Economics - Research Publications

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    Semicoherent Multipopulation Mortality Modeling: The Impact on Longevity Risk Securitization
    Li, JS-H ; Chan, W-S ; Zhou, R (Wiley, 2017-09)
    Multipopulation mortality models play an important role in longevity risk transfers involving more than one population. Most of the existing multi‐population mortality models are built on the hypothesis of coherence, which assumes that there always exists a force that brings the mortality differential between any two populations back to a constant long‐term equilibrium level. This hypothesis prevents diverging long‐term forecasts, which do not seem to be biologically reasonable. However, the coherence assumption may be perceived by market participants as too strong and is in fact not always supported by empirical observations. In this article, we introduce a new concept called “semicoherence,” which is less stringent in the sense that it permits the mortality trajectories of two related populations to diverge, as long as the divergence does not exceed a specific tolerance corridor, beyond which mean reversion will come into effect. We further propose to produce semicoherent mortality forecasts by using a vector threshold autoregression. The proposed modeling approach is illustrated with mortality data from U.S. and English and Welsh male populations, and is applied to several pricing and hedging scenarios.
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    Modelling Mortality Dependence: An Application of Dynamic Vine Copula
    Zhou, R ; Ji, M (Elsevier, 2021)
    Vine copula, constructed from bivariate copulas, provides great exibility in modelling complex high-dimensional dependence. When applied to multi- population mortality modelling, vine copula yields signi_cant improvement over traditional multivariate copulas. In this paper, we propose to capture time- varying features in mortality dependence with dynamic regular vine (R-vine) copula which is built from bivariate copulas with time-varying dependence pa- rameters. We develop two dependence dynamics for R-vine copulas and illustrate the selection and estimation of dynamic R-vine copulas using mortality data from eight populations. The estimated R-vine copulas using the proposed dependence dynamics are shown to yield better goodness of _t than both static and regime- switching vine copulas. We further demonstrate the simulation of mortality paths using dynamic R-vine copulas and examine the impact of vine copula choice on the assessed e_ectiveness of longevity hedge.
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    The Boundary of the Market for Biosecurity Risk
    Stoneham, G ; Hester, SM ; Li, JS-H ; Zhou, R ; Chaudhry, A (WILEY, 2020-10-30)
    Imported goods create value in destination countries but also create biosecurity risk. Although widely used in other domains of the economy, risk markets have not been created to manage losses that occur when exotic pests and diseases are introduced with traded goods. In this article we show that not all biosecurity risks are insurable. Losses arising from effort needed to detect and respond to exotic pests and diseases that breach national borders appear to be insurable because entry of these threats and consequent response costs, can be regarded as random events. As pests and diseases establish and spread, however, loss of access to export markets and productivity losses display systematic risk and appear to be uninsurable. Other insurability criteria support this definition of the boundary of biosecurity risk markets. We use the Australian biosecurity system as an example, although the framework described in this study will be applicable to biosecurity systems worldwide. We argue that biosecurity risk insurance could be incorporated into the current biosecurity system but would require legislation mandating importers to purchase insurance. Advantages of actuarial pricing of biosecurity risk are: (i) an increase in economic efficiency to the extent that importers respond to the price of biosecurity risk; (ii) financial sustainability would improve because actuarial pricing creates a structural link between funds available for biosecurity activities and risk exposure; and (iii) equity issues evident in the current biosecurity system could be addressed because risk creators (importers) would fund response activities through the purchase of insurance.
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    A General Semi-Markov Model for Coupled Lifetimes
    Ji, M ; Zhou, R (Taylor & Francis (Routledge), 2019-02-15)
    Joint-life annuities with a high last survivor benefit play an important role in the optimal annuity portfolio for a retired couple. The dependence between coupled lifetimes is crucial for valuing joint-life annuities. Existing bivariate modeling of coupled lifetimes is based on outdated data with limited observation periods and does not take into account mortality improvement. In this article, we propose a transparent and dynamic framework for modeling coupled lifetime dependence caused by both marital status and common mortality improvement factors. Dependence due to marital status is captured by a semi-Markov joint life model. Dependence due to common mortality improvement, which represents the correlation between mortality improvement patterns of coupled lives, is incorporated by a two-population mortality improvement model. The proposed model is applied to pricing the longevity risk in last survivor annuities sold in the United States and the United Kingdom.
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    Pricing temperature derivatives with a filtered historical simulation approach
    Zhou, R ; Li, JSH ; Pai, J (Taylor & Francis (Routledge), 2019-10-13)
    In this paper, we propose pricing temperature derivatives using a filtered historical simulation (FHS) approach that amalgamates model-based treatment of volatility and empirical innovation density. The FHS approach implicitly captures the risk premium with the entire risk-neutral model (except the innovation distribution), thereby providing significantly more flexibility than existing methods that use only one designated parameter to capture the risk premium. Additionally, instead of relying on the fitted innovation distribution, the FHS approach uses empirical innovations to capture excess skewness, excess kurtosis, and other non-standard features in the temperature data, all of which are important for the correct pricing of temperature derivatives. We apply the FHS approach to pricing derivatives written on the temperature of Chicago, and demonstrate that this approach yields better in-sample and out-of-sample pricing performance than the constant market price of risk method and the consumption-based method.
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    MODELLING MORTALITY DEPENDENCE WITH REGIME-SWITCHING COPULAS
    Zhou, R (Cambridge University Press (CUP), 2019-05-01)
    We propose a two-regime Markov switching copula to depict the evolution of mortality dependence. One regime represents periods of high dependence and the other regime represents periods of low dependence. Each regime features a regular vine (R-vine) copula that, built on bivariate copulas, provides great flexibility for modelling complex high-dimensional dependence. Our estimated model indicates that the years of recovery from extreme mortality deterioration and the years of health care reform more likely fall into the low regime, while the years in which extreme mortality deteriorating events break out and the peaceful years without major mortality-impacting events more likely fall into the high regime. We use a case study to illustrate how the regime-switching copula can be applied to assess the effectiveness of longevity risk hedge with different beliefs about future mortality dependence evolution incorporated.
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    Drivers of Mortality Dynamics: Identifying Age/Period/Cohort Components of Historical U.S. Mortality Improvements
    Li, JS-H ; Zhou, R ; Liu, Y ; Graziani, G ; Hall, D ; Haid, J ; Peterson, A ; Pinzur, L (Taylor & Francis (Routledge), 2020)
    The goal of this paper is to obtain an Age/Period/Cohort (A/P/C) decomposition of historical U.S. mortality improvement. Two different routes to achieving this goal are considered. In the first route, the desired components are obtained by fitting an A/P/C model directly to historical mortality improvement rates. In the second route, an A/P/C model is estimated to historical crude death rates and the desired components are then obtained by differencing the estimated model parameters. For each route, various possible A/P/C model structures are experimented, and are evaluated on the basis of their robustness to several factors (e.g., changes in the calibration window) and their ability to explain historical changes in mortality improvement. Based on the evaluation results, an A/P/C decomposition for each gender is recommended. The decomposition will be examined in a follow-up project, in which the linkages between the A/P/C components and certain intrinsic factors will be identified.