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Dynamic importance allocated nested simulation for variable annuity risk measurement 动态重要度分配嵌套模拟变量年金风险度量
IF 1.7
Annals of Actuarial Science Pub Date : 2022-02-21 DOI: 10.1017/s1748499521000257
Ou Dang, Mingbin Feng, Mary R. Hardy
{"title":"Dynamic importance allocated nested simulation for variable annuity risk measurement","authors":"Ou Dang, Mingbin Feng, Mary R. Hardy","doi":"10.1017/s1748499521000257","DOIUrl":"https://doi.org/10.1017/s1748499521000257","url":null,"abstract":"<p>Estimating tail risk measures for portfolios of complex variable annuities is an important enterprise risk management task which usually requires nested simulation. In the nested simulation, the outer simulation stage involves projecting scenarios of key risk factors under the real-world measure, while the inner simulations are used to value pay-offs under guarantees of varying complexity, under a risk-neutral measure. In this paper, we propose and analyse an efficient simulation approach that dynamically allocates the inner simulations to the specific outer scenarios that are most likely to generate larger losses. These scenarios are identified using a proxy calculation that is used only to rank the outer scenarios, not to estimate the tail risk measure directly. As the proxy ranking will not generally provide a perfect match to the true ranking of outer scenarios, we calculate a measure based on the concomitant of order statistics to test whether further tail scenarios are required to ensure, with given confidence, that the true tail scenarios are captured. This procedure, which we call the dynamic importance allocated nested simulation approach, automatically adjusts for the relationship between the proxy calculations and the true valuations and also signals when the proxy is not sufficiently accurate.</p>","PeriodicalId":44135,"journal":{"name":"Annals of Actuarial Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138509586","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
Real-time measurement of portfolio mortality levels in the presence of shocks and reporting delays 存在冲击和报告延迟情况下投资组合死亡率水平的实时测量
IF 1.7
Annals of Actuarial Science Pub Date : 2022-02-21 DOI: 10.1017/S1748499522000021
S. Richards
{"title":"Real-time measurement of portfolio mortality levels in the presence of shocks and reporting delays","authors":"S. Richards","doi":"10.1017/S1748499522000021","DOIUrl":"https://doi.org/10.1017/S1748499522000021","url":null,"abstract":"Abstract The COVID-19 pandemic requires that actuaries track short-term mortality fluctuations in the portfolios they manage. This demands methods that not only operate over much shorter time periods than a year but that also deal with reporting delays. In this paper, we consider a semi-parametric approach for tracking portfolio mortality levels in continuous time. We identify both seasonal patterns and mortality shocks, thus providing a comparison benchmark for the impact of COVID-19 in terms of a portfolio’s own past experience. A parametric model is presented to allow for the average impact of seasonal variation and also reporting delays. We find that an estimate of mortality reporting delays can be made from a single extract of experience data. This can be used to forecast unreported deaths and improve estimates of recent mortality levels. Results are given for annuity portfolios in France, the UK and the USA.","PeriodicalId":44135,"journal":{"name":"Annals of Actuarial Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48970111","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: 3
Optimal investment strategy for a DC pension fund plan in a finite horizon time: an optimal stochastic control approach 有限时间内DC养老基金计划的最优投资策略：一种最优随机控制方法
IF 1.7
Annals of Actuarial Science Pub Date : 2022-02-18 DOI: 10.1017/S1748499521000270
Saman Vahabi, Amir T. Payandeh Najafabadi
{"title":"Optimal investment strategy for a DC pension fund plan in a finite horizon time: an optimal stochastic control approach","authors":"Saman Vahabi, Amir T. Payandeh Najafabadi","doi":"10.1017/S1748499521000270","DOIUrl":"https://doi.org/10.1017/S1748499521000270","url":null,"abstract":"Abstract This paper obtains an optimal strategy in a finite horizon time for a portfolio of a defined contribution (DC) pension fund for an investor with the CRRA utility function. It employs the optimal stochastic control method in a financial market with two different asset markets, one risk-free and another one risky asset in which its jump follows either by a finite or infinite activity Lévy process. Sensitivity of jump parameters in an uncertainty financial market has been studied.","PeriodicalId":44135,"journal":{"name":"Annals of Actuarial Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45221015","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
On the integration of deterministic opinions into mortality smoothing and forecasting 确定性意见在死亡率平滑和预测中的整合
IF 1.7
Annals of Actuarial Science Pub Date : 2022-02-09 DOI: 10.1017/S1748499521000282
V. Djeundje
{"title":"On the integration of deterministic opinions into mortality smoothing and forecasting","authors":"V. Djeundje","doi":"10.1017/S1748499521000282","DOIUrl":"https://doi.org/10.1017/S1748499521000282","url":null,"abstract":"Abstract Modelling and forecasting mortality is a topic of crucial importance to actuaries and demographers. However, forecasts from the majority of mortality projection models are continuations of past trends seen in the data. As such, these models are unable to account for external opinions or expert judgement. In this work, we present a method for the incorporation of deterministic opinions into the smoothing and forecasting of mortality rates using constraints. Not only does our approach yield a smooth transition from the past into the future, but also, the shapes of the resulting forecasts are governed by a combination of the opinion inputs and the speed of improvements observed in the data. In addition, our approach offers the possibility to compute the amount of uncertainty around the projected mortality trends conditional on the opinion inputs, and this allows us to highlight some of the pitfalls of deterministic projection methods.","PeriodicalId":44135,"journal":{"name":"Annals of Actuarial Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47397258","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: 2
Bayesian vine copulas for modelling dependence in data breach losses 数据泄露损失依赖性建模的贝叶斯藤copula
IF 1.7
Annals of Actuarial Science Pub Date : 2022-02-03 DOI: 10.1017/S174849952200001X
Jia Liu, Jackie Li, K. Daly
{"title":"Bayesian vine copulas for modelling dependence in data breach losses","authors":"Jia Liu, Jackie Li, K. Daly","doi":"10.1017/S174849952200001X","DOIUrl":"https://doi.org/10.1017/S174849952200001X","url":null,"abstract":"Abstract Potentialdata breach losses represent a significant part of operational risk and can be a serious concern for risk managers and insurers. In this paper, we employ the vine copulas under a Bayesian framework to co-model incidences from different data breach types. A full Bayesian approach can allow one to select both the copulas and margins and estimate their parameters in a coherent fashion. In particular, it can incorporate process, parameter, and model uncertainties, and this is very important for applications in risk management under current regulations. We also conduct a series of sensitivity tests on the Bayesian modelling results. Using two public data sets of data breach losses, we find that the overall dependency structure and tail dependence vary significantly between different types of data breaches. The optimally selected vine structure and pairwise copulas suggest more conservative value-at-risk estimates when compared to the other suboptimal copula models.","PeriodicalId":44135,"journal":{"name":"Annals of Actuarial Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43657957","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: 4
On RVaR-based optimal partial hedging 基于rvar的最优部分套期保值
IF 1.7
Annals of Actuarial Science Pub Date : 2022-01-25 DOI: 10.1017/S1748499521000269
A. Melnikov, Hongxi Wan
{"title":"On RVaR-based optimal partial hedging","authors":"A. Melnikov, Hongxi Wan","doi":"10.1017/S1748499521000269","DOIUrl":"https://doi.org/10.1017/S1748499521000269","url":null,"abstract":"Abstract The main aim of this paper is to develop an optimal partial hedging strategy that minimises an investor’s shortfall subject to an initial wealth constraint. The risk criterion we employ is a robust tail risk measure called Range Value-at-Risk (RVaR) which belongs to a wider class of distortion risk measures and contains the well-known measures VaR and CVaR as important limiting cases. Explicit forms of such RVaR-based optimal hedging strategies are derived. In addition, we provide a numerical example to demonstrate how to apply this more comprehensive methodology of partial hedging in the area of mixed finance/insurance contracts in the market with long-range dependence.","PeriodicalId":44135,"journal":{"name":"Annals of Actuarial Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43006127","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
AI: Coming of age? AI：成年？
IF 1.7
Annals of Actuarial Science Pub Date : 2022-01-19 DOI: 10.1017/S1748499521000245
T. Maynard, Luca Baldassarre, Y. de Montjoye, L. McFall, M. Óskarsdóttir
{"title":"AI: Coming of age?","authors":"T. Maynard, Luca Baldassarre, Y. de Montjoye, L. McFall, M. Óskarsdóttir","doi":"10.1017/S1748499521000245","DOIUrl":"https://doi.org/10.1017/S1748499521000245","url":null,"abstract":"Abstract AI has had many summers and winters. Proponents have overpromised, and there has been hype and disappointment. In recent years, however, we have watched with awe, surprise, and hope at the successes: Better than human capabilities of image-recognition; winning at Go; useful chatbots that seem to understand your needs; recommendation algorithms harvesting the wisdom of crowds. And with this success comes the spectre of danger. Machine behaviours that embed the worst of human prejudice and biases; techniques trying to exploit human weaknesses to skew elections or prompt self-harming behaviours. Are we seeing a perfect storm of social media, sensor technologies, new algorithms and edge computing? With this backdrop: is AI coming of age?","PeriodicalId":44135,"journal":{"name":"Annals of Actuarial Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46584743","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: 4
Auto-balanced common shock claim models 自动平衡常见冲击索赔模型
IF 1.7
Annals of Actuarial Science Pub Date : 2021-12-24 DOI: 10.1017/s1748499523000064
G. Taylor, Phuong Vu
{"title":"Auto-balanced common shock claim models","authors":"G. Taylor, Phuong Vu","doi":"10.1017/s1748499523000064","DOIUrl":"https://doi.org/10.1017/s1748499523000064","url":null,"abstract":"\u0000 The paper is concerned with common shock models of claim triangles. These are usually constructed as linear combinations of shock components and idiosyncratic components. Previous literature has discussed the unbalanced property of such models, whereby the shocks may over- or under-contribute to some observations. The literature has also introduced corrections for this. The present paper discusses “auto-balanced” models, in which all shock and idiosyncratic components contribute to observations such that their proportionate contributions are constant from one observation to another. The conditions for auto-balance are found to be simple and applicable to a wide range of model structures. Numerical illustrations are given.","PeriodicalId":44135,"journal":{"name":"Annals of Actuarial Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45618622","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
Pricing insurance policies with offsetting relationship – ERRATUM 具有抵销关系的保险单定价。勘误
IF 1.7
Annals of Actuarial Science Pub Date : 2021-11-19 DOI: 10.1017/s1748499521000221
Hamza Hanbali
{"title":"Pricing insurance policies with offsetting relationship – ERRATUM","authors":"Hamza Hanbali","doi":"10.1017/s1748499521000221","DOIUrl":"https://doi.org/10.1017/s1748499521000221","url":null,"abstract":"DOI: https://doi.org/10.1017/S1748499521000208, Published online by Cambridge University Press, 17 September 2021 The publisher apologises that upon publication of this article the authors name was swapped around, presenting the surname as their first. The authors correct name is Hamza Hanbali. The online version of this article has been updated. Reference Hanbali, H. (2021). Pricing insurance policies with offsetting relationship. Annals of Actuarial Science, 1-27. doi: 10.1017/S1748499521000208","PeriodicalId":44135,"journal":{"name":"Annals of Actuarial Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46075563","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
Joint models for cause-of-death mortality in multiple populations 多人群死亡原因的联合模型
IF 1.7
Annals of Actuarial Science Pub Date : 2021-11-12 DOI: 10.1017/s1748499523000118
Nhan H. Huynh, M. Ludkovski
{"title":"Joint models for cause-of-death mortality in multiple populations","authors":"Nhan H. Huynh, M. Ludkovski","doi":"10.1017/s1748499523000118","DOIUrl":"https://doi.org/10.1017/s1748499523000118","url":null,"abstract":"\u0000 We investigate jointly modelling age–year-specific rates of various causes of death in a multinational setting. We apply multi-output Gaussian processes (MOGPs), a spatial machine learning method, to smooth and extrapolate multiple cause-of-death mortality rates across several countries and both genders. To maintain flexibility and scalability, we investigate MOGPs with Kronecker-structured kernels and latent factors. In particular, we develop a custom multi-level MOGP that leverages the gridded structure of mortality tables to efficiently capture heterogeneity and dependence across different factor inputs. Results are illustrated with datasets from the Human Cause-of-Death Database (HCD). We discuss a case study involving cancer variations in three European nations and a US-based study that considers eight top-level causes and includes comparison to all-cause analysis. Our models provide insights into the commonality of cause-specific mortality trends and demonstrate the opportunities for respective data fusion.","PeriodicalId":44135,"journal":{"name":"Annals of Actuarial Science","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2021-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45603244","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: 2
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