North American Actuarial Journal最新文献_第5页

Flexible Weather Index Insurance Design with Penalized Splines 基于惩罚样条的灵活天气指数保险设计

North American Actuarial Journal Pub Date : 2023-02-03 DOI: 10.1080/10920277.2022.2162924

Ken Seng Tan, Jinggong Zhang

{"title":"Flexible Weather Index Insurance Design with Penalized Splines","authors":"Ken Seng Tan, Jinggong Zhang","doi":"10.1080/10920277.2022.2162924","DOIUrl":"https://doi.org/10.1080/10920277.2022.2162924","url":null,"abstract":"In this article, we propose a flexible framework for the design of weather index insurance (WII) based on penalized spline methods. The aim is to find the indemnity function that optimally characterizes the intricate relationship between agricultural production losses and weather variables and thus effectively improves policyholders’ utilities. We use B-spline functions to define the feasible set of the optimization problem and a penalty function to avoid the “overfitting” issue. The proposed design framework is applied to an empirical study in which we use precipitation and vapor pressure deficit (VPD) to construct an index insurance contract for corn producers in Illinois. Numerical evidence shows that the resulting optimal insurance contract effectively enhances policyholder’s utility, even in the absence of the government’s premium subsidy. In addition, the performance of our proposed index insurance is robust to a variety of key factors, and the general payment structure is highly interpretable for marketing purposes. All of these merits indicate its potential to increase efficiency of the agricultural insurance market and thus enhance social welfare.","PeriodicalId":46812,"journal":{"name":"North American Actuarial Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135205969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multivariate Insurance Portfolio Risk Retention Using the Method of Multipliers 基于乘数方法的多变量保险组合风险保持

IF 1.4

North American Actuarial Journal Pub Date : 2023-01-27 DOI: 10.1080/10920277.2022.2161578

Gee Y. Lee

{"title":"Multivariate Insurance Portfolio Risk Retention Using the Method of Multipliers","authors":"Gee Y. Lee","doi":"10.1080/10920277.2022.2161578","DOIUrl":"https://doi.org/10.1080/10920277.2022.2161578","url":null,"abstract":"For an insurance company insuring multiple risks, capital allocation is an important practical problem. In the capital allocation problem, the insurance company must determine the amount of capital to assign to each policy or, equivalently, the amount of premium to be collected from each policy. Doing this relates to the problem of determining the risk retention parameters for each policy within the portfolio. In this article, the insurance risk retention problem of determining the optimal retention parameters is explored in a multivariate context. Given an underlying claims distribution and premium constraint, we are interested in finding the optimal amount of risk to retain or, equivalently, which level of risk retention parameters should be chosen by an insurance company. The risk retention parameter may be deductible (d), upper limit (u), or coinsurance (c). We present a numerical approach to solving the risk retention problem using the method of multipliers and illustrate how it can be implemented. In a case study, the minimum amount of premium to be collected is used as a constraint to the optimization and the upper limit is optimized for each policyholder. A Bayesian approach is taken for estimation of the parameters in a simple model involving regional effects and individual policyholder effects for the Wisconsin Local Government Property Insurance Fund (LGPIF) data, where the parameter estimation is performed in the R computing environment using the Stan library.","PeriodicalId":46812,"journal":{"name":"North American Actuarial Journal","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2023-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49207702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Society of Actuaries and North American Actuarial Journal Announce New Editor 精算师协会和北美精算杂志宣布新编辑

IF 1.4

North American Actuarial Journal Pub Date : 2023-01-02 DOI: 10.1080/10920277.2023.2169533

引用次数: 0

On a Risk Model With Dual Seasonalities 具有双重季节性的风险模型

IF 1.4

North American Actuarial Journal Pub Date : 2023-01-02 DOI: 10.1080/10920277.2022.2068611

Yang Miao, Kristina P. Sendova, B. Jones

引用次数: 2

The Automated Bias-Corrected and Accelerated Bootstrap Confidence Intervals for Risk Measures 风险度量的自动偏差校正和加速Bootstrap置信区间

IF 1.4

North American Actuarial Journal Pub Date : 2022-12-02 DOI: 10.1080/10920277.2022.2141781

B. Grün, T. Miljkovic

{"title":"The Automated Bias-Corrected and Accelerated Bootstrap Confidence Intervals for Risk Measures","authors":"B. Grün, T. Miljkovic","doi":"10.1080/10920277.2022.2141781","DOIUrl":"https://doi.org/10.1080/10920277.2022.2141781","url":null,"abstract":"Different approaches to determining two-sided interval estimators for risk measures such as Value-at-Risk (VaR) and conditional tail expectation (CTE) when modeling loss data exist in the actuarial literature. Two contrasting methods can be distinguished: a nonparametric one not relying on distributional assumptions or a fully parametric one relying on standard asymptotic theory to apply. We complement these approaches and take advantage of currently available computer power to propose the bias-corrected and accelerated (BCA) confidence intervals for VaR and CTE. The BCA confidence intervals allow the use of a parametric model but do not require standard asymptotic theory to apply. We outline the details to determine interval estimators for these three different approaches using general computational tools as well as with analytical formulas when assuming the truncated Lognormal distribution as a parametric model for insurance loss data. An extensive simulation study is performed to assess the performance of the proposed BCA method in comparison to the two alternative methods. A real dataset of left-truncated insurance losses is employed to illustrate the implementation of the BCA-VaR and BCA-CTE interval estimators in practice when using the truncated Lognormal distribution for modeling the loss data.","PeriodicalId":46812,"journal":{"name":"North American Actuarial Journal","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45276732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computing and Estimating Distortion Risk Measures: How to Handle Analytically Intractable Cases? 计算和估计失真风险度量：如何处理分析难以解决的病例？

IF 1.4

North American Actuarial Journal Pub Date : 2022-11-30 DOI: 10.1080/10920277.2022.2137201

Sahadeb Upretee, V. Brazauskas

{"title":"Computing and Estimating Distortion Risk Measures: How to Handle Analytically Intractable Cases?","authors":"Sahadeb Upretee, V. Brazauskas","doi":"10.1080/10920277.2022.2137201","DOIUrl":"https://doi.org/10.1080/10920277.2022.2137201","url":null,"abstract":"In insurance data analytics and actuarial practice, distortion risk measures are used to capture the riskiness of the distribution tail. Point and interval estimates of the risk measures are then employed to price extreme events, to develop reserves, to design risk transfer strategies, and to allocate capital. Often the computation of those estimates relies on Monte Carlo simulations, which, depending upon the complexity of the problem, can be very costly in terms of required expertise and computational time. In this article, we study analytic and numerical evaluation of distortion risk measures, with the expectation that the proposed formulas or inequalities will reduce the computational burden. Specifically, we consider several distortion risk measures––value-at-risk (VaR), conditional tail expectation (cte), proportional hazards transform (pht), Wang transform (wt), and Gini shortfall (gs)––and evaluate them when the loss severity variable follows shifted exponential, Pareto I, and shifted lognormal distributions (all chosen to have the same support), which exhibit common distributional shapes of insurance losses. For these choices of risk measures and loss models, only the VaR and cte measures always possess explicit formulas. For pht, wt, and gs, there are cases when the analytic treatment of the measure is not feasible. In the latter situations, conditions under which the measure is finite are studied rigorously. In particular, we prove several theorems that specify two-sided bounds for the analytically intractable cases. The quality of the bounds is further investigated by comparing them with numerically evaluated risk measures. Finally, a simulation study involving application of those bounds in statistical estimation of the risk measures is also provided.","PeriodicalId":46812,"journal":{"name":"North American Actuarial Journal","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46989295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Are Internal Capital Markets Ex Post Efficient? 内部资本市场事后有效吗?

IF 1.4

North American Actuarial Journal Pub Date : 2022-11-08 DOI: 10.1080/10920277.2022.2126373

James M. Carson, Evan M. Eastman, David L. Eckles, Joshua D. Frederick

引用次数: 2

Conformal Prediction Credibility Intervals 保形预测可信区间

IF 1.4

North American Actuarial Journal Pub Date : 2022-10-25 DOI: 10.1080/10920277.2022.2123364

Liang Hong

引用次数: 0

An Empirical Assessment of Regulatory Lag in Insurance Rate Filings 保险费率备案监管滞后的实证评估

IF 1.4

North American Actuarial Journal Pub Date : 2022-10-20 DOI: 10.1080/10920277.2022.2123360

P. Born, J. Bradley Karl, R. Klein

{"title":"An Empirical Assessment of Regulatory Lag in Insurance Rate Filings","authors":"P. Born, J. Bradley Karl, R. Klein","doi":"10.1080/10920277.2022.2123360","DOIUrl":"https://doi.org/10.1080/10920277.2022.2123360","url":null,"abstract":"In this article, we evaluate factors that help to explain an important source of variation in insurers' rate filing experiences across states and over time for personal automobile insurance. Using a new source of data from personal auto insurance rate filings for all U.S. insurers, we examine factors associated with regulatory lag. The timeliness of the disposition of insurers' rate filings is important, as significant delays can undermine the usefulness of the actuarial analysis required for justifying rate changes and may result in rate inadequacy pending the approval of rate increases. While there is a considerable literature on the effect of rate regulation regimes on insurance market outcomes, this is the first article that evaluates factors associated with regulatory lag. We use a principal components approach to explore the relative influence of various factors on the timeliness of filing approval. These factors are associated with (1) industry interest, resources, and influence, (2) demand conditions, complexity, and saliency, (3) the goals of political elites, and (4) the goals and resources of regulators as important drivers of insurers' rate filing experience. We find that state rate filing statutes account for some of the variation in regulatory lag and identify other significant factors that explain the variation in the timeliness of rate approvals across states and over time.","PeriodicalId":46812,"journal":{"name":"North American Actuarial Journal","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46478713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bayesian Multivariate Mixed Poisson Models with Copula-Based Mixture 基于copula的Bayesian多元混合泊松模型

IF 1.4

North American Actuarial Journal Pub Date : 2022-09-30 DOI: 10.1080/10920277.2022.2112233

Pengcheng Zhang, E. Calderín-Ojeda, Shuanming Li, Xueyuan Wu

{"title":"Bayesian Multivariate Mixed Poisson Models with Copula-Based Mixture","authors":"Pengcheng Zhang, E. Calderín-Ojeda, Shuanming Li, Xueyuan Wu","doi":"10.1080/10920277.2022.2112233","DOIUrl":"https://doi.org/10.1080/10920277.2022.2112233","url":null,"abstract":"It is common practice to use multivariate count modeling in actuarial literature when dealing with claim counts from insurance policies with multiple covers. One possible way to construct such a model is to implement copula directly on discrete margins. However, likelihood inference under this construction involves the computation of multidimensional rectangle probabilities, which could be computationally expensive, especially in the elliptical copula case. Another potential approach is based on the multivariate mixed Poisson model. The crucial work under this method is to find an appropriate multivariate continuous distribution for mixing parameters. By virtue of the copula, this issue could be easily addressed. Under such a framework, the Markov chain Monte Carlo (MCMC) method is a feasible strategy for inference. The usefulness of our model is then illustrated through a real-life example. The empirical analysis demonstrates the superiority of adopting a copula-based mixture over other types of mixtures. Finally, we demonstrate how those fitted models can be applied to the insurance ratemaking problem in a Bayesian context.","PeriodicalId":46812,"journal":{"name":"North American Actuarial Journal","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42189061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0