provide efficient risk exposures to a diversified range of asset classes that dynamically match the risk profile of the investment payoff as the investors age. This is often achieved by making increasingly conservative asset allocations over time as the retirement date approaches. Such dynamically evolving allocation strategies for TDFs are often referred to as glide paths. We propose a systematic approach to the design of optimal TDF glide paths implied by retirement dates and risk preferences and construct the corresponding dynamic asset allocation strategy that delivers the optimal payoffs at minimal costs. The TDF strategies we propose are dynamic portfolios consisting of units of the growth-optimal portfolio (GP) and the risk-free asset. Here, the GP is often approximated by a well-diversified index of multiple risky assets. We backtest the TDF strategies with the historical returns of the S&P500 total return index serving as the GP approximation.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.6
      Issue No: Vol. 51, No. 2 (2021)
       
  • ROBUST ESTIMATION OF LOSS MODELS FOR LOGNORMAL INSURANCE PAYMENT SEVERITY
           DATA

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      Authors: Chudamani Poudyal
      Pages: 475 - 507
      Abstract: The primary objective of this scholarly work is to develop two estimation procedures – maximum likelihood estimator (MLE) and method of trimmed moments (MTM) – for the mean and variance of lognormal insurance payment severity data sets affected by different loss control mechanism, for example, truncation (due to deductibles), censoring (due to policy limits), and scaling (due to coinsurance proportions), in insurance and financial industries. Maximum likelihood estimating equations for both payment-per-payment and payment-per-loss data sets are derived which can be solved readily by any existing iterative numerical methods. The asymptotic distributions of those estimators are established via Fisher information matrices. Further, with a goal of balancing efficiency and robustness and to remove point masses at certain data points, we develop a dynamic MTM estimation procedures for lognormal claim severity models for the above-mentioned transformed data scenarios. The asymptotic distributional properties and the comparison with the corresponding MLEs of those MTM estimators are established along with extensive simulation studies. Purely for illustrative purpose, numerical examples for 1500 US indemnity losses are provided which illustrate the practical performance of the established results in this paper.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.4
      Issue No: Vol. 51, No. 2 (2021)
       
  • TEMPERED PARETO-TYPE MODELLING USING WEIBULL DISTRIBUTIONS

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      Authors: Hansjörg Albrecher; José Carlos Araujo-Acuna, Jan Beirlant
      Pages: 509 - 538
      Abstract: In various applications of heavy-tail modelling, the assumed Pareto behaviour is tempered ultimately in the range of the largest data. In insurance applications, claim payments are influenced by claim management and claims may, for instance, be subject to a higher level of inspection at highest damage levels leading to weaker tails than apparent from modal claims. Generalizing earlier results of Meerschaert et al. (2012) and Raschke (2020), in this paper we consider tempering of a Pareto-type distribution with a general Weibull distribution in a peaks-over-threshold approach. This requires to modulate the tempering parameters as a function of the chosen threshold. Modelling such a tempering effect is important in order to avoid overestimation of risk measures such as the value-at-risk at high quantiles. We use a pseudo maximum likelihood approach to estimate the model parameters and consider the estimation of extreme quantiles. We derive basic asymptotic results for the estimators, give illustrations with simulation experiments and apply the developed techniques to fire and liability insurance data, providing insight into the relevance of the tempering component in heavy-tail modelling.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2020.43
      Issue No: Vol. 51, No. 2 (2021)
       
  • ESTIMATION OF HIGH CONDITIONAL TAIL RISK BASED ON EXPECTILE REGRESSION

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      Authors: Jie Hu; Yu Chen, Keqi Tan
      Pages: 539 - 570
      Abstract: Assessing conditional tail risk at very high or low levels is of great interest in numerous applications. Due to data sparsity in high tails, the widely used quantile regression method can suffer from high variability at the tails, especially for heavy-tailed distributions. As an alternative to quantile regression, expectile regression, which relies on the minimization of the asymmetric l2-norm and is more sensitive to the magnitudes of extreme losses than quantile regression, is considered. In this article, we develop a new estimation method for high conditional tail risk by first estimating the intermediate conditional expectiles in regression framework, and then estimating the underlying tail index via weighted combinations of the top order conditional expectiles. The resulting conditional tail index estimators are then used as the basis for extrapolating these intermediate conditional expectiles to high tails based on reasonable assumptions on tail behaviors. Finally, we use these high conditional tail expectiles to estimate alternative risk measures such as the Value at Risk (VaR) and Expected Shortfall (ES), both in high tails. The asymptotic properties of the proposed estimators are investigated. Simulation studies and real data analysis show that the proposed method outperforms alternative approaches.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.3
      Issue No: Vol. 51, No. 2 (2021)
       
  • ASYMPTOTICS FOR SYSTEMIC RISK WITH DEPENDENT HEAVY-TAILED LOSSES

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      Authors: Jiajun Liu; Yang Yang
      Pages: 571 - 605
      Abstract: Systemic risk (SR) is considered as the risk of collapse of an entire system, which has played a significant role in explaining the recent financial turmoils from the insurance and financial industries. We consider the asymptotic behavior of the SR for portfolio losses in the model allowing for heavy-tailed primary losses, which are equipped with a wide type of dependence structure. This risk model provides an ideal framework for addressing both heavy-tailedness and dependence. As some extensions, several simulation experiments are conducted, where an insurance application of the asymptotic characterization to the determination and approximation of related SR capital has been proposed, based on the SR measure.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.11
      Issue No: Vol. 51, No. 2 (2021)
       
  • OPTIMAL REINSURANCE DESIGN WITH DISTORTION RISK MEASURES AND ASYMMETRIC
           INFORMATION

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      Authors: Tim J. Boonen; Yiying Zhang
      Pages: 607 - 629
      Abstract: This paper studies a problem of optimal reinsurance design under asymmetric information. The insurer adopts distortion risk measures to quantify his/her risk position, and the reinsurer does not know the functional form of this distortion risk measure. The risk-neutral reinsurer maximizes his/her net profit subject to individual rationality and incentive compatibility constraints. The optimal reinsurance menu is succinctly derived under the assumption that one type of insurer has a larger willingness to pay than the other type of insurer for every risk. Some comparative analyses are given as illustrations when the insurer adopts the value at risk or the tail value at risk as preferences.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.8
      Issue No: Vol. 51, No. 2 (2021)
       
  • OPTIMAL REINSURANCE FROM THE VIEWPOINTS OF BOTH AN INSURER AND A REINSURER
           UNDER THE CVAR RISK MEASURE AND VAJDA CONDITION

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      Authors: Yanhong Chen
      Pages: 631 - 659
      Abstract: In this paper, we study the optimal reinsurance contracts that minimize the convex combination of the Conditional Value-at-Risk (CVaR) of the insurer’s loss and the reinsurer’s loss over the class of ceded loss functions such that the retained loss function is increasing and the ceded loss function satisfies Vajda condition. Among a general class of reinsurance premium principles that satisfy the properties of risk loading and convex order preserving, the optimal solutions are obtained. Our results show that the optimal ceded loss functions are in the form of five interconnected segments for general reinsurance premium principles, and they can be further simplified to four interconnected segments if more properties are added to reinsurance premium principles. Finally, we derive optimal parameters for the expected value premium principle and give a numerical study to analyze the impact of the weighting factor on the optimal reinsurance.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.9
      Issue No: Vol. 51, No. 2 (2021)
       
  • OPTIMAL INCENTIVE-COMPATIBLE INSURANCE WITH BACKGROUND RISK

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      Authors: Yichun Chi; Ken Seng Tan
      Pages: 661 - 688
      Abstract: In this paper, the optimal insurance design is studied from the perspective of an insured, who faces an insurable risk and a background risk. For the reduction of ex post moral hazard, alternative insurance contracts are asked to satisfy the principle of indemnity and the incentive-compatible condition. As in the literature, it is assumed that the insurer calculates the insurance premium solely on the basis of the expected indemnity. When the insured has a general mean-variance preference, an explicit form of optimal insurance is derived explicitly. It is found that the stochastic dependence between the background risk and the insurable risk plays a critical role in the insured’s risk transfer decision. In addition, the optimal insurance policy can often change significantly once the incentive-compatible constraint is removed.
      PubDate: 2021-05-01T00:00:00.000Z
      DOI: 10.1017/asb.2021.7
      Issue No: Vol. 51, No. 2 (2021)
       
 
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