North American Actuarial Journal最新文献_第5页

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":" ","pages":""},"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":" ","pages":""},"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":"27 1","pages":"602 - 617"},"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":"27 1","pages":"560 - 578"},"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

Why Changes in PBGC and FDIC Premiums Should Not Fully Reflect Changes in Underlying Risk (With Some Application to Long-Term Private Insurance Contracts) 为什么PBGC和FDIC保费的变化不应完全反映潜在风险的变化（适用于长期私人保险合同）

IF 1.4

North American Actuarial Journal Pub Date : 2022-09-30 DOI: 10.1080/10920277.2022.2123362

David McCarthy

{"title":"Why Changes in PBGC and FDIC Premiums Should Not Fully Reflect Changes in Underlying Risk (With Some Application to Long-Term Private Insurance Contracts)","authors":"David McCarthy","doi":"10.1080/10920277.2022.2123362","DOIUrl":"https://doi.org/10.1080/10920277.2022.2123362","url":null,"abstract":"The degree of risk adjustment in both FDIC and PBGC premiums appears to be much smaller than actuarially fair. We explore why this is using a stylized theoretical model of multiperiod insurance contracts in the presence of moral hazard where the risk status of insureds changes over the life of the contract. If insureds value stable premiums and there is moral hazard, we show that the optimal multiperiod insurance contract for full insurance allocates greater premiums to higher risk states, and lower premiums to lower risk states, but the optimal allocation of premiums across risk states will usually not be actuarially fair. The degree of risk adjustment rises with the extent of moral hazard and falls as risk aversion rises. We extend our analysis to examine optimal risk classification in private insurance in the presence of moral hazard, with similar results. We also discuss practical considerations that further reduce the desirability and feasibility of actuarially fair risk adjustments in premiums for the FDIC and PBGC, and show how our model extends prior work on social insurance with moral hazard.","PeriodicalId":46812,"journal":{"name":"North American Actuarial Journal","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41804844","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

Updating Bonus–Malus Indexing Mechanism to Adjust Long-Term Health Insurance Premiums 更新奖金-Malus指数机制以调整长期健康保险费率

IF 1.4

North American Actuarial Journal Pub Date : 2022-09-30 DOI: 10.1080/10920277.2022.2110123

Atefeh Kanani Dizaji, Amir T. Payandeh Najafabadi

引用次数: 0

A Model Stacking Approach for Forecasting Mortality 预测死亡率的模型叠加法

IF 1.4

North American Actuarial Journal Pub Date : 2022-09-22 DOI: 10.1080/10920277.2022.2108453

Jackie Li

引用次数: 1