Risks, Volume 10, Issue 7 (July 2022) – 12 articles

We consider the problem where a modeller conducts sensitivity analysis of a model consisting of random input factors, a corresponding random output of interest, and a baseline probability measure. The modeller seeks to understand how the model (the distribution of the input factors as well as the output) changes under a stress on the output’s distribution. Specifically, for a stress on the output random variable, we derive the unique stressed distribution of the output that is closest in the Wasserstein distance to the baseline output’s distribution and satisfies the stress. We further derive the stressed model, including the stressed distribution of the inputs, which can be calculated in a numerically efficient way from a set of baseline Monte Carlo samples and which is implemented in the R package SWIM on CRAN. The proposed reverse sensitivity analysis framework is model-free and allows for stresses on the output such as (a) the mean and variance, (b) any distortion risk measure including the Value-at-Risk and Expected-Shortfall, and (c) expected utility type constraints, thus making the reverse sensitivity analysis framework suitable for risk models. Full article

In many countries around the world, demographic and civilization changes have brought about the phenomenon of aging societies. This phenomenon affects the economy, especially the pension and health care systems, causing difficulties in their financing. The implementation of a policy that would effectively manage the problem of the longevity risk is thus required. Using housing resources and private health insurance to improve retirees’ living standards may serve this purpose. The instruments we propose comprise two variants of contracts: the first for a marriage, the second for an individual client. We analysed the cash flow in both the cases. The results suggest that the amount of cash flows related to reverse equity and dread disease insurance benefits depends on the spouse’s economic status, age, and health conditions. The benefits of the two variants of the contract vary. This paper examines numerous strategies for selecting the type of the contract, taking into consideration the abovementioned factors. Full article

This paper contributes to the supply chain finance literature with an agent-based Monte Carlo simulation model focusing on the bank’s point of view. Our theoretical model assesses how a bank should screen a supply chain (SC) member and whether that requires different considerations and monitoring systems compared with traditional corporate loans. In the model, the SC members may cooperate, reducing their bankruptcy risk considerably; thus, the chance for and extent of inter-entity financial aid are critical to consider when assessing bankruptcy risk. A cooperative SC member cannot just be financed from debt taken by other members, but it may also offer protection to other SC members using its operating cash flow. Thus, based on our results, bankruptcy risk is SC-specific, rather than a characteristic of an individual firm. Therefore, to finance an SC member is a quasi-joint decision of its peers, so particular care should be paid to estimating and monitoring the correlations between the operational cash flows of cooperative SC members. One of the key results is that of edge default exposure of the bank; it might be optimal to limit the amount of the loan made available to a given collaborative SC member instead of charging higher rates or financing the most attractive SC member only. Another SC member offering an additional guarantee with its assets will provide the remaining need for financing. As this solution also reduces the total bankruptcy risk of the SC, the SC itself should prefer this financing structure. Full article

This study provides a detailed investigation of the time–frequency and frequency-domain analysis of the interconnectedness of country-level macroeconomic variables. Hence, the wavelet techniques—vector wavelet and wavelet multiple—employed with TVP-VAR are utilised as a robustness check. The macroeconomic variables considered are consumer price index (CPI), real exchange rate (EXR) and nominal effective exchange rate (NEER) for four selected West African economies—Côte d’Ivoire, Gambia, Ghana and Nigeria. The findings of the study reveal that there are significant comovements between the macroeconomic dynamics in a time–frequency domain for the selected economies. From the wavelet multiple technique, the study finds three interesting outcomes. First, there are traces of high comovements between the macroeconomic conditions of some countries in the long term. In addition, NEER has a strong exposure to external shocks due to the presence of periodic swings such as inflation, which makes it largely susceptible to shocks. Second, a high integration of macroeconomic variables, in the long term is found. Third, Global Economic Policy Uncertainty (GEPU) lags in the long term within the interdependencies of CPI as well as NEER but not EXR. This suggests that the presence of inflation most likely exposes these economies to external shocks. However, when this happens, external shocks act as a follower to influence economic activities within this region. The study advocates that governments and policymakers should deploy efficient inflation-targeting monetary policies to enhance price stability and minimise the adverse impact of GEPU for future monetary convergence. Full article

This study investigates the co-movements between the Solactive Electric Vehicle and Future Mobility Index (EVFMI) and multiple rare earth elements (REEs). We applied a TVP-VAR model and bivariate wavelet coherence approach to capture co-movements both in the time and frequency domain considering short-, medium- and long-term investment horizons. Using daily returns from 1 June 2012 to 4 June 2021, the results of the TVP-VAR model show that individual REEs and the EVFMI have strong return connectedness and are heterogenous over time. The bivariate wavelet coherence approach reveals that Dysprosium, Neodymium, Praseodymium and Terbium returns have positive co-movement (in-phase) with the EVFMI in the medium-term and long-term. In contrast, Cerium, Europium, Lanthanum and Yttrium returns have negative co-movements (out-phase) with the EVFMI in the medium-term and long-term. We find strong positive co-movements between the MVIS Global Rare Earth/Strategic Metals Index (MVREMX) and EVFMI at multiple wavelet scales. Following the lead/lag relationship, Cerium, Europium and Lanthanum, Yttrium returns are leading the EVFMI, and Neodymium, Dysprosium, Praseodymium, Terbium and MVREMX returns are lagging to the EVFMI. This study, therefore, suggests heterogenous hedging and diversification properties of REEs over time and investment horizons. Specifically, Cerium, Europium, Lanthanum and Yttrium act as strong hedges in long-term investment horizons and Neodymium, Dysprosium, Praseodymium and Terbium are weak hedges or diversifiers in short-term investment horizons. These results may be of particular interest to investors and relevant to policymakers considering multiple investment horizons. Full article

This study examines the responses of Bitcoin and gold to categorical financial stress and compares the responses before and during the COVID-19 pandemic. The OLS and Quantile regression estimations revealed that gold and Bitcoin exhibit similar reactions in full and pre COVID-19 samples. Gold and Bitcoin respond positively to equity valuation and safe assets categories of financial stress. Gold also reacts positively to the credit category of financial stress suggesting that widening credit spreads are bullish for gold. Bitcoin and gold respond differently in the funding category, and there is no significant reaction to volatility-related financial stress. Overall, the effects of categorical financial stress on gold and Bitcoin are similar in the full sample and sub-sample before COVID-19, but the effects are heterogeneous. Interestingly, during the pandemic, the reactions of gold and Bitcoin to categorical financial stress have changed. Gold only reacts positively to the credit category of financial stress across quantiles. Bitcoin reacts positively to credit and safe asset categories but not across all quantiles. The findings offer insights into the effects of several systemic financial stress on the value of safe haven assets. Full article

The main aim of this study is to explore the conceptual framework of corporate financial culture and its practical relevance in an emerging Central European market economy, at the level of the Hungarian SME, with a special emphasis on the Hungarian SME sector. In our study, we highlight each dimension of corporate financial culture, focusing on the established corporate financial culture index, and within it, we examine the significance of the financial management elements sub-index and the risk and insurance sub-index separately. In addition, we look for logical, causal, and statistically verifiable relationships between corporate financial literacy and the outcome of corporate financial decisions and corporate risk taking. The relationships were broken down over two years in the analysis. Approximately 2167 responses were included in the 2019 sample and 3281 in the 2021 sample. These representative samples were taken from the Hungarian SME sector and multiple linear regression models were built to find a significant moderation effect of financial literacy between perceived risks and the insurance activity of companies. We conducted our research in two different periods, the unique feature of which is that we conducted a survey before and during the coronavirus crisis, so we could make a comparative analysis. The method used in this research study is a literature review analysis of reference manuscripts, discussing topics related to financial literacy, corporate risk management, and corporate financial management, published in the last 10 years. Our results show that there are positive and significant relationships between company management, corporate risk management, and corporate financial literacy. The results of our study draw the attention of company leaders to the practical significance of financial culture—efficiency, profitability, and stability. Full article

In this paper, we focus on an implicit assumption in the BSM framework that limits the scope of market network connections to seeking gains in the currency basis, i.e., on trading strategies between the numeraire and the stock and between the numeraire and the option, separately. We relax this assumption and derive the equivalent of the standard BSM approach under a more general market network framework in order to assess its implications. In doing so, we find that it is not possible to hedge on an implicit option that allows one to directly trade the option and stock. This represents a potential challenge to the BSM framework, since the missing market network connection provides a potentially useful mechanism for risk-bearing portfolio managers to alter their portfolios. Full article

A new Archimedean copula family is presented that was derived from the SAHARA utility function introduced in the economic literature in 2011. Its properties are discussed, and its flexibility and versatility are demonstrated. It is left tail decreasing or right tail increasing, but unlike mainstream Archimedean families, not necessarily stochastically increasing at the same time. It is shown that the family fits very well to a dataset of previously studied coupled lives in the literature. Full article

The detection of anomalous data patterns is one of the most prominent machine learning use cases in industrial applications. Unfortunately very often there are no ground truth labels available and therefore it is good practice to combine different unsupervised base learners with the hope to improve the overall predictive quality. Here one of the challenges is to combine base learners that are accurate and divers at the same time, where another challenge is to enable model explainability. In this paper we present BHAD, a fast unsupervised Bayesian histogram anomaly detector, which scales linearly with the sample size and the number of attributes and is shown to have very competitive accuracy compared to other analyzed anomaly detectors. For the problem of model explainability in unsupervised outlier ensembles we introduce a generic model explanation approach using a supervised surrogate model. For the problem of ensemble construction we propose a greedy model selection approach using the mutual information of two score distributions as a similarity measure. Finally we give a detailed description of a real fraud detection application from the corporate insurance domain using an outlier ensemble, we share various feature engineering ideas as well as discuss practical challenges. Full article

In this paper, we present extensions of the Hatzopoulos–Sagianou (2020) (HS) multiple-component stochastic mortality model. Our aim is to thoroughly evaluate and stress test the HS model by deploying various link functions, using generalised linear models, and diverse distributions in the model’s estimation method. In this work, we differentiate the HS approach by modelling the number of deaths using the Binomial model commonly employed in the literature of mortality modelling. Given this, new HS extensions are derived using the off-the-shelf link functions, namely the complementary log–log, logit and probit, while we also reform the model by introducing a new form of link functions with a particular focus on the use of heavy-tailed distributions. The above-mentioned enhancements conclude to a new methodology for the HS model, and we prove that it is more suitable than those used in the literature to model the mortality dynamics. In this regard, our work offers an extensive experimental testbed to scrutinise the efficiency, explainability and capacity of the HS model extensions using both the off-the-shelf and the newly introduced form of link functions over datasets with different characteristics. The introduced HS extensions bring an improvement by approximately 16% to the model’s goodness-of-fit, while they uncover more fine-grained age clusters. In addition, we compare the performance of the HS extensions against other well-known mortality models, both under fitting and forecast modes. The results reflect the advantageous features of the HS extensions to deliver a highly informative structure and enable the attribution of an identified mortality trend to a unique age cluster. The above-mentioned improvements enable mortality analysts to perform an in-depth and more detailed investigation of mortality trends for specific age clusters and can contribute to the attempts of academia and industry to tackle the uncertainties and risks introduced by the increasing life expectancy. Full article

China’s bond market has been ranked third globally; however, China’s corporate bonds are significantly less liquid than its stocks. Liquidity risk is an important component in China’s corporate bond spreads. In this paper, we propose a stochastic liquidity discount factor model to evaluate the liquidity risk premium and its term structure in China’s corporate bond market. The Monte Carlo simulation technique is used to quantify the impact on the liquidity premium of various liquidity factors: the liquidity level, liquidity volatility, liquidity shock, and the liquidity elasticity. Our findings conclude that the liquidity level is the most significant component of a liquidity premium. The impact on the liquidity premium of other liquidity factors is all conditional on the liquidity level. In addition, the impact of liquidity shocks and volatility is also subject to the market’s equilibrium mechanism. Further, the term of a bond affects the premium both directly and indirectly through its influence on a bond’s liquidity. Full article