Risks, Volume 6, Issue 4 (December 2018) – 42 articles

Policymakers in developing and emerging countries are facing higher risk that is related to natural disasters in comparison to developed ones because of persistent problem of supply-side bottleneck for disaster insurance. Additionally, lower insurance consumption, higher disaster risk, and high income elasticity of insurance demand have worsened the loss consequences of natural disaster in these markets. In this context, current study for the first time argues that the supply side bottleneck problem has its origin in peculiar pattern of disaster consumption owing to memory cues. The study finds that relatively higher frequency of natural disasters acts as a negative memory cue and positively impacts insurance consumption. On the other hand, a relatively lower frequency of natural disasters adversely impacts insurance consumption in the background of variation in risk aversion behavior. For this purpose, current study has based its work on Mullainathan (2002), which builds its argument around memory cues. Full article

Credibility theory is used widely in group health and casualty insurance. However, it is generally not used in individual life and annuity business. With the introduction of principle-based reserving (PBR), which relies more heavily on company-specific experience, credibility theory is becoming increasingly important for life actuaries. In this paper, we review the two most commonly used credibility methods: limited fluctuation and greatest accuracy (Bühlmann) credibility. We apply the limited fluctuation method to M Financial Group’s experience data and describe some general qualitative observations. In addition, we use simulation to generate a universe of data and compute Limited Fluctuation and greatest accuracy credibility factors for actual-to-expected (A/E) mortality ratios. We also compare the two credibility factors to an intuitive benchmark credibility measure. We see that for our simulated data set, the limited fluctuation factors are significantly lower than the greatest accuracy factors, particularly for low numbers of claims. Thus, the limited fluctuation method may understate the credibility for companies with favorable mortality experience. The greatest accuracy method has a stronger mathematical foundation, but it generally cannot be applied in practice because of data constraints. The National Association of Insurance Commissioners (NAIC) recognizes and is addressing the need for life insurance experience data in support of PBR—this is an area of current work. Full article

A risk-return association under normal market conditions can be conventional positive (risk-averse) or “paradoxical” negative (risk seeking). This study has the objective to investigate whether such an association is stable across market trends (i.e., bull and bear) and for overall, industry-classified and partitions sub-samples after controlling for a firm’s age, size, leverage and liquidity using operating performance risk-return measures. In total, this study analyses 2666 firms (1199 firms from 15 developed countries and 1467 firms from 12 emerging countries) for the period of 1999–2015. Results show that in the overall and bull sub-periods, firms across countries are showing conventional positive (superior firms) and “paradoxical” negative (poor firms) in most cases. However, in the bear sub-periods all firms from emerging countries are risk seeking in order to maintain their position in the pecking order. Full article

In both financial theory and practice, Value-at-risk (VaR) has become the predominant risk measure in the last two decades. Nevertheless, there is a lively and controverse on-going discussion about possible alternatives. Against this background, our first objective is to provide a current overview of related competitors with the focus on credit risk management which includes definition, references, striking properties and classification. The second part is dedicated to the measurement of risk concentrations of credit portfolios. Typically, credit portfolio models are used to calculate the overall risk (measure) of a portfolio. Subsequently, Euler’s allocation scheme is applied to break the portfolio risk down to single counterparties (or different subportfolios) in order to identify risk concentrations. We first carry together the Euler formulae for the risk measures under consideration. In two cases (Median Shortfall and Range-VaR), explicit formulae are presented for the first time. Afterwards, we present a comprehensive study for a benchmark portfolio according to Duellmann and Masschelein (2007) and nine different risk measures in conjunction with the Euler allocation. It is empirically shown that—in principle—all risk measures are capable of identifying both sectoral and single-name concentration. However, both complexity of IT implementation and sensitivity of the risk figures w.r.t. changes of portfolio quality vary across the specific risk measures. Full article

We enhance the modelling and risk assessment of sovereign bond spreads by taking into account quantitative information gained from macro-economic news sentiment. We investigate sovereign bonds spreads of five European countries and improve the prediction of spread changes by incorporating news sentiment from relevant entities and macro-economic topics. In particular, we create daily news sentiment series from sentiment scores as well as positive and negative news volume and investigate their effects on yield spreads and spread volatility. We conduct a correlation and rolling correlation analysis between sovereign bond spreads and accumulated sentiment series and analyse changing correlation patterns over time. Market regimes are detected through correlation series and the impact of news sentiment on sovereign bonds in different market circumstances is investigated. We find best-suited external variables for forecasts in an ARIMAX model set-up. Error measures for forecasts of spread changes and volatility proxies are improved when sentiment is considered. These findings are then utilised to monitor sovereign bonds from European countries and detect changing risks through time. Full article

Effects of seasonal affective disorder (SAD) are explored on several selected Central and South East European markets in this study for the period 2010–2018. Both return and risk sensitivities on the SAD effect are examined for 11 markets in total (Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Hungary, Poland, Serbia, Slovakia, Slovenia, Romania and Ukraine). SAD effects are based upon psychiatric and behavioural theories, and are rarely observed on the stock markets today. Thus, this research provides empirical evaluation of the mentioned effects for some of the markets for the first time in the literature. The results indicate that 6 out of 11 markets exhibit SAD effects to some extent, meaning that investors’ risk aversion does change over the year, depending upon the season of the year. Such results have consequences in finance theory modelling and practical usage in investment strategies on stock markets as well. Full article

The aim of this paper is to carry out a closed tool to estimate the one-year volatility of the claims reserve, calculated through the generalized linear models (GLM), notably the overdispersed- Poisson model. Up to now, this one-year volatility has been estimated through the well-known bootstrap methodology that demands the use of the Monte Carlo method with a re-reserving technique. Nonetheless, this method is time consuming under the calculation point of view; therefore, approximation techniques are often used in practice, such as an emergence pattern based on the link between the one-year volatility—resulting from the Merz–Wüthrich method—and the ultimate volatility—resulting from the Mack method. Full article

We develop a government debt management model to study the optimal debt ceiling when the ability of the government to generate primary surpluses to reduce the debt ratio is limited. We succeed in finding a solution for the optimal debt ceiling. We study the conditions under which a country is not able to reduce its debt ratio to reach its optimal debt ceiling, even in the long run. In addition, this model with bounded intervention is consistent with the fact that, in reality, countries that succeed in reducing their debt ratio do not do so immediately, but over some period of time. To the best of our knowledge, this is the first theoretical model on the debt ceiling that accounts for bounded interventions. Full article

Scientific discussions have emphasized that the main problem with the current deposit insurance system is that the current system does not evaluate the risks that banks assume to calculate the deposit insurance premiums in many countries of the European Union (E.U.). Thus, the prevailing system does not safeguard a sufficient level of stability in the banking system. Scientific studies show that the deposit insurance system should consider not only the risk indicators for individual banks, but it must also consider the systemic risk of banks that affects the stability of the banking system. Hence, the question arises as to whether measurements of systemic risk in a common E.U. risk-based deposit insurance system are a formal necessity or if they are a value-adding process. Expanding the discussion of scientists, this article analyzes how contributions to insurance funds would change the banks of Lithuania following the introduction of the E.U.’s overall risk-based deposit insurance system and after taking into consideration the additional systemic risk. The research results that were obtained provide evidence that the introduction of a risk-based deposit insurance system would redistribute payments to the deposit insurance fund between banks operating in Lithuania, and, thereby, would contribute to a reduction in the negative effects of the deposit insurance system and would improve the stability in the financial system. Full article

The financial crises which occurred in the last several decades have demonstrated the significant impact of market structural breaks on firms’ credit behavior. To incorporate the impact of market structural break into the analysis of firms’ credit rating transitions and firms’ asset structure, we develop a continuous-time modulated Markov model for firms’ credit rating transitions with unobserved market structural breaks. The model takes a semi-parametric multiplicative regression form, in which the effects of firms’ observable covariates and macroeconomic variables are represented parametrically and nonparametrically, respectively, and the frailty effects of unobserved firm-specific and market-wide variables are incorporated via the integration form of the model assumption. We further develop a mixtured-estimating-equation approach to make inference on the effect of market variations, baseline intensities of all firms’ credit rating transitions, and rating transition intensities for each individual firm. We then use the developed model and inference procedure to analyze the monthly credit rating of U.S. firms from January 1986 to December 2012, and study the effect of market structural breaks on firms’ credit rating transitions. Full article

In this paper, the risk model with constant interest based on an entrance process is investigated. Under the assumptions that the entrance process is a renewal process and the claims sizes satisfy a certain dependence structure, which belong to the different heavy-tailed distribution classes, the finite-time asymptotic estimate of the bidimensional risk model with constant interest force is obtained. Particularly, when inter-arrival times also satisfy a certain dependence structure, these formulas still hold. Full article

In risk theory, risks are often modeled by risk measures which allow quantifying the risks and estimating their possible outcomes. Risk measures rely on measure theory, where the risks are assumed to be random variables with some distribution function. In this work, we derive a novel topological-based representation of risks. Using this representation, we show the differences between diversifiable and non-diversifiable. We show that topological risks should be modeled using two quantities, the risk measure that quantifies the predicted amount of risk, and a distance metric which quantifies the uncertainty of the risk. Full article

This study utilizes the seven bivariate generalized autoregressive conditional heteroskedasticity (GARCH) models to forecast the out-of-sample value-at-risk (VaR) of 21 stock portfolios and seven currency-stock portfolios with three weight combinations, and then employs three accuracy tests and one efficiency test to evaluate the VaR forecast performance for the above models. The seven models are constructed by four types of bivariate variance-covariance specifications and two approaches of parameters estimates. The four types of bivariate variance-covariance specifications are the constant conditional correlation (CCC), asymmetric and symmetric dynamic conditional correlation (ADCC and DCC), and the BEKK, whereas the two types of approach include the standard and non-standard approaches. Empirical results show that, regarding the accuracy tests, the VaR forecast performance of stock portfolios varies with the variance-covariance specifications and the approaches of parameters estimate, whereas it does not vary with the weight combinations of portfolios. Conversely, the VaR forecast performance of currency-stock portfolios is almost the same for all models and still does not vary with the weight combinations of portfolios. Regarding the efficiency test via market risk capital, the NS-BEKK model is the most suitable model to be used in the stock and currency-stock portfolios for bank risk managers irrespective of the weight combination of portfolios. Full article

In recent times, investing in volatile security increases the risk of losses and reduces gains. Many traders who depend on these risks indulge in multiple volatility procedures to inform their trading strategies. We explore two models to measure the tails behaviour and the period the stock will gain or fall within a five-month trading period. We obtained data from the Ghana stock exchange and applied generalized extreme value distribution validated by backtesting and an artificial neural network for forecasting. The network training produces and manages more than 90% accuracy respectively for gains and falls for given input-output pairs. Based on this, estimates of extreme value distribution proves that it is formidable. There is a significant development in market prediction in assessing the results of actual and forecast performance. The study reveals that once every five months, at a 5% confidence level, the market is expected to gain and fall 2.12% and 2.23%, respectively. The Ghana stock exchange market showed a maximum monthly stock gain above or below 2.12% in the fourth and fifth months, whiles maximum monthly stock fell above or below 2.23% in the third and fourth months. The study reveals that once every five months’ trading period, the stock market will gain and fall by almost an equal percentage, with a significant increase in value-at-risk and expected shortfall at the left tail as the quantiles increases compared to the right tail. Full article

In our model, private actors with interbank cash flows similar to, but more general than that by Carmona et al. (2013) borrow from the non-banking financial sector at a certain interest rate, controlled by the central bank, and invest in risky assets. Each private actor aims to maximize its expected terminal logarithmic wealth. The central bank, in turn, aims to control the overall economy by means of an exponential utility function. We solve all stochastic optimal control problems explicitly. We are able to recreate occasions such as liquidity trap. We study distribution of the number of defaults (net worth of a private actor going below a certain threshold). Full article

The informal constraints that arise from the national culture in which a firm resides have a pervasive impact on managerial decision making and corporate credit risk, which in turn impacts on corporate ratings and rating changes. In some cultures, firms are naturally predisposed to rating changes in a particular direction (downgrade or upgrade) while, in other cultures, firms are more likely to migrate from the current rating in either direction. This study employs a survival analysis framework to examine the effect of national culture on the probability of rating transitions of 5360 firms across 50 countries over the period 1985–2010. Firms located in long-term oriented cultures are less likely to be downgraded and, in some cases, more likely to be upgraded. Downgrades occur more often in strong uncertainty-avoiding countries and less often in large power distance (hierarchy) and embeddedness countries. There is some evidence that masculinity predisposes firms to more rating transitions. Studying culture helps enrich our understanding of corporate rating migrations, and helps develop predictive models of corporate rating changes across countries. Full article

This paper studies the peer-to-peer lending and loan application processing of LendingClub. We tried to reproduce the existing loan application processing algorithm and find features used in this process. Loan application processing is considered a binary classification problem. We used the area under the ROC curve (AUC) for evaluation of algorithms. Features were transformed with splines for improving the performance of algorithms. We considered three classification algorithms: logistic regression, buffered AUC (bAUC) maximization, and AUC maximization.With only three features, Debt-to-Income Ratio, Employment Length, and Risk Score, we obtained an AUC close to 1. We have done both in-sample and out-of-sample evaluations. The codes for cross-validation and solving problems in a Portfolio Safeguard (PSG) format are in the Appendix. The calculation results with the data and codes are posted on the website and are available for downloading. Full article

Stocks are riskier than bonds. This causes a risk premium for stocks. That the size of this premium, however, seems to be larger than risk aversion alone can explain the so-called “equity premium puzzle”. One possible explanation is the inclusion of a degree of ambiguity in stock returns to account for an additional ambiguity premium, whose size depends on the degree of ambiguity aversion among investors. It is, however, difficult to test this empirically. In this paper, we compute the first firm-level estimation of equity premium based on the internal rate of return (IRR) approach for a total of N = 28,256 companies in 54 countries worldwide. Using a survey of international data on ambiguity aversion, we find a strong and robust relation between equity premia and ambiguity aversion. Full article

We present closed-form solutions to the perpetual American dividend-paying put and call option pricing problems in two extensions of the Black–Merton–Scholes model with random dividends under full and partial information. We assume that the dividend rate of the underlying asset price changes its value at a certain random time which has an exponential distribution and is independent of the standard Brownian motion driving the price of the underlying risky asset. In the full information version of the model, it is assumed that this time is observable to the option holder, while in the partial information version of the model, it is assumed that this time is unobservable to the option holder. The optimal exercise times are shown to be the first times at which the underlying risky asset price process hits certain constant levels. The proof is based on the solutions of the associated free-boundary problems and the applications of the change-of-variable formula. Full article

Risk management policy in agriculture has become particularly prominent nowadays, considering the evolution of the Common Agricultural Policy (CAP) and climate change. Moreover, the Word Trade Organization places constraints on it. In this context, (1) the aim is to analyze the causes of the loss of effectiveness of the Italian insurance system, unable to deal with the specific coverage demand from agriculture. (2) The analysis is carried out through the economic evaluation of convenience in adhering to the instruments offered by the insurance market to winegrowers in the Controlled and Guaranteed Denomination of Origin (DOCG) area of Conegliano-Valdobbiadene. (3) The study highlights that the subsidized coverage alone is not the most adequate measure of agricultural policy. Adhering to preferential programs implies the drafting of a supplementary insurance policy to minimize the loss function. (4) The current insurance system impasse demonstrates that the producer hardly accepts to policies which do not convert into an immediate income benefit. The European risk management regulation confirms its limits in terms of usefulness and efficiency of the agrarian policy. (5) The prediction of probabilistic increase of severe-weather patterns makes the search for innovative risk assessment models more urgent, models which can combine the different needs of stakeholders: farmers, insurance companies, and society. Full article

Portfolio weights solely based on risk avoid estimation errors from the sample mean, but they are still affected from the misspecification in the sample covariance matrix. To solve this problem, we shrink the covariance matrix towards the Identity, the Variance Identity, the Single-index model, the Common Covariance, the Constant Correlation, and the Exponential Weighted Moving Average target matrices. Using an extensive Monte Carlo simulation, we offer a comparative study of these target estimators, testing their ability in reproducing the true portfolio weights. We control for the dataset dimensionality and the shrinkage intensity in the Minimum Variance (MV), Inverse Volatility (IV), Equal-Risk-Contribution (ERC), and Maximum Diversification (MD) portfolios. We find out that the Identity and Variance Identity have very good statistical properties, also being well conditioned in high-dimensional datasets. In addition, these two models are the best target towards which to shrink: they minimise the misspecification in risk-based portfolio weights, generating estimates very close to the population values. Overall, shrinking the sample covariance matrix helps to reduce weight misspecification, especially in the Minimum Variance and the Maximum Diversification portfolios. The Inverse Volatility and the Equal-Risk-Contribution portfolios are less sensitive to covariance misspecification and so benefit less from shrinkage. Full article

The variance of stock returns is decomposed based on a conditional Fama–French three-factor model instead of its unconditional counterpart. Using time-varying alpha and betas in this model, it is evident that four additional risk terms must be considered. They include the variance of alpha, the variance of the interaction between the time-varying component of beta and factors, and two covariance terms. These additional risk terms are components that are included in the idiosyncratic risk estimate using an unconditional model. By investigating the relation between the risk terms and stock returns, we find that only the variance of the time-varying alpha is negatively associated with stock returns. Further tests show that stock returns are not affected by the variance of time-varying beta. These results are consistent with the findings in the literature identifying return predictability from time-varying alpha rather than betas. Full article

Mortality forecasting has always been a target of study by academics and practitioners. Since the introduction and rising significance of securitization of risk in mortality and longevity, more in-depth studies regarding mortality have been carried out to enable the fair pricing of such derivatives. In this article, a comparative analysis is performed on the mortality forecasting accuracy of four mortality models. The methodology employs the Age-Period-Cohort model, the Cairns-Blake-Dowd model, the classical Lee-Carter model and the Kou-Modified Lee-Carter model. The Kou-Modified Lee-Carter model combines the classical Lee-Carter with the Double Exponential Jump Diffusion model. This paper is the first study to employ the Kou model to forecast French mortality data. The dataset comprises death data of French males from age 0 to age 90, available for the years 1900–2015. The paper differentiates between two periods: the 1900–1960 period where extreme mortality events occurred for French males and the 1961–2015 period where no significant jump is observed. The Kou-modified Lee-Carter model turns out to give the best mortality forecasts based on the RMSE, MAE, MPE and MAPE metrics for the period 1900–1960 during which the two World Wars occurred. This confirms that the consideration of jumps and leptokurtic features conveys important information for mortality forecasting. Full article

We propose a Monte Carlo simulation method to generate stress tests by VaR scenarios under Solvency II for dependent risks on the basis of observed data. This is of particular interest for the construction of Internal Models. The approach is based on former work on partition-of-unity copulas, however with a direct scenario estimation of the joint density by product beta distributions after a suitable transformation of the original data. Full article

There has been much discussion in the literature about how central measures of equity risk such as standard deviation fail to account for extreme tail risk of equities. Similarly, parametric measures of value at risk (VaR) may also fail to account for extreme risk as they assume a normal distribution which is often not the case in practice. Nonparametric measures of extreme risk such as nonparametric VaR and conditional value at risk (CVaR) have often been found to overcome this problem by measuring actual tail risk without applying any predetermined assumptions. However, this article argues that it is not just the actual risk of equites that is important to investor choices, but also the relative (ordinal) risk of equities compared to each other. Using an applied setting of industry portfolios in a variety of Asian countries (benchmarked to the United States), over crisis and non-crisis periods, this article finds that nonparametric measures of VaR and CVaR may provide only limited new information to investors about relative risk in the portfolios examined as there is a high degree of similarity found in relative industry risk when using nonparametric metrics as compared to central or parametric measures such as standard deviation and parametric VaR. Full article

This study examines empirically the volatility spillover effects between the RMB foreign exchange markets and the stock markets by employing daily returns of the Chinese RMB exchange rates and the stock markets in China and Japan during the period in 1998–2018. We find evidence that there exist co-volatility effects among the financial markets in China and Japan, and the volatility of RMB exchange rates contribute to the co-volatility spillovers across the financial markets. Reversely, the return shock from the stock markets can also generate co-volatility spillover to the foreign exchange markets. The bidirectional relationship reveals that both the fundamental hypothesis and the investor-induced hypothesis are valid. Our estimates also show that the spillover effects led by the stock market in Japan are stronger than that from the foreign exchange markets and the Chinese stock markets, implying that market with higher accessibility has greater spillover effects onto other markets. We also found that the average co-volatility spillover effects among the RMB exchange markets and the stock markets in Japan and China are generally negative. These findings have important policy implications for risk management and hedging strategies. Full article

Based on suitable left-truncated or censored data, two flexible classes of M-estimations of Weibull tail coefficient are proposed with two additional parameters bounding the impact of extreme contamination. Asymptotic normality with $\sqrt{n}$ -rate of convergence is obtained. Its robustness is discussed via its asymptotic relative efficiency and influence function. It is further demonstrated by a small scale of simulations and an empirical study on CRIX. Full article

The objective of this research is to evaluate the influence on hedging decisions of a realistic set of transaction costs which are largely stochastic. The stochastic nature of some transaction costs (such as margin calls) means that their exact value is unknown when the hedge is placed, since they depend on the trajectory of futures prices during the hedge. Results are consistent with previous studies in that the introduction of transaction costs tend to affect hedge ratios. However, as opposed to the traditional literature, the introduction of stochastic costs in futures hedging can either decrease or increase hedge ratios depending on how these costs are determined. Full article

In this paper, the following research problem was addressed: Is DEA (Data Envelopment Analysis) method a suitable alternative to Altman model in predicting the risk of bankruptcy? Based on the above-mentioned research problem, we formulated the aim of the paper: To apply DEA method for predicting the risk of bankruptcy and to compare its results with the results of Altman model. The research problem and the aim of the paper follow the research of authors aimed at the application of methods which are appropriate for measuring business financial health, performance and competitiveness as well as for predicting the risk of bankruptcy. To address the problem, the following methods were applied: financial ratios, Altman model for private non-manufacturing firms and DEA method. When applying DEA method, we formulated input-oriented DEA CCR model. We found that DEA method is an appropriate alternative to Altman model in predicting the risk of possible business bankruptcy. The important conclusion is that DEA allows us to apply not only outputs but also inputs. Since prediction models do not include these indicators, DEA method appears to be the right choice. We recommend, especially for Slovak companies, to apply cost ratio when calculating risk of bankruptcy. Full article

Addressing the volatility spillovers of agricultural commodities is important for at least two reasons. First, for the last several years, the volatility of agricultural commodity prices seems to have increased. Second, according to the Food and Agriculture Organization, there is a strong need for understanding the potential (negative) impacts on food security caused by food commodity volatilities. This paper aims at investigating the presence, the size, and the persistence of volatility spillovers among five agricultural commodities (corn, sugar, wheat, soybean, and bioethanol) and five Latin American (Argentina, Brazil, Chile, Colombia, Peru) stock market indexes. Overall, when a negative shock hits the commodity market, Latin American stock market volatility tends to increase. This happens, for instance, for the relationships from corn to Chile and Colombia and from wheat to Peru and Chile. Full article