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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.

The purpose of this paper is to propose that simple measures of linear association are unable to capture accurately the dependence between the survival of hedge funds and funds of funds, respectively. The paper then aims to advocate the use of copulas to model the joint survival of hedge funds and funds of funds managed by the same manager.

The paper uses both a one‐step approach where the margins and the copula parameters are estimated jointly, and a two‐step approach where the margins are fitted first and the copula parameter is estimated thereafter given the fixed margins. The margins are estimated non‐parametrically, semi‐parametrically, and parametrically, respectively.

First, the paper finds that Kendall's tau and Spearman's rho are anywhere between three and eight times larger than the corresponding sample based measures when various families of copulas are employed. Second, additional tests show that the two survival functions are strongly dependent, with the degree of nonlinear association increasing in the lower left quadrant.

This is the first paper to use copulas to model the joint survival of hedge funds and funds of funds. The results highlight the asymmetric dependence between hedge funds and funds of funds, which has implications for risk management practices.

The purpose of this paper is to find the impact of food price volatility on child health and education attainment in urban areas of Pakistan. This research also compares the two variables among the two time periods: the period of low volatile food prices (2014‒2015) and the period of high volatile food prices (2013‒2014). The rate of child immunization and the rate of child school attendance are used as proxies for child health and child education, respectively.

This study employs propensity score matching (PSM) technique introduced by Rosenbaum and Rubin (1983), to overcome the selection bias problem in the observational studies.

The closing part of the paper concludes that both the rate of child immunization and the rate of child school attendance are significantly poorer for the households of Pakistan in the control period (of high food price volatility) as compared to the treated period (of low food price volatility). After controlling the problem of selection bias through PSM technique, it is found that there is a further increase in the rate of child immunization and the rate of child school attendance. It proves that the data were biased before applying the matching technique.

This study lengthens the literature by identifying the impact of food price volatility on child health and education of urban households of Pakistan, using high frequency data of PSLM/HIES, with the help of semi-parametric technique of matching. This type of micro-level research has not been conducted (nationally or internationally) so far; therefore, it would possibly open a sphere for policy makers to implement the suitable policies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2019-0275.

The purpose of this paper is to decompose the effects of democracy and risk of expropriation on economic volatility.

The authors follow Acemouglu et al. and use settler mortality in former colonies in the seventeenth, eighteenth and nineteenth centuries as an instrument of “risk of expropriation,” in addition to a democracy index to capture institutional effects on economic stability.

The authors present empirical evidence that the economic performance of more centralized former European colonies is not more volatile than that of democratic ones, once the exogenous variation of expropriation risk across countries is included in the model

The paper investigates the role of a spectrum of different institutions on economic stability. In this sense, the paper contributes to the literature analyzing the effect of property‐rights protection, as measured by a risk‐of‐expropriation index, on the relation between democracy and economic stability.

The purpose of this study is to empirically examine the impact of the novel coronavirus (COVID-19) on Egyptian stock market returns and volatility between July 2018 and June 2021.

This study utilizes a generalized autoregressive conditional heteroskedasticity (GARCH) model to examine the impact of COVID-19 on two basic stock market indices (EGX30 and EGX100). In addition, the heteroskedasticity corrected model (HCM) was employed to differentiate between the effects of each subsequent wave of the pandemic.

The results of the GARCH model revealed that all COVID-19 variables have a significant impact on the daily returns of EGX100, but an insignificant impact on that of EGX30. The mortality rate and transmission speed increased the market volatility of EGX30 daily returns. The results of the HCM confirmed that the Egyptian stock market reacted more nervously to the first wave than to the second, while the impact was not detected in the third wave.

This study provides useful insights to investors and policymakers in handling the negative influence of unanticipated events. To retain economic stability, the Egyptian government can impose fiscal stimuli and consider policies to combat the impact of the pandemic.

This study is one of the first attempts to differentiate between the effects of subsequent waves of the pandemic on the stock market in Egypt, one of the largest economies in Africa.

This research provides some evidence by the vine copula approach, suggesting the significant and symmetric causal relation between subsections of Baltic Exchange and hence concluding that investing in different indexes, which is currently a risk diversification system, is not a correct risk reduction strategy.

The daily observations of Baltic Capesize Index (BCI), Baltic Handysize Index (BHSI), Baltic Dirty Tanker Index (BDTI) and Baltic LNG Tanker Index (BLNG) over an eight-year period have been used. After collecting data, calculating the return and estimating the marginal distribution of return rates for each of the indexes applying asymmetric power generalized autoregressive conditional heteroskedasticity and autoregressive moving average (APGARCH-ARMA), and with the assumption of skew student's t-distribution, the dependence of Baltic indexes was modeled based on Vine-R structures.

A positive and symmetrical correlation was observed between the study groups. High and low tail dependence is observed between all four indexes. In other words, the sector business groups associated with each of these indexes react similarly to the extreme events of other groups. The BHSI has a pivotal role in examining the dependency structure of Baltic Exchange indexes. That is, in addition to the direct dependence of Baltic groups, the dependence of each group on the BHSI can transmit accidents and shocks to other groups.

Since the Baltic Exchange indexes are tradable, these findings have implications for portfolio design and hedging strategies for investors in shipping markets.

Vine copula structures proves the causal relationship between different Baltic Exchange indexes, which are derived from different types of markets.

The COVID-19 outbreak and its confinement resulted in an unexpected stock market crash, hence the interest in environmental, social and governance (hereafter, ESG) policies. This paper aims to examine the association between ESG performance and stock market volatility before and after the COVID-19 pandemic.

This paper examined 500 US companies listed in the S&P 500. The window period volatility refers to March 18, 2020, when the US President signed into law the Families First Coronavirus Response Act. Here, the Thomson Reuters database was used to collect ESG data and daily market information.

The findings suggest that companies with high ESG performance have lower stock price volatility than companies with poor ESG performance. In other words, strong ESG performance reduces stock price volatility resulting from the COVID-19 shock and promotes resilience and stock price stability.

This research contributes to current debates on emerging pandemics and unexpected risks and highlights the need to invest more in improving corporate sustainability.

The results have substantial implications for managers and investors, as it highlights the relevance of customer and investor loyalty to the durability of ESG stocks.

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.

The authors present a model that incorporates stochastic interest rates to value equity‐linked life insurance contracts. The model generalizes some previous pricing results of Arne and Persson [1994] that are based on deterministic interest rates. The article also proposes and compares a design for a new equity‐linked product with the periodical premium contract of Brennan and Schwartz [1976]. The advantages of the proposed prod‐uct are its simplicity in pricing and its ease of hedging, by using either by long positions in the linked mutual fund or by European call options on the same fund.