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GEMAct: a Python package for non-life (re)insurance modeling Annals of Actuarial Science Pub Date : 2024-02-14 Gabriele Pittarello, Edoardo Luini, Manfred Marvin Marchione
This paper introduces gemact, a Python package for actuarial modeling based on the collective risk model. The library supports applications to risk costing and risk transfer, loss aggregation, and loss reserving. We add new probability distributions to those available in scipy, including the (a, b, 0) and (a, b, 1) discrete distributions, copulas of the Archimedean family, the Gaussian, the Student
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The discrete-time arbitrage-free Nelson-Siegel model: a closed-form solution and applications to mixed funds representation Annals of Actuarial Science Pub Date : 2024-02-12 Ramin Eghbalzadeh, Frédéric Godin, Patrice Gaillardetz
A closed-form solution for zero-coupon bonds is obtained for a version of the discrete-time arbitrage-free Nelson-Siegel model. An estimation procedure relying on a Kalman filter is provided. The model is shown to produce adequate fit when applied to historical Canadian spot rate data and to improve distributional predictive performance over benchmarks. An adaptation of the mixed fund return model
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On clustering levels of a hierarchical categorical risk factor Annals of Actuarial Science Pub Date : 2024-02-01 Bavo D.C. Campo, Katrien Antonio
Handling nominal covariates with a large number of categories is challenging for both statistical and machine learning techniques. This problem is further exacerbated when the nominal variable has a hierarchical structure. We commonly rely on methods such as the random effects approach to incorporate these covariates in a predictive model. Nonetheless, in certain situations, even the random effects
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Boosted Poisson regression trees: a guide to the BT package in R Annals of Actuarial Science Pub Date : 2024-01-15 Gireg Willame, Julien Trufin, Michel Denuit
Thanks to its outstanding performances, boosting has rapidly gained wide acceptance among actuaries. Wüthrich and Buser (Data Analytics for Non-Life Insurance Pricing. Lecture notes available at SSRN. http://dx.doi.org/10.2139/ssrn.2870308, 2019) established that boosting can be conducted directly on the response under Poisson deviance loss function and log-link, by adapting the weights at each step
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Epidemic modelling and actuarial applications for pandemic insurance: a case study of Victoria, Australia Annals of Actuarial Science Pub Date : 2024-01-09 Chang Zhai, Ping Chen, Zhuo Jin, Tak Kuen Siu
With the recent outbreak of COVID-19, evaluating the epidemic risk appears to be a pressing issue of global concern and one of the major challenges recently. In the fight against pandemics, the ability to understand, model, and forecast the transmission dynamics of infectious diseases plays a crucial role. This paper provides an overview of foundational compartment models and introduces the Suscep
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Nonparametric intercept regularization for insurance claim frequency regression models Annals of Actuarial Science Pub Date : 2024-01-05 Gee Y. Lee, Himchan Jeong
In a subgroup analysis for an actuarial problem, the goal is for the investigator to classify the policyholders into unique groups, where the claims experience within each group are made as homogenous as possible. In this paper, we illustrate how the alternating direction method of multipliers (ADMM) approach for subgroup analysis can be modified so that it can be more easily incorporated into an insurance
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Modeling and management of cyber risk: a cross-disciplinary review Annals of Actuarial Science Pub Date : 2024-01-04 Rong He, Zhuo Jin, Johnny Siu-Hang Li
This paper provides a review of cyber risk research accomplished in different disciplines, with a primary goal to aid researchers in the field of insurance and actuarial science in identifying potential research gaps as well as leveraging useful models and techniques that have been considered in the literature. We highlight the recent advancements in cyber risk prediction, modeling, management, and
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Error propagation and attribution in simulation-based capital models Annals of Actuarial Science Pub Date : 2023-11-28 Daniel J. Crispin
Calculation of loss scenarios is a fundamental requirement of simulation-based capital models and these are commonly approximated. Within a life insurance setting, a loss scenario may involve an asset-liability optimization. When cashflows and asset values are dependent on only a small number of risk factor components, low-dimensional approximations may be used as inputs into the optimization and resulting
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Capital requirement modeling for market and non-life premium risk in a dynamic insurance portfolio Annals of Actuarial Science Pub Date : 2023-10-31 Stefano Cotticelli, Nino Savelli
For some time now, Solvency II requires that insurance companies calculate minimum capital requirements to face the risk of insolvency, either in accordance with the Standard Formula or using a full or partial Internal Model. An Internal Model must be based on a market-consistent valuation of assets and liabilities at a 1-year time span, where a real-world probabilistic structure is used for the first
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An assessment of model risk in pricing wind derivatives Annals of Actuarial Science Pub Date : 2023-09-21 Giovani Gracianti, Rui Zhou, Johnny Siu-Hang Li, Xueyuan Wu
Wind derivatives are financial instruments designed to mitigate losses caused by adverse wind conditions. With the rapid growth of wind power capacity due to efforts to reduce carbon emissions, the demand for wind derivatives to manage uncertainty in wind power production is expected to increase. However, existing wind derivative literature often assumes normally distributed wind speed, despite the
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Individual life insurance during epidemics Annals of Actuarial Science Pub Date : 2023-09-13 Laura Francis, Mogens Steffensen
The coronavirus pandemic has created a new awareness of epidemics, and insurance companies have been reminded to consider the risk related to infectious diseases. This paper extends the traditional multi-state models to include epidemic effects. The main idea is to specify the transition intensities in a Markov model such that the impact of contagion is explicitly present in the same way as in epidemiological
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An uncertainty-based risk management framework for climate change risk Annals of Actuarial Science Pub Date : 2023-09-05 Rüdiger Kiesel, Gerhard Stahl
Climate risks are systemic risks and may be clustered according to so-called volatilities, uncertainties, complexities, and ambiguities (VUCA) criteria. We analyze climate risk in the VUCA concept and provide a framework that allows to interpret systemic risks as model risk. As climate risks are characterized by deep uncertainties (unknown unknowns), we argue that precautionary and resilient principles
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Lapse risk modeling in insurance: a Bayesian mixture approach Annals of Actuarial Science Pub Date : 2023-09-01 Viviana G. R. Lobo, Thaís C. O. Fonseca, Mariane B. Alves
This paper focuses on modeling surrender time for policyholders in the context of life insurance. In this setup, a large lapse rate at the first months of a contract is often observed, with a decrease in this rate after some months. The modeling of the time to cancelation must account for this specific behavior. Another stylized fact is that policies which are not canceled in the study period are considered
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Detection and treatment of outliers for multivariate robust loss reserving Annals of Actuarial Science Pub Date : 2023-08-24 Benjamin Avanzi, Mark Lavender, Greg Taylor, Bernard Wong
Traditional techniques for calculating outstanding claim liabilities such as the chain-ladder are notoriously at risk of being distorted by outliers in past claims data. Unfortunately, the literature in robust methods of reserving is scant, with notable exceptions such as Verdonck & Debruyne (2011, Insurance: Mathematics and Economics, 48, 85–98) and Verdonck & Van Wouwe (2011, Insurance: Mathematics
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Plant growth stages and weather index insurance design Annals of Actuarial Science Pub Date : 2023-08-03 Jing Zou, Martin Odening, Ostap Okhrin
Given the assumption that weather risks affect crop yields, we designed a weather index insurance product for soybean producers in the US state of Illinois. By separating the entire vegetation cycle into four growth stages, we investigate whether the phase-division procedure contributes to weather–yield loss relation estimation and, hence, to basis risk mitigation. Concretely, supposing stage-variant
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Portfolio management for insurers and pension funds and COVID-19: targeting volatility for equity, balanced, and target-date funds with leverage constraints Annals of Actuarial Science Pub Date : 2023-07-11 Bao Doan, Jonathan J. Reeves, Michael Sherris
Insurers and pension funds face the challenges of historically low-interest rates and high volatility in equity markets, that have been accentuated due to the COVID-19 pandemic. Recent advances in equity portfolio management with a target volatility have been shown to deliver improved on average risk-adjusted return, after transaction costs. This paper studies these targeted volatility portfolios in
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Some comments on “A Hermite spline approach for modelling population mortality” by Tang, Li & Tickle (2022) Annals of Actuarial Science Pub Date : 2023-06-13 Stephen J. Richards
Tang et al. (2022) propose a new class of models for stochastic mortality modelling using Hermite splines. There are four useful features of this class that are worth emphasising. First, for single-sex datasets, this new class of projection models can be fitted as a generalised linear model. Second, these models can automatically extrapolate mortality rates to ages above the maximum age of the data
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Joint models for cause-of-death mortality in multiple populations Annals of Actuarial Science Pub Date : 2023-05-18 Nhan Huynh, Mike Ludkovski
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
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Neural networks for quantile claim amount estimation: a quantile regression approach Annals of Actuarial Science Pub Date : 2023-05-17 Alessandro G. Laporta, Susanna Levantesi, Lea Petrella
In this paper, we discuss the estimation of conditional quantiles of aggregate claim amounts for non-life insurance embedding the problem in a quantile regression framework using the neural network approach. As the first step, we consider the quantile regression neural networks (QRNN) procedure to compute quantiles for the insurance ratemaking framework. As the second step, we propose a new quantile
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Package AdvEMDpy: Algorithmic variations of empirical mode decomposition in Python Annals of Actuarial Science Pub Date : 2023-05-05 Cole van Jaarsveldt, Matthew Ames, Gareth W. Peters, Mike Chantler
This work presents a $\textsf{Python}$ EMD package named AdvEMDpy that is both more flexible and generalises existing empirical mode decomposition (EMD) packages in $\textsf{Python}$, $\textsf{R}$, and $\textsf{MATLAB}$. It is aimed specifically for use by the insurance and financial risk communities, for applications such as return modelling, claims modelling, and life insurance applications with
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Impact of combination methods on extreme precipitation projections Annals of Actuarial Science Pub Date : 2023-04-24 Sébastien Jessup, Mélina Mailhot, Mathieu Pigeon
Climate change is expected to increase the frequency and intensity of extreme weather events. To properly assess the increased economical risk of these events, actuaries can gain in relying on expert models/opinions from multiple different sources, which requires the use of model combination techniques. From non-parametric to Bayesian approaches, different methods rely on varying assumptions potentially
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Auto-balanced common shock claim models Annals of Actuarial Science Pub Date : 2023-04-12 Greg Taylor, Phuong Anh Vu
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
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How do empirical estimators of popular risk measures impact pro-cyclicality? Annals of Actuarial Science Pub Date : 2023-03-29 Marcel Bräutigam, Marie Kratz
Risk measurements are clearly central to risk management, in particular for banks, (re)insurance companies, and investment funds. The question of the appropriateness of risk measures for evaluating the risk of financial institutions has been heavily debated, especially after the financial crisis of 2008/2009. Another concern for financial institutions is the pro-cyclicality of risk measurements. In
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On Bayesian credibility mean for finite mixture distributions Annals of Actuarial Science Pub Date : 2023-03-29 Ehsan Jahanbani, Amir T. Payandeh Najafabadi, Khaled Masoumifard
Consider the problem of determining the Bayesian credibility mean $E(X_{n+1}|X_1,\cdots, X_n),$ whenever the random claims $X_1,\cdots, X_n,$ given parameter vector $\boldsymbol{\Psi},$ are sampled from the K-component mixture family of distributions, whose members are the union of different families of distributions. This article begins by deriving a recursive formula for such a Bayesian credibility
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Benchmarks for the benchmark approach to valuing long-term insurance liabilities: comment on Fergusson & Platen (2023) Annals of Actuarial Science Pub Date : 2023-03-20 Daniel Bauer
This article comments on the paper “Less-expensive long-term annuities linked to mortality, cash and equity” by Kevin Fergusson and Eckard Platen, appearing in this issue of the Annals of Actuarial Science. It adds two perspectives to their thought-provoking contribution. The first is a similarity to some recent work in quantitative finance on “deep hedging” that leverages machine learning models to
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Pseudo-model-free hedging for variable annuities via deep reinforcement learning Annals of Actuarial Science Pub Date : 2023-03-14 Wing Fung Chong, Haoen Cui, Yuxuan Li
This paper proposes a two-phase deep reinforcement learning approach, for hedging variable annuity contracts with both GMMB and GMDB riders, which can address model miscalibration in Black-Scholes financial and constant force of mortality actuarial market environments. In the training phase, an infant reinforcement learning agent interacts with a pre-designed training environment, collects sequential
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An attribution analysis of investment risk sharing in collective defined contribution schemes Annals of Actuarial Science Pub Date : 2023-02-28 Andres Barajas-Paz, Catherine Donnelly
A quantification of the financial implications of the design of a funded, collective defined contribution (CDC) pension scheme is presented and illustrated. It is done through an attribution analysis, which allows the importance of various elements of CDC scheme design to be determined. The model of a CDC scheme analysed is based lightly on the first CDC scheme set to be approved in the UK. In the
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On impact of largest claims reinsurance treaties on the ceding company’s loss reserve Annals of Actuarial Science Pub Date : 2023-02-01 Fatemeh Atatalab, Amir T Payandeh Najafabadi
This article examines the impact of the largest claims reinsurance treaties on loss reserve of the ceding company. The largest claims reinsurance, known as LCR, and ECOMOR reinsurance treaties are considered to be the two most appropriate reinsurance treaties for large or catastrophe claims. Then, it studies the impact of such treaties on loss reserves. Through a simulation study, it shown that, under
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Analysis of option-like fund performance fees in asset management via Monte Carlo actuarial distortion pricing Annals of Actuarial Science Pub Date : 2023-01-09 Gareth W. Peters, Mantana Chudtong, Andrea De Gaetano
A detailed analysis of management and performance fees for asset managers and investment funds is undertaken. While fund fees are considered as a cost of capital for investors, the structuring of such fee mechanisms in a fund can also influence a fund manager’s decisions and investment strategy, thereby also influencing the investment performance of the investors funds. The study undertaken will allow
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Long-term option pricing with a lower reflecting barrier Annals of Actuarial Science Pub Date : 2023-01-05 R. Guy Thomas
This paper considers the pricing of long-term options on assets such as housing, where either government intervention or the economic nature of the asset limits large falls in prices. The observed asset price is modelled by a geometric Brownian motion (“the notional price”) reflected at a lower barrier. The resulting observed price has standard dynamics but with localised intervention at the barrier
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A Hermite spline approach for modelling population mortality Annals of Actuarial Science Pub Date : 2022-10-17 Sixian Tang, Jackie Li, Leonie Tickle
One complication in mortality modelling is capturing the impact of risk factors that contribute to mortality differentials between different populations. Evidence has suggested that mortality differentials tend to diminish over age. Classical methods such as the Gompertz law attempt to capture mortality patterns over age using intercept and slope parameters, possibly causing an unjustified mortality
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Eliminating proxy errors from capital estimates by targeted exact computation Annals of Actuarial Science Pub Date : 2022-10-07 Daniel J. Crispin, Sam M. Kinsley
Determining accurate capital requirements is a central activity across the life insurance industry. This is computationally challenging and often involves the acceptance of proxy errors that directly impact capital requirements. Within simulation-based capital models, where proxies are being used, capital estimates are approximations that contain both statistical and proxy errors. Here, we show how
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A stochastic model for capital requirement assessment for mortality and longevity risk, focusing on idiosyncratic and trend components Annals of Actuarial Science Pub Date : 2022-09-30 Gian Paolo Clemente, Francesco Della Corte, Nino Savelli
This paper provides a stochastic model, consistent with Solvency II and the Delegated Regulation, to quantify the capital requirement for demographic risk. In particular, we present a framework that models idiosyncratic and trend risks exploiting a risk theory approach in which results are obtained analytically. We apply the model to non-participating policies and quantify the Solvency Capital Requirement
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Panjer class revisited: one formula for the distributions of the Panjer (a,b,n) class Annals of Actuarial Science Pub Date : 2022-09-26 Michael Fackler
The loss count distributions whose probabilities ultimately satisfy Panjer’s recursion were classified between 1981 and 2002; they split into six types, which look quite diverse. Yet, the distributions are closely related – we show that their probabilities emerge out of one formula: the binomial series. We propose a parameter change that leads to a unified, practical and intuitive, representation of
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The moments of the time of ruin in Sparre Andersen risk models Annals of Actuarial Science Pub Date : 2022-08-25 David C.M. Dickson
We derive formulae for the moments of the time of ruin in both ordinary and modified Sparre Andersen risk models without specifying either the inter-claim time distribution or the individual claim amount distribution. We illustrate the application of our results in the special case of exponentially distributed claims, as well as for the following ordinary models: the classical risk model, phase-type(2)
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Modelling the burden of long-term care for institutionalised elderly based on care duration and intensity Annals of Actuarial Science Pub Date : 2022-08-15 Martin Bladt, Michel Fuino, Aleksandr Shemendyuk, Joël Wagner
The financing of long-term care and the planning of care capacity are of increasing interest due to demographic changes and the ageing population in many countries. Since many care-intensive conditions begin to manifest at higher ages, a better understanding and assessment of the expected costs, required infrastructure, and number of qualified personnel are essential. To evaluate the overall burden
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Unbiased estimator for the ultimate claim prediction error in the chain-ladder model of Mack Annals of Actuarial Science Pub Date : 2022-08-01 Filippo Siegenthaler
We propose a new estimator for the ultimate prediction uncertainty within the famous Mack’s distribution-free chain-ladder model, which can be proved to be unbiased (conditionally given the first triangle column) under some additional technical assumptions. A peculiar behaviour of the unbiased estimator is given by its possible negativity. This is a drawback which might be worth trading off for the
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Bonus-Malus Scale models: creating artificial past claims history Annals of Actuarial Science Pub Date : 2022-07-29 Jean-Philippe Boucher
In recent papers, Bonus-Malus Scales (BMS) estimated using data have been considered as an alternative to longitudinal data and hierarchical data approaches to model the dependence between different contracts for the same insured. Those papers, however, did not discuss in detail how to construct and understand BMS models, and many of the BMS’s basic properties were not discussed. The first objective
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Less-expensive long-term annuities linked to mortality, cash and equity Annals of Actuarial Science Pub Date : 2022-07-28 Kevin Fergusson, Eckhard Platen
This paper proposes a shift in the valuation and production of long-term annuities, away from the classical risk-neutral methodology towards a methodology using the real-world probability measure. The proposed production method is applied to three examples of annuity products, one having annual payments linked to a mortality index and the savings account and the others having annual payments linked
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COVID-19 accelerated mortality shocks and the impact on life insurance: the Italian situation Annals of Actuarial Science Pub Date : 2022-07-13 Maria Carannante, Valeria D’Amato, Steven Haberman
The Covid-19 pandemic caused an alarming mortality stress. The evidence shows that a significant proportion of people who die from Covid-19 are in a frail state. According to this consideration, we assume that the mortality shocks are related to a group of the individuals with some co-morbidities at Covid-19 diagnosis. In other words, the mortality shocks present a specific characterisation, which
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A multi-parameter-level model for simulating future mortality scenarios with COVID-alike effects Annals of Actuarial Science Pub Date : 2022-05-24 Rui Zhou, Johnny Siu-Hang Li
There has been a growing interest among pension plan sponsors in envisioning how the mortality experience of their active and deferred members may turn out to be if a pandemic similar to the COVID-19 occurs in the future. To address their needs, we propose in this paper a stochastic model for simulating future mortality scenarios with COVID-alike effects. The proposed model encompasses three parameter
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SPLICE: a synthetic paid loss and incurred cost experience simulator Annals of Actuarial Science Pub Date : 2022-05-23 Benjamin Avanzi, Greg Taylor, Melantha Wang
In this paper, we first introduce a simulator of cases estimates of incurred losses called SPLICE (Synthetic Paid Loss and Incurred Cost Experience). In three modules, case estimates are simulated in continuous time, and a record is output for each individual claim. Revisions for the case estimates are also simulated as a sequence over the lifetime of the claim in a number of different situations.
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The impact of mortality shocks on modelling and insurance valuation as exemplified by COVID-19 Annals of Actuarial Science Pub Date : 2022-05-10 Simon Schnürch, Torsten Kleinow, Ralf Korn, Andreas Wagner
The COVID-19 pandemic interrupts the relatively steady trend of improving longevity observed in many countries over the last decades. We claim that this needs to be addressed explicitly in many mortality modelling applications, for example, in the life insurance industry. To support this position, we provide a descriptive analysis of the mortality development of several countries up to and including
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Dynamic importance allocated nested simulation for variable annuity risk measurement Annals of Actuarial Science Pub Date : 2022-02-21 Ou Dang, Mingbin Feng, Mary R. Hardy
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
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Real-time measurement of portfolio mortality levels in the presence of shocks and reporting delays Annals of Actuarial Science Pub Date : 2022-02-21 Stephen J. Richards
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
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Optimal investment strategy for a DC pension fund plan in a finite horizon time: an optimal stochastic control approach Annals of Actuarial Science Pub Date : 2022-02-18 Saman Vahabi, Amir T. Payandeh Najafabadi
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
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On the integration of deterministic opinions into mortality smoothing and forecasting Annals of Actuarial Science Pub Date : 2022-02-09 Viani Biatat Djeundje
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
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Bayesian vine copulas for modelling dependence in data breach losses Annals of Actuarial Science Pub Date : 2022-02-03 Jia Liu, Jackie Li, Kevin Daly
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
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On RVaR-based optimal partial hedging Annals of Actuarial Science Pub Date : 2022-01-25 Alexander Melnikov, Hongxi Wan
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
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AI: Coming of age? Annals of Actuarial Science Pub Date : 2022-01-19 Trevor Maynard, Luca Baldassarre, Yves-Alexandre de Montjoye, Liz McFall, María Óskarsdóttir
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
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Pricing insurance policies with offsetting relationship – ERRATUM Annals of Actuarial Science Pub Date : 2021-11-19 Hamza Hanbali
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Empirical tests for ex post moral hazard in a market for automobile insurance Annals of Actuarial Science Pub Date : 2021-11-03 David Rowell, Son Nghiem, Luke B. Connelly
Ex post moral hazard arises when the insured has an unobservable influence on the size of a loss after its occurrence. In automobile (property) insurance, ex post moral hazard could increase in the scope of the repairs and/or the value of the repairs. Both vehicle owners and auto repairers could gain from increasing the scope of repairs, while auto repairers would gain from an increase in the value
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Multidisciplinary collaboration on discrimination – not just “Nice to Have” Annals of Actuarial Science Pub Date : 2021-11-01 Chris Dolman,Edward (Jed) Frees,Fei Huang
Although much of the discipline of actuarial science has its roots in isolated mathematicians or small collaborative teams toiling to produce fundamental truths, practice today is frequently geared towards large collaborative teams. In some cases, these teams can cross academic disciplines. In our view, whilst certain matters can be effectively researched within isolated disciplines, others are more
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Pricing insurance policies with offsetting relationship Annals of Actuarial Science Pub Date : 2021-09-17 Hamza Hanbali
This paper investigates the benefits of incorporating diversification effects into the pricing process of insurance policies from two different business lines. The paper shows that, for the same risk reduction, insurers pricing policies jointly can have a competitive advantage over those pricing them separately. However, the choice of competitiveness constrains the underwriting flexibility of joint
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Conditional mean risk sharing in the individual model with graphical dependencies Annals of Actuarial Science Pub Date : 2021-06-17 Michel Denuit, Christian Y. Robert
Conditional mean risk sharing appears to be effective to distribute total losses amongst participants within an insurance pool. This paper develops analytical results for this allocation rule in the individual risk model with dependence induced by the respective position within a graph. Precisely, losses are modelled by zero-augmented random variables whose joint occurrence distribution and individual
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Impact of the choice of risk assessment time horizons on defined benefit pension schemes Annals of Actuarial Science Pub Date : 2021-06-09 Douglas Andrews, Stephen Bonnar, Lori J. Curtis, Jaideep S. Oberoi, Aniketh Pittea, Pradip Tapadar
We examine the impact of asset allocation and contribution rates on the risk of defined benefit (DB) pension schemes, using both a run-off and a shorter 3-year time horizon. Using the 3-year horizon, which is typically preferred by regulators, a high bond allocation reduces the spread of the distribution of surplus. However, this result is reversed when examined on a run-off basis. Furthermore, under
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A robust random coefficient regression representation of the chain-ladder method Annals of Actuarial Science Pub Date : 2021-06-09 Ioannis Badounas, Apostolos Bozikas, Georgios Pitselis
It is well known that the presence of outliers can mis-estimate (underestimate or overestimate) the overall reserve in the chain-ladder method, when we consider a linear regression model, based on the assumption that the coefficients are fixed and identical from one observation to another. By relaxing the usual regression assumptions and applying a regression with randomly varying coefficients, we
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Multi-output Gaussian processes for multi-population longevity modelling Annals of Actuarial Science Pub Date : 2021-05-17 Nhan Huynh, Mike Ludkovski
We investigate joint modelling of longevity trends using the spatial statistical framework of Gaussian process (GP) regression. Our analysis is motivated by the Human Mortality Database (HMD) that provides unified raw mortality tables for nearly 40 countries. Yet few stochastic models exist for handling more than two populations at a time. To bridge this gap, we leverage a spatial covariance framework
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Scenario Weights for Importance Measurement (SWIM) – an R package for sensitivity analysis Annals of Actuarial Science Pub Date : 2021-05-12 Silvana M. Pesenti, Alberto Bettini, Pietro Millossovich, Andreas Tsanakas
The Scenario Weights for Importance Measurement (SWIM) package implements a flexible sensitivity analysis framework, based primarily on results and tools developed by Pesenti et al. (2019). SWIM provides a stressed version of a stochastic model, subject to model components (random variables) fulfilling given probabilistic constraints (stresses). Possible stresses can be applied on moments, probabilities
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Statistical features of persistence and long memory in mortality data Annals of Actuarial Science Pub Date : 2021-05-11 Gareth W. Peters, Hongxuan Yan, Jennifer Chan
Understanding core statistical properties and data features in mortality data are fundamental to the development of machine learning methods for demographic and actuarial applications of mortality projection. The study of statistical features in such data forms the basis for classification, regression and forecasting tasks. In particular, the understanding of key statistical structure in such data