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The Stochastic Mortality Modeling and the Pricing of Mortality/longevity Linked Derivatives

The Stochastic Mortality Modeling and the Pricing of Mortality/longevity Linked Derivatives
Author: Shuo-Li Chuang
Publisher:
Total Pages: 316
Release: 2013
Genre:
ISBN:
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The Lee-Carter mortality model provides the very first model for modeling the mortality rate with stochastic time and age mortality dynamics. The model is constructed modeling the mortality rate to incorporate both an age effect and a period effect. The Lee-Carter model provides the fundamental set up currently used in most modern mortality modeling. Various extensions of the Lee-Carter model include either adding an extra term for a cohort effect or imposing a stochastic process for mortality dynamics. Although both of these extensions can provide good estimation results for the mortality rate, applying them for the pricing of the mortality/ longevity linked derivatives is not easy. While the current stochastic mortality models are too complicated to be explained and to be implemented, transforming the cohort effect into a stochastic process for the pricing purpose is very difficult. Furthermore, the cohort effect itself sometimes may not be significant. We propose using a new modified Lee-Carter model with a Normal Inverse Gaussian (NIG) Lévy process along with the Esscher transform for the pricing of mortality/ longevity linked derivatives. The modified Lee-Carter model, which applies the Lee-Carter model on the growth rate of mortality rates rather than the level of iv mortality rates themselves, performs better than the current mortality rate models shown in Mitchell et al (2013). We show that the modified Lee-Carter model also retains a similar stochastic structure to the Lee-Carter model, so it is easy to demonstrate the implication of the model. We proposed the additional NIG Lévy process with Esscher transform assumption that can improve the fit and prediction results by adapting the mortality improvement rate. The resulting mortality rate matches the observed pattern that the mortality rate has been improving due to the advancing development of technology and improvements in the medical care system. The resulting mortality rate is also developed under a martingale measure so it is ready for the direct application of pricing the mortality/longevity linked derivatives, such as q-forward, longevity bond, and mortality catastrophe bond. We also apply our proposed model along with an information theoretic optimization method to construct the pricing procedures for a life settlement. While our proposed model can improve the mortality rate estimation, the application of information theory allows us to incorporate the private health information of a specific policy holder and hence customize the distribution of the death year distribution for the policy holder so as to price the life settlement. The resulting risk premium is close to the practical understanding in the life settlement market.

Stochastic Mortality Modelling

Stochastic Mortality Modelling
Author: Xiaoming Liu
Publisher:
Total Pages: 380
Release: 2008
Genre:
ISBN: 9780494590171
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For life insurance and annuity products whose payoffs depend on the future mortality rates, there is a risk that realized mortality rates will be different from the anticipated rates accounted for in their pricing and reserving calculations. This is termed as mortality risk. Since mortality risk is difficult to diversify and has significant financial impacts on insurance policies and pension plans, it is now a well-accepted fact that stochastic approaches shall be adopted to model the mortality risk and to evaluate the mortality-linked securities.To be more specific, we consider a finite-state Markov process with one absorbing state. This Markov process is related to an underlying aging mechanism and the survival time is viewed as the time until absorption. The resulting distribution for the survival time is a so-called phase-type distribution. This approach is different from the traditional curve fitting mortality models in the sense that the survival probabilities are now linked with an underlying Markov aging process. Markov mathematical and phase-type distribution theories therefore provide us a flexible and tractable framework to model the mortality dynamics. And the time-changed Markov process allows us to incorporate the uncertainties embedded in the future mortality evolution.The proposed model has been applied to price the EIB/BNP Longevity Bonds and other mortality derivatives under the independent assumption of interest rate and mortality rate. A calibrating method for the model is suggested so that it can utilize both the market price information involving the relevant mortality risk and the latest mortality projection. The proposed model has also been fitted to various type of population mortality data for empirical study. The fitting results show that our model can interpret the stylized mortality patterns very well.The objective of this thesis is to propose the use of a time-changed Markov process to describe stochastic mortality dynamics for pricing and risk management purposes. Analytical and empirical properties of this dynamics have been investigated using a matrix-analytic methodology. Applications of the proposed model in the evaluation of fair values for mortality linked securities have also been explored.

Life Settlements and Longevity Structures

Life Settlements and Longevity Structures
Author: Geoff Chaplin
Publisher: John Wiley & Sons
Total Pages: 425
Release: 2009-08-06
Genre: Business & Economics
ISBN: 0470684852
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Recent turbulence in the financial markets has highlighted the need for diversified portfolios with lower correlations between the different investments. Life settlements meet this need, offering investors the prospect of high, stable returns, uncorrelated with the broader financial markets. This book provides readers of all levels of experience with essential information on the process surrounding the acquisition and management of a portfolio of life settlements; the assessment, modelling and mitigation of the associated longevity, interest rate and credit risks; and practical approaches to financing and risk management structures. It begins with the history of life insurance and looks at how the need for new financing sources has led to the growth of the life settlements market in the United States. The authors provide a detailed exploration of the mathematical formulae surrounding the generation of mortality curves, drawing a parallel between the tools deployed in the credit derivatives market and those available to model longevity risk. Structured products and securitisation techniques are introduced and explained, starting with simple vanilla products and models before illustrating some of the investment structures associated with life settlements. Capital market mechanisms available to assist the investor in limiting the risks associated with life settlement portfolios are outlined, as are opportunities to use life settlement portfolios to mitigate the risks of traditional capital markets. The last section of the book covers derivative products, either available now or under consideration, that will reduce or potentially eliminate longevity risks within life settlement portfolios. It then reviews hedging and risk management strategies and considers how to measure the effectiveness of risk mitigation.

Longevity Risk Modeling, Securities Pricing and Other Related Issues

Longevity Risk Modeling, Securities Pricing and Other Related Issues
Author: Yinglu Deng
Publisher:
Total Pages: 216
Release: 2011
Genre:
ISBN:
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This dissertation studies the adverse financial implications of "longevity risk" and "mortality risk", which have attracted the growing attention of insurance companies, annuity providers, pension funds, public policy decision-makers, and investment banks. Securitization of longevity/mortality risk provides insurers and pension funds an effective, low-cost approach to transferring the longevity/mortality risk from their balance sheets to capital markets. The modeling and forecasting of the mortality rate is the key point in pricing mortality-linked securities that facilitates the emergence of liquid markets. First, this dissertation introduces the discrete models proposed in previous literature. The models include: the Lee-Carter Model, the Renshaw Haberman Model, The Currie Model, the Cairns-Blake-Dowd (CBD) Model, the Cox-Lin-Wang (CLW) Model and the Chen-Cox Model. The different models have captured different features of the historical mortality time series and each one has their own advantages. Second, this dissertation introduces a stochastic diffusion model with a double exponential jump diffusion (DEJD) process for mortality time-series and is the first to capture both asymmetric jump features and cohort effect as the underlying reasons for the mortality trends. The DEJD model has the advantage of easy calibration and mathematical tractability. The form of the DEJD model is neat, concise and practical. The DEJD model fits the actual data better than previous stochastic models with or without jumps. To apply the model, the implied risk premium is calculated based on the Swiss Re mortality bond price. The DEJD model is the first to provide a closed-form solution to price the q-forward, which is the standard financial derivative product contingent on the LifeMetrics index for hedging longevity or mortality risk. Finally, the DEJD model is applied in modeling and pricing of life settlement products. A life settlement is a financial transaction in which the owner of a life insurance policy sells an unneeded policy to a third party for more than its cash value and less than its face value. The value of the life settlement product is the expected discounted value of the benefit discounted from the time of death. Since the discount function is convex, it follows by Jensen's Inequality that the expected value of the function of the discounted benefit till random time of death is always greater than the benefit discounted by the expected time of death. So, the pricing method based on only the life expectancy has the negative bias for pricing the life settlement products. I apply the DEJD mortality model using the Whole Life Time Distribution Dynamic Pricing (WLTDDP) method. The WLTDDP method generates a complete life table with the whole distribution of life times instead of using only the expected life time (life expectancy). When a life settlement underwriter's gives an expected life time for the insured, information theory can be used to adjust the DEJD mortality table to obtain a distribution that is consistent with the underwriter projected life expectancy that is as close as possible to the DEJD mortality model. The WLTDDP method, incorporating the underwriter information, provides a more accurate projection and evaluation for the life settlement products. Another advantage of WLTDDP is that it incorporates the effect of dynamic longevity risk changes by using an original life table generated from the DEJD mortality model table.

Modeling and Pricing of Longevity Risk

Modeling and Pricing of Longevity Risk
Author: Roman Siegenthaler
Publisher:
Total Pages:
Release: 2012
Genre:
ISBN:
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In this paper, we have applied the stochastic mortality model of Lee and Carter to Swiss national mortality data of the Federal Statistical Office. By means of the obtained stochastic mortality rates and hypothetical portfolios of pensioners and active insured, we have quantified the longevity risk that Swiss pension funds are exposed to. Subsequently, we have illustrated how pension funds can hedge against longevity risk. To that end, based on the model developed in this paper, we have structured various instruments that facilitate the transfer of longevity risk from a pension fund to a protection seller (e.g. longevity bonds, longevity swaps, buy-outs or longevity options). Finally, we provide a discussion about how a Swiss pension fund may manage the longevity risk that it holds in its book. Based on our research, we conclude that the longevity risk of a portfolio of pensioners is limited. This comes as no surprise, as the remaining average life expectancy of pensioners tends to be rather short. However, model and parameter risks constitute a source of uncertainty.

Mortality Risk Modeling

Mortality Risk Modeling
Author: Samuel H. Cox
Publisher:
Total Pages: 35
Release: 2011
Genre:
ISBN:
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This paper proposes a stochastic mortality model featuring both permanent longevity jump and temporary mortality jump processes. A trend reduction component describes unexpected mortality improvement over an extended period of time. The model also captures the uneven effect of mortality events on different ages and the correlations among them. The model will be useful in analyzing future mortality dependent cash flows of life insurance portfolios, annuity portfolios, and portfolios of mortality derivatives. We show how to apply the model to analyze and price a longevity security.

Market Price of Longevity Risk for a Multi-Cohort Mortality Model with Application to Longevity Bond Option Pricing

Market Price of Longevity Risk for a Multi-Cohort Mortality Model with Application to Longevity Bond Option Pricing
Author: Michael Sherris
Publisher:
Total Pages: 38
Release: 2018
Genre:
ISBN:
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The pricing of longevity-linked securities depends not only on the stochastic uncertainty of the underlying risk factors, but also the attitude of investors towards those factors. In this research, we investigate how to estimate the market risk premium of longevity risk using investable retirement indexes, incorporating uncertain real interest rates using an affine dynamic Nelson-Siegel model. A multi-cohort aggregate, or systematic, continuous time affine mortality model is used where each risk factor is assigned a market price of mortality risk. To calibrate the market price of longevity risk, a common practice is to make use of market prices, such as longevity-linked securities and longevity indices. We use the BlackRock CoRI Retirement Indexes, which provides a daily level of estimated cost of lifetime retirement income for 20 cohorts in the U.S. Although investment in the index directly is not possible, individuals can invest in funds that track the index. For these 20 cohorts, we assume risk premiums for the common factors are the same across cohorts, but the risk premium of the factors for a specific cohort is allowed to take different values for different cohorts. The market prices of longevity risk are then calibrated by matching the risk-neutral model prices with BlackRock CoRI index values. Closed-form expressions and prices for European options on longevity zero-coupon bonds are derived using the model and compared to prices for standard options on zero coupon bonds. The impact of uncertain mortality on long term option prices is quantified and discussed.

Longevity Risk Management

Longevity Risk Management
Author: Kenneth Qian Zhou
Publisher:
Total Pages: 169
Release: 2019
Genre: Financial risk management
ISBN:
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Longevity risk management is becoming increasingly important in the pension and life insurance industries. The unexpected mortality improvements observed in recent decades are posing serious concerns to the financial stability of defined-benefit pension plans and annuity portfolios. It has recently been argued that the overwhelming longevity risk exposures borne by the pension and life insurance industries may be transferred to capital markets through standardized longevity derivatives that are linked to broad-based mortality indexes. To achieve the transfer of risk, two technical issues need to be addressed first: (1) how to model the dynamics of mortality indexes, and (2) how to optimize a longevity hedge using standardized longevity derivatives. The objective of this thesis is to develop sensible solutions to these two questions. In the first part of this thesis, we focus on incorporating stochastic volatility in mortality modeling, introducing the notion of longevity Greeks, and analysing the properties of longevity Greeks and their applications in index-based longevity hedging. In more detail, we derive three important longevity Greeks--delta, gamma and vega--on the basis of an extended version of the Lee-Carter model that incorporates stochastic volatility. We also study the properties of each longevity Greek, and estimate the levels of effectiveness that different longevity Greek hedges can possibly achieve. The results reveal several interesting facts. For example, we found and explained that, other things being equal, the magnitude of the longevity gamma of a q-forward increases with its reference age. As with what have been developed for equity options, these properties allow us to know more about standardized longevity derivatives as a risk mitigation tool. We also found that, in a delta-vega hedge formed by q-forwards, the choice of reference ages does not materially affect hedge effectiveness, but the choice of times-to-maturity does. These facts may aid insurers to better formulate their hedge portfolios, and issuers of mortality-linked securities to determine what security structures are more likely to attract liquidity. We then move onto delta hedging the trend and cohort components of longevity risk under the M7-M5 model. In a recent project commissioned by the Institute and Faculty of Actuaries and the Life and Longevity Markets Association, a two-population mortality model called the M7-M5 model is developed and recommended as an industry standard for the assessment of population basis risk. We develop a longevity delta hedging strategy for use with the M7-M5 model, taking into account of not only period effect uncertainty but also cohort effect uncertainty and population basis risk. To enhance practicality, the hedging strategy is formulated in both static and dynamic settings, and its effectiveness can be evaluated in terms of either variance or 1-year ahead Value-at-Risk (the latter is highly relevant to solvency capital requirements). Three real data illustrations are constructed to demonstrate (1) the impact of population basis risk and cohort effect uncertainty on hedge effectiveness, (3) the benefit of dynamically adjusting a delta longevity hedge, and (3) the relationship between risk premium and hedge effectiveness. The last part of this thesis sets out to obtain a deeper understanding of mortality volatility and its implications on index-based longevity hedging. The volatility of mortality is crucially important to many aspects of index-based longevity hedging, including instrument pricing, hedge calibration, and hedge performance evaluation. We first study the potential asymmetry in mortality volatility by considering a wide range of GARCH-type models that permit the volatility of mortality improvement to respond differently to positive and negative mortality shocks. We then investigate how the asymmetry of mortality volatility may impact index-based longevity hedging solutions by developing an extended longevity Greeks framework, which encompasses longevity Greeks for a wider range of GARCH-type models, an improved version of longevity vega, and a new longevity Greek known as `dynamic delta'. Our theoretical work is complemented by two real-data illustrations, the results of which suggest that the effectiveness of an index-based longevity hedge could be significantly impaired if the asymmetry in mortality volatility is not taken into account when the hedge is calibrated.