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The purpose of this paper is to develop a model to hedge annuity portfolios against increases in life expectancy. Across the globe, and in the industrial nations in particular, people have seen an unprecedented increase in their life expectancy over the past decades. The benefits of this apply to the individual, but the dangers apply to annuity providers. Insurance companies often possess no effective tools to address the longevity risk inherent in their annuity portfolio. Securitization can serve as a substitute for classic reinsurance, as it also transfers risk to third parties.

This paper extends on methods insurer's can use to hedge their annuity portfolio against longevity risk with the help of annuity securitization. Future mortality rates with the Lee-Carter-model and use the Wang-transformation to incorporate insurance risk are forecasted. Based on the percentile tranching method, where individual tranches are aligned to Standard & Poor's ratings, we price an inverse survivor bond. This bond offers fix coupon payments to investors, while the principal payments are at risk and depend on the survival rate within the underlying portfolio.

The contribution to the academic literature is threefold. On the theoretical side, building on the work of Kim and Choi (2011), we adapt their pricing model to the current market situation. Putting the principal at risk instead of the coupon payments, the insurer is supplied with sufficient capital to cover additional costs due to longevity. On the empirical side, the method for the German market is specified. Inserting specific country data into the model, price sensitivities of the presented securitization model are analyzed. Finally, in a case study, the procedure to the annuity portfolio of a large German life insurer is applied and the price of hedging longevity risk is calculated.

To illustrate the implication of this bond structure, several sensitivity tests were conducted before applying the pricing model to the retail sample annuity portfolio from a leading German life insurer. The securitization structure was applied to calculate the securitization prices for a sample portfolio from a large life insurance company.

The findings contribute to the current discussion about how insurers can face longevity risk within their annuity portfolios. The fact that the rating structure has such a severe impact on the overall hedging costs for the insurer implies that companies that are willing to undergo an annuity securitization should consider their deal structure very carefully. In addition, we have pointed out that in imperfect markets, the retention of the equity tranche by the originator might be advantageous. Nevertheless, one has to bear in mind that by this behavior, the insurer is able to reduce the overall default risk in his balance sheet by securitizing a life insurance portfolio; however, the fraction of first loss pieces from defaults increases more than proportionally. The insurer has to take care to not be left with large, unwanted remaining risk positions in his books.

In this paper, we extend on methods insurer's can use to hedge their annuity portfolio against longevity risk with the help of annuity securitization. To do so, we take the perspective of the issuing insurance company and calculate the costs of hedging in a four-step process. On the theoretical side, building on the work of Kim and Choi (2011), we adapt their pricing model to the current market situation. On the empirical side, we specify the method for the German market. Inserting specific country data into the model, price sensitivities of the presented securitization model are analyzed.

The demographic risk is the risk due to the uncertainty in the demographic scenario assumptions by which life insurance products are designed and valued. The uncertainty lies both in the accidental (insurance risk) and systematic (longevity risk) deviations of the number of deaths from the value anticipated for it. This last component gives rise to the risk due to the randomness in the choice of the survival model for valuations (model risk or projection risk). If the insurance risk component can be assumed negligible for well‐diversified portfolios, as in the case of pension annuities, longevity risk is crucial in the actuarial valuations. The question is particularly decisive in contexts in which the longevity phenomenon of the population is strong and pension annuity portfolios constitute a meaningful slice of the financial market – both typical elements of Western economies. The paper aims to focus on the solvency appraisal for a portfolio of life annuities, deepening the impact of the demographic risk according to suitable risk indexes apt to describe its evolution in time.

The financial quantity proposed for representing the economic wealth of the life insurance company is the stochastic surplus, and the paper analyses the impact on it of different demographic assumptions by means of risk indicators as the projection risk index, the quantile surplus valuation and the ruin probability. By means of the proposed models, the longevity risk is mainly taken into account in a stochastic scenario for the financial risk component, in order to consider their interactions, too. In order to furnish practical details significant in the portfolio risk management, several numerical applications clarify the practical meaning of the models in the solvency context.

This paper studies the impact on the portfolio surplus of the systematic demographic risk, taking into account their interaction with the financial risk sources. In this order of ideas, the internal risk profile of a life annuity portfolio is deeply investigated by means of suitable risk indexes: in a solvency analysis perspective, some possible scenarios for the evolution of death rates (generated by different survival models) are considered and this paper evaluates the impact on the portfolio surplus caused by different choices of the demographic model. The first index is deduced by a variance decomposition formula, the other ones involve the conditional quantile calculus and the ruin probability. Such indexes constitute benchmarks, whose conjoined use provides useful information to the meeting of the solvency requirements.

With respect to the recent actuarial literature, in which the most important contribution on the surplus analysis has been given by Lisenko et al. – where the analysis focuses on the financial aspect applied to portfolios of temporary and endowment contracts – the paper considers life annuity portfolios, taking into account the effect of the systematic demographic risk and its interactions with the financial risk components.

The improvements of longevity are intensifying the need for capital markets to be used to manage and transfer the risk through longevity-linked securities. Nevertheless, the difference between the reference population of the hedging instrument and the population of members of a pension plan, or the beneficiaries of an annuity portfolio, determines a significant heterogeneity causing the so-called basis risk. In particular, it is shown that if insurers use financial instruments based on national indices to hedge longevity risk, this hedge can become imperfect. For this reason, it is fundamental to arrange a model allowing to quantify the basis risk for minimising it through a correct calibration of the hedging instrument.

The paper provides a framework for measuring the basis risk impact on the. To this aim, we propose a model that measures the population basis risk involved in a longevity hedge, in the functional data model setting. hedging strategies.

The innovative contribution of the paper occurs in two key points: the modelling of mortality and the hedging strategy. Regarding the first point, the paper proposes a functional demographic model framework (FDMF) for capturing the basis risk. The FDMF model generally designed for single population combines functional data analysis, nonparametric smoothing and robust statistics. It allows to capture the variability of the mortality trend, by separating out the effects of several orthogonal components. The novelty is to set the FDMF for modelling the mortality of the two populations, the hedging and the exposed one. Regarding the second point, the basic idea is to calibrate the hedging strategy determining a suitable mixture of q-forwards linked to mortality rates to maximise the degree of longevity risk reduction. This calibration is based on the key q-duration intended as a measure allowing to estimate the price sensitivity of the annuity portfolio to the changes in the underlying mortality curve.

The novelty lies in linking the shift in the mortality curve to the standard deviation of the historical mortality rates of the exposed population. This choice has been determined by the observation that the shock in a mortality rate is age dependent. The main advantage of the presented framework is its strong versatility, being the functional demographic setting a generalisation of the Lee-Carter model commonly used in mortality forecasting, it allows to adapt to different demographic scenarios. In the next developments, we set out to compare other common factor models to assess the most effective longevity hedge. Moreover, the parsimony for considering together two trajectories of the populations under consideration and the convergence of long-term forecast are important aspects of our approach.

The determination of the capital requirements represents the first Pillar of Solvency II. The main purpose of the new solvency regulation is to obtain more realistic modelling and assessment of the different risks insurance companies are exposed to in a balance‐sheet perspective. In this context, the Solvency Capital Requirement (SCR) standard calculation is based on a modular approach, where the overall risk is split into several modules and submodules. In Solvency II, standard formula longevity risk is explicitly considered. The purpose of this paper is to look at the backtesting approach for measuring the consistency of SCR calculations for life insurance policies.

A multiperiod approach is suggested for correctly calculating the SCR in a risk management perspective, in the sense that the amount of capital necessary to meet company future obligations year by year until the contract will be in force has to be assessed. The backtesting approach for measuring the consistency of SCR calculations for life insurance policies represents the main contribution of the research. In fact this kind of model performance is generally specified in the VaR validation analysis. In this paper, this approach is considered for testing the ex post performance of SCR calculation methodology.

The backtesting framework is able to measure, from time to time, if the insurer has allocated more or less capital to support his in‐force business, with adverse effects on free reserves and profitability or solvency.

The paper shows that the forecasting performance is an important aspect to assess the effectiveness of the model, a poor performance corresponding to a biased allocation of capital.

The backtesting approach for measuring the consistency of SCR calculations for life insurance policies represents the main contribution of the research. In fact this kind of model performance is generally specified in the VaR validation analysis. Recently, Dowd et al. have proposed it for verifying the goodness of mortality models and now, in this paper, this approach is considered for testing the ex post performance of SCR calculation methodology.

Systematic mortality risk, i.e. the risk of unexpected changes in mortality and survival rates, can substantially impact a life insurers' risk and solvency situation. By using the “natural hedge” between life insurance and annuities, insurance companies have an effective tool for reducing their net‐exposure. The purpose of this paper is to analyze this risk management tool and to quantify its effectiveness in hedging against changes in mortality with respect to default risk measures.

To achieve this goal, the paper models the insurance company as a whole and takes into account the interaction between assets and liabilities. Systematic mortality risk is considered in two ways. First, systematic mortality risk is modeled using scenario analyses and, second, empirically observed changes in mortality rates for the last 10‐15 years are used.

The paper demonstrates that the consideration of both the asset and liability side is vital to obtain deeper insight into the impact of natural hedging on an insurer's risk situation and shows how to reach a desired safety level while simultaneously immunizing the portfolio against changes in mortality rates.

The paper contributes to the literature by considering the insurance company as a whole in a multi‐period setting and taking into account both, assets and liabilities, as well as their interaction. Furthermore, the paper shows how to obtain a desired safety level while simultaneously immunizing a portfolio against changes in default risk.

The purpose of this paper is to study the risk of misspecifying solvency models for insurance companies.

Based on a basic solvency model, the authors examine the sensitivity of different risk measures with respect to model misspecification. An analysis considers the effects of introducing stochastic jumps and linear, as well as non‐linear dependencies into the basic setting on the solvency capital requirements, shortfall probability and expected policyholder deficit. Additionally, the authors take a regulatory view and consider the degree to which the deviations in risk measures, due to the different model specifications, can be diminished by means of requiring interim financial reports.

The simulation results suggest that the sensitivity of solvency capital as a risk measure – as it is in regulatory practice – underestimates the actual misspecification risk that policyholders are exposed to. It is also found that semi‐annual mandatory interim reports can already reduce the model uncertainty faced by a regulator, significantly. This has important implications for the design of risk‐based capital standards and the implementation of internal solvency models.

The results from the Monte Carlo simulation show that changes in the specification of a solvency model have a much greater impact on shortfall probabilities and expected policyholder deficits than they have on capital requirements. The shortfall risk measures react much more sensitively to small changes in the model assumptions, than the capital requirements. This leads us to the conclusion that regulators should not solely rely on capital requirements to monitor the solvency situation of an insurer, but should additionally consider shortfall risk measures. More precisely, an analysis of model risk focusing on the sensitivity of capital requirements will typically underestimate the relevant risk of model misspecification from a policyholder's perspective. Finally, the simulation results suggest that mandatory interim reports on the solvency and financial situation of an insurance company are a powerful tool in order to reduce the model uncertainty faced by regulators.

The life insurance industry has been exposed to high levels of longevity risk born from the mismatch between realized mortality trends and anticipated forecast. Annuity providers are exposed to extended periods of annuity payments. There are no immediate instruments in the market to counter the risk directly. This paper aims to develop appropriate instruments for hedging longevity risk and providing an insight on how existing products can be tailor-made to effectively immunize portfolios consisting of life insurance using a cointegration vector error correction model with regime-switching (RS-VECM), which enables both short-term fluctuations, through the autoregressive structure [AR(1)] and long-run equilibria using a cointegration relationship. The authors also develop synthetic products that can be used to effectively hedge longevity risk faced by life insurance and annuity providers who actively hold portfolios of life insurance products. Models are derived using South African data. The authors also derive closed-form expressions for hedge ratios associated with synthetic products written on life insurance contracts as this will provide a natural way of immunizing the associated portfolios. The authors further show how to address the current liquidity challenges in the longevity market by devising longevity swaps and develop pricing and hedging algorithms for longevity-linked securities. The use of a cointergrating relationship improves the model fitting process, as all the VECMs and RS-VECMs yield greater criteria values than their vector autoregressive model (VAR) and regime-switching vector autoregressive model (RS-VAR) counterpart’s, even though there are accruing parameters involved.

The market model adopted from Ngai and Sherris (2011) is a cointegration RS-VECM for this enables both short-term fluctuations, through the AR(1) and long-run equilibria using a cointegration relationship (Johansen, 1988, 1995a, 1995b), with a heteroskedasticity through the use of regime-switching. The RS-VECM is seen to have the best fit for Australian data under various model selection criteria by Sherris and Zhang (2009). Harris (1997) (Sajjad et al., 2008) also fits a regime-switching VAR model using Australian (UK and US) data to four key macroeconomic variables (market stock indices), showing that regime-switching is a significant improvement over autoregressive conditional heteroscedasticity (ARCH) and generalised autoregressive conditional heteroscedasticity (GARCH) processes in the account for volatility, evidence similar to that of Sherris and Zhang (2009) in the case of Exponential Regressive Conditional Heteroscedasticity (ERCH). Ngai and Sherris (2011) and Sherris and Zhang (2009) also fit a VAR model to Australian data with simultaneous regime-switching across many economic and financial series.

The authors develop a longevity swap using nighttime data instead of usual income measures as it yields statistically accurate results. The authors also develop longevity derivatives and annuities including variable annuities with guaranteed lifetime withdrawal benefit (GLWB) and inflation-indexed annuities. Improved market and mortality models are developed and estimated using South African data to model the underlying risks. Macroeconomic variables dependence is modeled using a cointegrating VECM as used in Ngai and Sherris (2011), which enables both short-run dependence and long-run equilibrium. Longevity swaps provide protection against longevity risk and benefit the most from hedging longevity risk. Longevity bonds are also effective as a hedging instrument in life annuities. The cost of hedging, as reflected in the price of longevity risk, has a statistically significant effect on the effectiveness of hedging options.

This study relied on secondary data partly reported by independent institutions and the government, which may be biased because of smoothening, interpolation or extrapolation processes.

An examination of South Africa’s mortality based on industry experience in comparison to population mortality would demand confirmation of the analysis in this paper based on Belgian data as well as other less developed economies. This study shows that to provide inflation-indexed life annuities, there is a need for an active market for hedging inflation in South Africa. This would demand the South African Government through the help of Actuarial Society of South Africa (ASSA) to issue inflation-indexed securities which will help annuities and insurance providers immunize their portfolios from longevity risk.

In South Africa, there is an infant market for inflation hedging and no market for longevity swaps. The effect of not being able to hedge inflation is guaranteed, and longevity swaps in annuity products is revealed to be useful and significant, particularly using developing or emerging economies as a laboratory. This study has shown that government issuance or allowing issuance, of longevity swaps, can enable insurers to manage longevity risk. If the South African Government, through ASSA, is to develop a projected mortality reference index for South Africa, this would allow the development of mortality-linked securities and longevity swaps which ultimately maximize the social welfare of life assurance policy holders.

The paper proposes longevity swaps and static hedging because they are simple, less costly and practical with feasible applications to the South African market, an economy of over 50 million people. As the market for MLS develops further, dynamic hedging should become possible.

Deferred annuities, which offer longevity insurance with relatively low premiums, are a potential payout option in defined contribution (DC) pension plans in Japan. This study aims to measure individual preferences for these annuities.

This study conducts stated choice experiments using an original internet survey. This methodology provides a decision-making scenario similar to that faced by individuals when making real retirement saving decisions. Subjective valuations of deferred, immediate and term annuities are compared.

This study finds that male individuals have an insignificant preference for deferred annuities – the benefits of which begin at an advanced age. On average, deferred annuities are considered a gamble, betting against life and individuals who are married and have higher financial assets tend to value them less.

While previous studies, based on theory and simulations, have found that deferred annuities should be included in individual retirement assets, this study examines annuity preferences from the demand side (i.e. DC plan participants) –an approach that has not been addressed in the literature.

The purpose of this paper is to explain how the current “crisis” in the UK pension system arose. I argue that it is a result of a combination of changes in government policy and basic instabilities always inherent in the financial system. Policy changes increased the vulnerability of the pension system to those instabilities. The background to these changes and also the frame of reference in terms of which the “crisis” itself is now phrased is broadly neoliberal. Its theoretical roots are in ideas of the efficiency of free markets. Its policy roots are expressed in a series of similar neoliberal policy tendencies in other capitalist states. I further argue that neoliberal solutions to the pension crisis simply offer more of the very matters that created the problems in the first place. Moreover, the very terms of debate, based in markets, financialisation of saving and individualisation of risk, disguise a more basic debate about providing a living retirement income for all. This is a debate that New Labour is simply not prepared to constructively engage with in any concrete fashion.

The purpose of this paper is to highlight not only the pre‐closing, but also the continuing due diligence required of all parties in private placement life insurance or annuities invested in hedge funds.

This technical paper describes the due diligence process for these high‐end offerings, illustrating key concerns through case studies.

Recent events have caused the advantages, disadvantages and timing issues to crystallize, together with what issues require pre‐closing and post‐closing due diligence.

This paper provides timely guidance from experts approaching the issues from multiple disciplines – law, accounting, and financial analysis – to yield a comprehensive analysis of the position of all parties to the transaction.