Insurance Mathematics & Economics最新文献_第4页

Analytic valuation of guaranteed lifetime withdrawal benefits with a modified ratchet 采用修改后的棘轮法对保证终身提取福利进行分析估值

IF 1.9 2区经济学

Insurance Mathematics & Economics Pub Date : 2024-06-10 DOI: 10.1016/j.insmatheco.2024.06.001

Darcy Harcourt, Toby Daglish, Eric R. Ulm

引用次数: 0

Benefit volatility-targeting strategies in lifetime pension pools 终生养老金池的福利波动目标策略

IF 1.9 2区经济学

Insurance Mathematics & Economics Pub Date : 2024-06-06 DOI: 10.1016/j.insmatheco.2024.05.006

Jean-François Bégin, Barbara Sanders

{"title":"Benefit volatility-targeting strategies in lifetime pension pools","authors":"Jean-François Bégin, Barbara Sanders","doi":"10.1016/j.insmatheco.2024.05.006","DOIUrl":"10.1016/j.insmatheco.2024.05.006","url":null,"abstract":"<div><p>Lifetime pension pools—also known as group self-annuitization plans, pooled annuity funds, and retirement tontines in the literature—allow retirees to convert a lump sum into lifelong income, with payouts linked to investment performance and the collective mortality experience of the pool. Existing literature on these pools has predominantly examined basic investment strategies like constant allocations and investments solely in risk-free assets. Recent studies, however, proposed volatility targeting, aiming to enhance risk-adjusted returns and minimize downside risk. Yet they only considered investment risk in the volatility target, neglecting the impact of mortality risk on the strategy. This study thus aims to address this gap by investigating volatility-targeting strategies for both investment and mortality risks, offering a solution that keeps the risk associated with benefit variation as constant as possible through time. Specifically, we derive a new asset allocation strategy that targets both investment and mortality risks, and we provide insights about it. Practical investigations of the strategy demonstrate the effectiveness and robustness of the new dynamic volatility-targeting approach, ultimately leading to enhanced lifetime pension benefits.</p></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"118 ","pages":"Pages 72-94"},"PeriodicalIF":1.9,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167668724000623/pdfft?md5=00d5170f64043924f6f839f91565a832&pid=1-s2.0-S0167668724000623-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141401878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An excursion theoretic approach to Parisian ruin problem 用游览理论解决巴黎废墟问题

IF 1.9 2区经济学

Insurance Mathematics & Economics Pub Date : 2024-05-27 DOI: 10.1016/j.insmatheco.2024.05.001

Bo Li , Xiaowen Zhou

引用次数: 0

Optimal insurance with mean-deviation measures 采用均值--偏差测量法的最佳保险

IF 1.9 2区经济学

Insurance Mathematics & Economics Pub Date : 2024-05-24 DOI: 10.1016/j.insmatheco.2024.05.005

Tim J. Boonen , Xia Han

{"title":"Optimal insurance with mean-deviation measures","authors":"Tim J. Boonen , Xia Han","doi":"10.1016/j.insmatheco.2024.05.005","DOIUrl":"https://doi.org/10.1016/j.insmatheco.2024.05.005","url":null,"abstract":"<div><p>This paper studies an optimal insurance contracting problem in which the preferences of the decision maker are given by the sum of the expected loss and a convex, increasing function of a deviation measure. As for the deviation measure, our focus is on convex signed Choquet integrals (such as the Gini coefficient and a convex distortion risk measure minus the expected value) and on the standard deviation. We find that if the expected value premium principle is used, then stop-loss indemnities are optimal, and we provide a precise characterization of the corresponding deductible. Moreover, if the premium principle is based on Value-at-Risk or Expected Shortfall, then a particular layer-type indemnity is optimal, in which there is coverage for small losses up to a limit, and additionally for losses beyond another deductible. The structure of these optimal indemnities remains unchanged if there is a limit on the insurance premium budget. If the unconstrained solution is not feasible, then the deductible is increased to make the budget constraint binding. We provide several examples of these results based on the Gini coefficient and the standard deviation.</p></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"118 ","pages":"Pages 1-24"},"PeriodicalIF":1.9,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141163764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effective experience rating for large insurance portfolios via surrogate modeling 通过代用模型对大型保险组合进行有效的经验评级

IF 1.9 2区经济学

Insurance Mathematics & Economics Pub Date : 2024-05-24 DOI: 10.1016/j.insmatheco.2024.05.004

Sebastián Calcetero Vanegas, Andrei L. Badescu, X. Sheldon Lin

{"title":"Effective experience rating for large insurance portfolios via surrogate modeling","authors":"Sebastián Calcetero Vanegas, Andrei L. Badescu, X. Sheldon Lin","doi":"10.1016/j.insmatheco.2024.05.004","DOIUrl":"10.1016/j.insmatheco.2024.05.004","url":null,"abstract":"<div><p>Experience rating in insurance uses a Bayesian credibility model to upgrade the current premiums of a contract by taking into account policyholders' attributes and their claim history. Most data-driven models used for this task are mathematically intractable, and premiums must be obtained through numerical methods such as simulation via MCMC. However, these methods can be computationally expensive and even prohibitive for large portfolios when applied at the policyholder level. Additionally, these computations become “black-box” procedures as there is no analytical expression showing how the claim history of policyholders is used to upgrade their premiums. To address these challenges, this paper proposes a surrogate modeling approach to inexpensively derive an analytical expression for computing the Bayesian premiums for any given model, approximately. As a part of the methodology, the paper introduces a <em>likelihood-based summary statistic</em> of the policyholder's claim history that serves as the main input of the surrogate model and that is sufficient for certain families of distribution, including the exponential dispersion family. As a result, the computational burden of experience rating for large portfolios is reduced through the direct evaluation of such analytical expression, which can provide a transparent and interpretable way of computing Bayesian premiums.</p></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"118 ","pages":"Pages 25-43"},"PeriodicalIF":1.9,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S016766872400060X/pdfft?md5=485a9e9970e8fac466b99440e9e27b0a&pid=1-s2.0-S016766872400060X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141142117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Star-shaped acceptability indexes 星形可接受性指数

IF 1.9 2区经济学

Insurance Mathematics & Economics Pub Date : 2024-05-21 DOI: 10.1016/j.insmatheco.2024.05.002

Marcelo Brutti Righi

引用次数: 0

Loss modeling with the size-biased lognormal mixture and the entropy regularized EM algorithm 利用大小偏置对数正态混合物和熵正则化 EM 算法建立损失模型

IF 1.9 2区经济学

Insurance Mathematics & Economics Pub Date : 2024-05-14 DOI: 10.1016/j.insmatheco.2024.05.003

Taehan Bae , Tatjana Miljkovic

{"title":"Loss modeling with the size-biased lognormal mixture and the entropy regularized EM algorithm","authors":"Taehan Bae , Tatjana Miljkovic","doi":"10.1016/j.insmatheco.2024.05.003","DOIUrl":"10.1016/j.insmatheco.2024.05.003","url":null,"abstract":"<div><p>The Erlang mixture with a common scale parameter is one of many popular models for modeling insurance losses. However, the actuarial literature recognizes and discusses some limitations of aforementioned model in approximate heavy-tailed distributions. In this paper, a size-biased left-truncated Lognormal (SB-ltLN) mixture is proposed as a robust alternative to the Erlang mixture for modeling left-truncated insurance losses with a heavy tail. The weak denseness property of the weighted Lognormal mixture is studied along with the tail behavior. Explicit analytical solutions are derived for moments and Tail Value at Risk based on the proposed model. An extension of the regularized expectation–maximization (REM) algorithm with Shannon's entropy weights (ewREM) is introduced for parameter estimation and variability assessment. The Operational Riskdata eXchange's left-truncated internal fraud loss data set is used to illustrate applications of the proposed model. Finally, the results of a simulation study show promising performance of the proposed SB-ltLN mixture in different simulation settings.</p></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"117 ","pages":"Pages 182-195"},"PeriodicalIF":1.9,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167668724000593/pdfft?md5=2b45204562f484c02c7d4416265ecc17&pid=1-s2.0-S0167668724000593-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141025931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coping with longevity via hedging: Fair dynamic valuation of variable annuities 通过对冲应对长寿：变额年金的公平动态估值

IF 1.9 2区经济学

Insurance Mathematics & Economics Pub Date : 2024-05-13 DOI: 10.1016/j.insmatheco.2024.04.005

Ze Chen , Runhuan Feng , Hong Li , Tianyu Yang

引用次数: 0

Law-invariant return and star-shaped risk measures 收益不变定律和星形风险度量

IF 1.9 2区经济学

Insurance Mathematics & Economics Pub Date : 2024-05-07 DOI: 10.1016/j.insmatheco.2024.04.006

Roger J.A. Laeven , Emanuela Rosazza Gianin , Marco Zullino

{"title":"Law-invariant return and star-shaped risk measures","authors":"Roger J.A. Laeven , Emanuela Rosazza Gianin , Marco Zullino","doi":"10.1016/j.insmatheco.2024.04.006","DOIUrl":"https://doi.org/10.1016/j.insmatheco.2024.04.006","url":null,"abstract":"<div><p>This paper presents novel characterization results for classes of law-invariant star-shaped functionals. We begin by establishing characterizations for positively homogeneous and star-shaped functionals that exhibit second- or convex-order stochastic dominance consistency. Building on these characterizations, we proceed to derive Kusuoka-type representations for these functionals, shedding light on their mathematical structure and intimate connections to Value-at-Risk and Expected Shortfall. Furthermore, we offer representations of general law-invariant star-shaped functionals as robustifications of Value-at-Risk. Notably, our results are versatile, accommodating settings that may, or may not, involve monotonicity and/or cash-additivity. All of these characterizations are developed within a general locally convex topological space of random variables, ensuring the broad applicability of our results in various financial, insurance and probabilistic contexts.</p></div>","PeriodicalId":54974,"journal":{"name":"Insurance Mathematics & Economics","volume":"117 ","pages":"Pages 140-153"},"PeriodicalIF":1.9,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167668724000568/pdfft?md5=acfda4a738d5cd409403a125c396f768&pid=1-s2.0-S0167668724000568-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140905586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Testing for auto-calibration with Lorenz and Concentration curves 利用洛伦兹曲线和浓度曲线进行自动校准测试

IF 1.9 2区经济学

Insurance Mathematics & Economics Pub Date : 2024-05-06 DOI: 10.1016/j.insmatheco.2024.04.003

Michel Denuit , Julie Huyghe , Julien Trufin , Thomas Verdebout

引用次数: 0