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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    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 Existing bivariate modeling of coupled lifetimes is based on outdated data with limited observation periods and does not take into account mortality improvement.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.