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  • VALUATION OF HYBRID FINANCIAL AND ACTUARIAL PRODUCTS IN LIFE INSURANCE BY A NOVEL THREE-STEP METHOD
    ASTIN Bull. (IF 1.236) Pub Date : 2020-08-14
    Griselda Deelstra; Pierre Devolder; Kossi Gnameho; Peter Hieber

    Financial products are priced using risk-neutral expectations justified by hedging portfolios that (as accurate as possible) match the product’s payoff. In insurance, premium calculations are based on a real-world best-estimate value plus a risk premium. The insurance risk premium is typically reduced by pooling of (in the best case) independent contracts. As hybrid life insurance contracts depend

    更新日期:2020-09-22
  • JOINT OPTIMIZATION OF TRANSITION RULES AND THE PREMIUM SCALE IN A BONUS-MALUS SYSTEM
    ASTIN Bull. (IF 1.236) Pub Date : 2020-09-11
    Kolos Csaba Ágoston; Márton Gyetvai

    Bonus-malus systems (BMSs) are widely used in actuarial sciences. These systems are applied by insurance companies to distinguish the policyholders by their risks. The most known application of BMS is in automobile third-party liability insurance. In BMS, there are several classes, and the premium of a policyholder depends on the class he/she is assigned to. The classification of policyholders over

    更新日期:2020-09-22
  • AN EFFECTIVE BIAS-CORRECTED BAGGING METHOD FOR THE VALUATION OF LARGE VARIABLE ANNUITY PORTFOLIOS
    ASTIN Bull. (IF 1.236) Pub Date : 2020-09-08
    Hyukjun Gweon; Shu Li; Rogemar Mamon

    To evaluate a large portfolio of variable annuity (VA) contracts, many insurance companies rely on Monte Carlo simulation, which is computationally intensive. To address this computational challenge, machine learning techniques have been adopted in recent years to estimate the fair market values (FMVs) of a large number of contracts. It is shown that bootstrapped aggregation (bagging), one of the most

    更新日期:2020-09-22
  • EFFICIENT DYNAMIC HEDGING FOR LARGE VARIABLE ANNUITY PORTFOLIOS WITH MULTIPLE UNDERLYING ASSETS
    ASTIN Bull. (IF 1.236) Pub Date : 2020-08-11
    X. Sheldon Lin; Shuai Yang

    A variable annuity (VA) is an equity-linked annuity that provides investment guarantees to its policyholder and its contributions are normally invested in multiple underlying assets (e.g., mutual funds), which exposes VA liability to significant market risks. Hedging the market risks is therefore crucial in risk managing a VA portfolio as the VA guarantees are long-dated liabilities that may span decades

    更新日期:2020-09-22
  • TAXATION OF A GMWB VARIABLE ANNUITY IN A STOCHASTIC INTEREST RATE MODEL
    ASTIN Bull. (IF 1.236) Pub Date : 2020-09-02
    Andrea Molent

    Modeling taxation of Variable Annuities has been frequently neglected, but accounting for it can significantly improve the explanation of the withdrawal dynamics and lead to a better modeling of the financial cost of these insurance products. The importance of including a model for taxation has first been observed by Moenig and Bauer (2016) while considering a Guaranteed Minimum Withdrawal Benefit

    更新日期:2020-09-22
  • RISK MEASURES DERIVED FROM A REGULATOR’S PERSPECTIVE ON THE REGULATORY CAPITAL REQUIREMENTS FOR INSURERS
    ASTIN Bull. (IF 1.236) Pub Date : 2020-07-22
    Jun Cai; Tiantian Mao

    In this study, we propose new risk measures from a regulator’s perspective on the regulatory capital requirements. The proposed risk measures possess many desired properties, including monotonicity, translation-invariance, positive homogeneity, subadditivity, nonnegative loading, and stop-loss order preserving. The new risk measures not only generalize the existing, well-known risk measures in the

    更新日期:2020-09-22
  • LARGE-LOSS BEHAVIOR OF CONDITIONAL MEAN RISK SHARING
    ASTIN Bull. (IF 1.236) Pub Date : 2020-07-13
    Michel Denuit; Christian Y. Robert

    We consider the conditional mean risk allocation for an insurance pool, as defined by Denuit and Dhaene (2012). Precisely, we study the asymptotic behavior of the respective relative contributions of the participants as the total loss of the pool tends to infinity. The numerical illustration in Denuit (2019) suggests that the application of the conditional mean risk sharing rule may produce a linear

    更新日期:2020-07-13
  • TESTING FOR RANDOM EFFECTS IN COMPOUND RISK MODELS VIA BREGMAN DIVERGENCE
    ASTIN Bull. (IF 1.236) Pub Date : 2020-07-02
    Himchan Jeong

    The generalized linear model (GLM) is a statistical model which has been widely used in actuarial practices, especially for insurance ratemaking. Due to the inherent longitudinality of property and casualty insurance claim datasets, there have been some trials of incorporating unobserved heterogeneity of each policyholder from the repeated observations. To achieve this goal, random effects models have

    更新日期:2020-07-02
  • PORTFOLIO INSURANCE STRATEGIES FOR A TARGET ANNUITIZATION FUND
    ASTIN Bull. (IF 1.236) Pub Date : 2020-07-01
    Mengyi Xu; Michael Sherris; Adam W. Shao

    The transition from defined benefit to defined contribution (DC) pension schemes has increased the interest in target annuitization funds that aim to fund a minimum level of retirement income. Prior literature has studied the optimal investment strategies for DC funds that provide minimum guarantees, but far less attention has been given to portfolio insurance strategies for DC pension funds focusing

    更新日期:2020-07-01
  • A STATISTICAL METHODOLOGY FOR ASSESSING THE MAXIMAL STRENGTH OF TAIL DEPENDENCE
    ASTIN Bull. (IF 1.236) Pub Date : 2020-06-29
    Ning Sun; Chen Yang; Ričardas Zitikis

    Several diagonal-based tail dependence indices have been suggested in the literature to quantify tail dependence. They have well-developed statistical inference theories but tend to underestimate tail dependence. For those problems when assessing the maximal strength of dependence is important (e.g., co-movements of financial instruments), the maximal tail dependence index was introduced, but it has

    更新日期:2020-06-29
  • WAVELET-BASED FEATURE EXTRACTION FOR MORTALITY PROJECTION
    ASTIN Bull. (IF 1.236) Pub Date : 2020-06-25
    Donatien Hainaut; Michel Denuit

    Wavelet theory is known to be a powerful tool for compressing and processing time series or images. It consists in projecting a signal on an orthonormal basis of functions that are chosen in order to provide a sparse representation of the data. The first part of this article focuses on smoothing mortality curves by wavelets shrinkage. A chi-square test and a penalized likelihood approach are applied

    更新日期:2020-06-25
  • RISK-BASED CAPITAL FOR VARIABLE ANNUITY UNDER STOCHASTIC INTEREST RATE
    ASTIN Bull. (IF 1.236) Pub Date : 2020-06-25
    JinDong Wang; Wei Xu

    Interest rate is one of the main risks for the liability of the variable annuity (VA) due to its long maturity. However, most existing studies on the risk measures of the VA assume a constant interest rate. In this paper, we propose an efficient two-dimensional willow tree method to compute the liability distribution of the VA with the joint dynamics of the mutual fund and interest rate. The risk measures

    更新日期:2020-06-25
  • DISTORTION RISKMETRICS ON GENERAL SPACES
    ASTIN Bull. (IF 1.236) Pub Date : 2020-06-11
    Qiuqi Wang; Ruodu Wang; Yunran Wei

    The class of distortion riskmetrics is defined through signed Choquet integrals, and it includes many classic risk measures, deviation measures, and other functionals in the literature of finance and actuarial science. We obtain characterization, finiteness, convexity, and continuity results on general model spaces, extending various results in the existing literature on distortion risk measures and

    更新日期:2020-06-11
  • A METHOD FOR CONSTRUCTING AND INTERPRETING SOME WEIGHTED PREMIUM PRINCIPLES
    ASTIN Bull. (IF 1.236) Pub Date : 2020-06-05
    Antonia Castaño-Martínez; Fernando López-Blazquez; Gema Pigueiras; Miguel Á. Sordo

    We present a method for constructing and interpreting weighted premium principles. The method is based on modifying the underlying risk distribution in such a way that the risk-adjusted expected value (or premium) is greater than the expected value of some conveniently chosen function of claims, which defines the insurer’s perception of the risk. Under some assumptions on the function of claims, the

    更新日期:2020-06-05
  • A GENERALISED PROPERTY EXPOSURE RATING FRAMEWORK THAT INCORPORATES SCALE-INDEPENDENT LOSSES AND MAXIMUM POSSIBLE LOSS UNCERTAINTY
    ASTIN Bull. (IF 1.236) Pub Date : 2020-05-18
    Pietro Parodi

    A generalised property exposure rating framework is presented here to address two issues arising in the standard approach to exposure rating, especially in the context of direct insurance and facultative reinsurance (D&F) property pricing: (a) What to do when the main assumption of exposure rating, scalability – that is, that the probability of a given damage ratio does not depend on the maximum possible

    更新日期:2020-05-18
  • OPTIMAL INSURANCE CONTRACTS UNDER DISTORTION RISK MEASURES WITH AMBIGUITY AVERSION
    ASTIN Bull. (IF 1.236) Pub Date : 2020-05-11
    Wenjun Jiang; Marcos Escobar-Anel; Jiandong Ren

    This paper presents analytical representations for an optimal insurance contract under distortion risk measure and in the presence of model uncertainty. We incorporate ambiguity aversion and distortion risk measure through the model of Robert and Therond [(2014) ASTIN Bulletin: The Journal of the IAA, 44(2), 277–302.] as per the framework of Klibanoff et al. [(2005) A smooth model of decision making

    更新日期:2020-05-11
  • AN EM ALGORITHM FOR FITTING A NEW CLASS OF MIXED EXPONENTIAL REGRESSION MODELS WITH VARYING DISPERSION
    ASTIN Bull. (IF 1.236) Pub Date : 2020-05-08
    George Tzougas; Dimitris Karlis

    Regression modelling involving heavy-tailed response distributions, which have heavier tails than the exponential distribution, has become increasingly popular in many insurance settings including non-life insurance. Mixed Exponential models can be considered as a natural choice for the distribution of heavy-tailed claim sizes since their tails are not exponentially bounded. This paper is concerned

    更新日期:2020-05-08
  • OPTIMAL INSURANCE STRATEGIES: A HYBRID DEEP LEARNING MARKOV CHAIN APPROXIMATION APPROACH
    ASTIN Bull. (IF 1.236) Pub Date : 2020-05-06
    Xiang Cheng; Zhuo Jin; Hailiang Yang

    This paper studies deep learning approaches to find optimal reinsurance and dividend strategies for insurance companies. Due to the randomness of the financial ruin time to terminate the control processes, a Markov chain approximation-based iterative deep learning algorithm is developed to study this type of infinite-horizon optimal control problems. The optimal controls are approximated as deep neural

    更新日期:2020-05-06
  • ONE-YEAR PREMIUM RISK AND EMERGENCE PATTERN OF ULTIMATE LOSS BASED ON CONDITIONAL DISTRIBUTION
    ASTIN Bull. (IF 1.236) Pub Date : 2020-05-05
    Łukasz Delong; Marcin Szatkowski

    We study the relation between one-year premium risk and ultimate premium risk. In practice, the one-year risk is sometimes related to the ultimate risk by using a so-called emergence pattern formula which postulates a linear relation between both risks. We define the true emergence pattern of the ultimate loss for the one-year premium risk based on a conditional distribution of the ultimate loss derived

    更新日期:2020-05-05
  • ACTUARIAL APPLICATIONS OF WORD EMBEDDING MODELS
    ASTIN Bull. (IF 1.236) Pub Date : 2019-10-22
    Gee Y Lee; Scott Manski; Tapabrata Maiti

    In insurance analytics, textual descriptions of claims are often discarded, because traditional empirical analyses require numeric descriptor variables. This paper demonstrates how textual data can be easily used in insurance analytics. Using the concept of word similarities, we illustrate how to extract variables from text and incorporate them into claims analyses using standard generalized linear

    更新日期:2020-04-18
  • A NEURAL NETWORK BOOSTED DOUBLE OVERDISPERSED POISSON CLAIMS RESERVING MODEL
    ASTIN Bull. (IF 1.236) Pub Date : 2019-12-17
    Andrea Gabrielli

    We present an actuarial claims reserving technique that takes into account both claim counts and claim amounts. Separate (overdispersed) Poisson models for the claim counts and the claim amounts are combined by a joint embedding into a neural network architecture. As starting point of the neural network calibration, we use exactly these two separate (overdispersed) Poisson models. Such a nested model

    更新日期:2020-04-18
  • ON MARINE LIABILITY PORTFOLIO MODELING
    ASTIN Bull. (IF 1.236) Pub Date : 2019-12-13
    William Guevara-Alarcón; Hansjörg Albrecher; Parvez Chowdhury

    Marine is the oldest type of insurance coverage. Nevertheless, unlike cargo and hull covers, marine liability is a rather young line of business with claims that can have very heavy and long tails. For reinsurers, the accumulation of losses from an event insured by various Protection and Indemnity clubs is an additional source for very large claims in the portfolio. In this paper, we first describe

    更新日期:2020-04-18
  • ON THE OPTIMAL COMBINATION OF ANNUITIES AND TONTINES
    ASTIN Bull. (IF 1.236) Pub Date : 2020-01-31
    An Chen; Manuel Rach; Thorsten Sehner

    Tontines, retirement products constructed in such a way that the longevity risk is shared in a pool of policyholders, have recently gained vast attention from researchers and practitioners. Typically, these products are cheaper than annuities, but do not provide stable payments to policyholders. This raises the question whether, from the policyholders' viewpoint, the advantages of annuities and tontines

    更新日期:2020-04-18
  • THE EFFECT OF THE ASSUMED INTEREST RATE AND SMOOTHING ON VARIABLE ANNUITIES
    ASTIN Bull. (IF 1.236) Pub Date : 2019-10-31
    Anne G. Balter; Bas J. M. Werker

    In this paper, we consider the risk–return trade-off for variable annuities in a Black–Scholes setting. Our analysis is based on a novel explicit allocation of initial wealth over the payments at various horizons. We investigate the relationship between the optimal consumption problem and the design of variable annuities by deriving the optimal so-called assumed interest rate for an investor with constant

    更新日期:2020-04-18
  • NATURAL HEDGES WITH IMMUNIZATION STRATEGIES OF MORTALITY AND INTEREST RATES
    ASTIN Bull. (IF 1.236) Pub Date : 2020-01-03
    Tzuling Lin; Cary Chi-liang Tsai

    In this paper, we first derive closed-form formulas for mortality-interest durations and convexities of the prices of life insurance and annuity products with respect to an instantaneously proportional change and an instantaneously parallel movement, respectively, in μ* (the force of mortality-interest), the addition of μ (the force of mortality) and δ (the force of interest). We then build several

    更新日期:2020-04-18
  • REACHING A BEQUEST GOAL WITH LIFE INSURANCE: AMBIGUITY ABOUT THE RISKY ASSET'S DRIFT AND MORTALITY'S HAZARD RATE
    ASTIN Bull. (IF 1.236) Pub Date : 2019-12-05
    Xiaoqing Liang; Virginia R. Young

    We determine the optimal robust strategy of an individual who seeks to maximize the (penalized) probability of reaching a bequest goal when she is uncertain about the drift of the risky asset and her hazard rate of mortality. We assume the individual can invest in a Black–Scholes market. We solve two optimization problems with ambiguity. The first is to maximize the penalized probability of reaching

    更新日期:2020-04-18
  • MULTIVARIATE LONG-MEMORY COHORT MORTALITY MODELS
    ASTIN Bull. (IF 1.236) Pub Date : 2019-12-23
    Hongxuan Yan; Gareth W. Peters; Jennifer S.K. Chan

    The existence of long memory in mortality data improves the understandings of features of mortality data and provides a new approach for establishing mortality models. The findings of long-memory phenomena in mortality data motivate us to develop new mortality models by extending the Lee–Carter (LC) model to death counts and incorporating long-memory model structure. Furthermore, there are no identification

    更新日期:2020-04-18
  • MULTIVARIATE GEOMETRIC TAIL- AND RANGE-VALUE-AT-RISK
    ASTIN Bull. (IF 1.236) Pub Date : 2019-10-21
    Klaus Herrmann; Marius Hofert; Mélina Mailhot

    A generalization of range-value-at-risk (RVaR) and tail-value-at-risk (TVaR) for d-dimensional distribution functions is introduced. Properties of these new risk measures are studied and illustrated. We provide special cases, applications and a comparison with traditional univariate and multivariate versions of the TVaR and RVaR.

    更新日期:2020-04-18
  • BILATERAL RISK SHARING WITH HETEROGENEOUS BELIEFS AND EXPOSURE CONSTRAINTS
    ASTIN Bull. (IF 1.236) Pub Date : 2020-01-07
    Tim J. Boonen; Mario Ghossoub

    This paper studies bilateral risk sharing under no aggregate uncertainty, where one agent has Expected-Utility preferences and the other agent has Rank-dependent utility preferences with a general probability distortion function. We impose exogenous constraints on the risk exposure for both agents, and we allow for any type or level of belief heterogeneity. We show that Pareto-optimal risk-sharing

    更新日期:2020-04-18
  • ASB volume 50 issue 1 Cover and Front matter
    ASTIN Bull. (IF 1.236) Pub Date : 2020-01-31

    None

    更新日期:2020-04-18
  • ASB volume 50 issue 1 Cover and Back matter
    ASTIN Bull. (IF 1.236) Pub Date : 2020-01-31

    None

    更新日期:2020-04-18
  • A NEW INFERENCE STRATEGY FOR GENERAL POPULATION MORTALITY TABLES
    ASTIN Bull. (IF 1.236) Pub Date : 2020-04-17
    Alexandre Boumezoued; Marc Hoffmann; Paulien Jeunesse

    We propose a new inference strategy for general population mortality tables based on annual population and death estimates, completed by monthly birth counts. We rely on a deterministic population dynamics model and establish formulas that link the death rates to be estimated with the observables at hand. The inference algorithm takes the form of a recursive and implicit scheme for computing death

    更新日期:2020-04-17
  • OPTIMAL ASSET ALLOCATION FOR DC PENSION DECUMULATION WITH A VARIABLE SPENDING RULE
    ASTIN Bull. (IF 1.236) Pub Date : 2020-04-15
    Peter A. Forsyth; Kenneth R. Vetzal; Graham Westmacott

    We determine the optimal asset allocation to bonds and stocks using an annually recalculated virtual annuity (ARVA) spending rule for DC pension plan decumulation. Our objective function minimizes downside withdrawal variability for a given fixed value of total expected withdrawals. The optimal asset allocation is found using optimal stochastic control methods. We formulate the strategy as a solution

    更新日期:2020-04-15
  • LESS-EXPENSIVE VALUATION AND RESERVING OF LONG-DATED VARIABLE ANNUITIES WHEN INTEREST RATES AND MORTALITY RATES ARE STOCHASTIC
    ASTIN Bull. (IF 1.236) Pub Date : 2020-04-13
    Kevin Fergusson

    Variable annuities are products offered by pension funds and life offices that provide periodic future payments to the investor and often have ancillary benefits that guarantee survival benefits or sums insured on death. This paper extends the benchmark approach to value and hedge long-dated variable annuities using a combination of cash, bonds and equities under a variety of market models, allowing

    更新日期:2020-04-13
  • WEIGHTED COMONOTONIC RISK SHARING UNDER HETEROGENEOUS BELIEFS
    ASTIN Bull. (IF 1.236) Pub Date : 2020-03-12
    Haiyan Liu

    We study a weighted comonotonic risk-sharing problem among multiple agents with distortion risk measures under heterogeneous beliefs. The explicit forms of optimal allocations are obtained, which are Pareto-optimal. A necessary and sufficient condition is given to ensure the uniqueness of the optimal allocation, and sufficient conditions are given to obtain an optimal allocation of the form of excess

    更新日期:2020-03-12
  • FORECASTING MULTIPLE FUNCTIONAL TIME SERIES IN A GROUP STRUCTURE: AN APPLICATION TO MORTALITY
    ASTIN Bull. (IF 1.236) Pub Date : 2020-02-18
    Han Lin Shang; Steven Haberman

    When modelling subnational mortality rates, we should consider three features: (1) how to incorporate any possible correlation among subpopulations to potentially improve forecast accuracy through multi-population joint modelling; (2) how to reconcile subnational mortality forecasts so that they aggregate adequately across various levels of a group structure; (3) among the forecast reconciliation methods

    更新日期:2020-02-18
  • POISSON MODELS WITH DYNAMIC RANDOM EFFECTS AND NONNEGATIVE CREDIBILITIES PER PERIOD
    ASTIN Bull. (IF 1.236) Pub Date : 2020-02-13
    Jean Pinquet

    This paper provides a toolbox for the credibility analysis of frequency risks, with allowance for the seniority of claims and of risk exposure. We use Poisson models with dynamic and second-order stationary random effects that ensure nonnegative credibilities per period. We specify classes of autocovariance functions that are compatible with positive random effects and that entail nonnegative credibilities

    更新日期:2020-02-13
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