Risks

31 pages, 771 KiB

Open AccessFeature PaperArticle

Stochastic Chain-Ladder Reserving with Modeled General Inflation

by Massimo De Felice and Franco Moriconi

Risks 2023, 11(12), 221; https://doi.org/10.3390/risks11120221 - 18 Dec 2023

Viewed by 1340

We consider two possible approaches to the problem of incorporating explicit general (i.e., economic) inflation in the non-life claims reserve estimates and the corresponding reserve SCR, defined—as in Solvency II—under the one-year view. What we call the actuarial approach provides a simplified solution [...] Read more.

We consider two possible approaches to the problem of incorporating explicit general (i.e., economic) inflation in the non-life claims reserve estimates and the corresponding reserve SCR, defined—as in Solvency II—under the one-year view. What we call the actuarial approach provides a simplified solution to the problem, obtained under the assumption of deterministic interest rates and absence of inflation risk premia. The market approach seeks to eliminate these shortcomings by combining a stochastic claims reserving model with a stochastic market model for nominal and real interest rates. The problem is studied in details referring to the stochastic chain-ladder provided by the Over-dispersed Poisson model. The application of the two approaches is illustrated by a worked example based on market data. Full article

(This article belongs to the Special Issue Advancements in Actuarial Mathematics and Risk Theory)

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21 pages, 557 KiB

Open AccessFeature PaperArticle

Bidual Representation of Expectiles

by Alejandro Balbás, Beatriz Balbás, Raquel Balbás and Jean-Philippe Charron

Risks 2023, 11(12), 220; https://doi.org/10.3390/risks11120220 - 15 Dec 2023

Cited by 1 | Viewed by 1265

Abstract

Downside risk measures play a very interesting role in risk management problems. In particular, the value at risk (VaR) and the conditional value at risk (CVaR) have become very important instruments to address problems such as risk optimization, capital requirements, portfolio selection, pricing [...] Read more.

Downside risk measures play a very interesting role in risk management problems. In particular, the value at risk (VaR) and the conditional value at risk (CVaR) have become very important instruments to address problems such as risk optimization, capital requirements, portfolio selection, pricing and hedging issues, risk transference, risk sharing, etc. In contrast, expectile risk measures are not as widely used, even though they are both coherent and elicitable. This paper addresses the bidual representation of expectiles in order to prove further important properties of these risk measures. Indeed, the bidual representation of expectiles enables us to estimate and optimize them by linear programming methods, deal with optimization problems involving expectile-linked constraints, relate expectiles with VaR and CVaR by means of both equalities and inequalities, give VaR and CVaR hyperbolic upper bounds beyond the level of confidence, and analyze whether co-monotonic additivity holds for expectiles. Illustrative applications are presented. Full article

(This article belongs to the Special Issue Optimal Investment and Risk Management)

18 pages, 2454 KiB

Open AccessArticle

Asymmetric Effects of Tax Competition on FDI vs. Budget Balance in European OECD Economies: Heterogeneous Panel Approach

by Marina Beljić, Olgica Glavaški, Emilija Beker Pucar, Stefan Stojkov and Jovica Pejčić

Risks 2023, 11(12), 219; https://doi.org/10.3390/risks11120219 - 15 Dec 2023

Viewed by 1353

Abstract

The global trends in taxation have generated a “race to the bottom” in capital income taxation, which is intended to be stopped by OECD through the introduction of a global minimum tax rate (15% of effective average tax rate—EATR). The question is whether [...] Read more.

The global trends in taxation have generated a “race to the bottom” in capital income taxation, which is intended to be stopped by OECD through the introduction of a global minimum tax rate (15% of effective average tax rate—EATR). The question is whether the defined tax competition floor would have heterogeneous implications in different economies. The aim of this paper is to examine the long-term relationship between the EATR and FDI, and between the EATR and budget balance (BB) in European OECD economies in the period 1998–2021, using non-stationary, heterogeneous panels. According to the linear PMG model, a significant negative long-term relationship was revealed between the EATR and FDI and between the EATR and BB, while the error-correction parameters are significant and heterogeneous, showing that the speed of adjustments towards equilibrium is different across the analyzed economies. However, the nonlinear PMG results revealed asymmetry as the magnitude of the influence of an EATR reduction has a greater effect on FDI attraction and deficit deepening than an increase in the EATR on the opposite tendencies of FDI and deficit. Policymakers are facing a trade-off related to FDI attraction/budget deficit deepening when making decisions in relation to the EATR, and they are mostly oriented toward FDI inflow using EATR reduction in the analyzed economies. Full article

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24 pages, 484 KiB

Open AccessArticle

Financial Stress and COVID-19: A Comprehensive Analysis of the Factors Associated with the Pandemic

by Keewon Moon, Wookjae Heo, Jae Min Lee and John E. Grable

Risks 2023, 11(12), 218; https://doi.org/10.3390/risks11120218 - 13 Dec 2023

Viewed by 2117

Abstract

The COVID-19 pandemic introduced unprecedented challenges for households globally, serving as a precursor to and trigger for financial stress. This study examined the associations across various factors thought to be associated with financial stress (a psychological syndrome) resulting from the COVID-19 pandemic. Using [...] Read more.

The COVID-19 pandemic introduced unprecedented challenges for households globally, serving as a precursor to and trigger for financial stress. This study examined the associations across various factors thought to be associated with financial stress (a psychological syndrome) resulting from the COVID-19 pandemic. Using survey data collected in 2019 (n = 997) and 2021 (n = 988), propensity score matching and hierarchical linear modeling were employed to identify the association between financial stress and the pandemic. Results indicated that financial stress increased during the COVID-19 pandemic. Three covariate groups, including financial characteristics, health status, and socio-demographic characteristics, were found to be associated with financial stress levels. The primary contribution of this paper lies in offering a comprehensive understanding of how the dynamics of financial stress evolve with shifting macroeconomic events. This paper serves as a framework to employ a comprehensive financial stress measure and matched samples at various data points. Findings from this study contribute to the existing literature on financial well-being, financial stress, and societal outcomes associated with global health events while providing implications for policy and practice. Full article

24 pages, 659 KiB

Open AccessFeature PaperArticle

Option Pricing and Portfolio Optimization under a Multi-Asset Jump-Diffusion Model with Systemic Risk

by Roman N. Makarov

Risks 2023, 11(12), 217; https://doi.org/10.3390/risks11120217 - 13 Dec 2023

Viewed by 1426

Abstract

We explore a multi-asset jump-diffusion pricing model, combining a systemic risk asset with several conditionally independent ordinary assets. Our approach allows for analyzing and modeling a portfolio that integrates high-activity security, such as an exchange trading fund (ETF) tracking a major market index [...] Read more.

We explore a multi-asset jump-diffusion pricing model, combining a systemic risk asset with several conditionally independent ordinary assets. Our approach allows for analyzing and modeling a portfolio that integrates high-activity security, such as an exchange trading fund (ETF) tracking a major market index (e.g., S&P500), along with several low-activity securities infrequently traded on financial markets. The model retains tractability even as the number of securities increases. The proposed framework allows for constructing models with common and asset-specific jumps with normally or exponentially distributed sizes. One of the main features of the model is the possibility of estimating parameters for each asset price process individually. We present the conditional maximum likelihood estimation (MLE) method for fitting asset price processes to empirical data. For the case with common jumps only, we derive a closed-form solution to the conditional MLE method for ordinary assets that works even if the data are incomplete and asynchronous. Alternatively, to find risk-neutral parameters, the least-square method calibrates the model to option values. The number of parameters grows linearly in the number of assets compared to the quadratic growth through the correlation matrix, which is typical for many other multi-asset models. We delve into the properties of the proposed model, its parameter estimation using the MLE method and least-squares technique, the evaluation of VaR and CVaR metrics, the identification of optimal portfolios, and the pricing of European-style basket options. We propose a Laplace-transform-based approach to computing Value at Risk (VaR) and conditional VaR (also known as the expected shortfall) of portfolio returns. Additionally, European-style basket options written on the extreme and average stock prices or returns can be evaluated semi-analytically. For numerical demonstration, we examine a combination of the SPDR S&P 500 ETF (as a systemic risk asset) with eight ordinary assets representing diverse industries. Using historical assets and options prices, we estimate the real-world and risk-neutral parameters of the model with common jumps, construct several optimal portfolios, and evaluate various basket options with the eight assets. The results affirm the robustness and efficiency of the estimation and evaluation methodologies. Computational results are compared with Monte Carlo estimates. Full article

(This article belongs to the Special Issue Optimal Investment and Risk Management)

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27 pages, 510 KiB

Open AccessArticle

Consumer Preferences for Health Services Offered by Health Insurance Companies in Germany

by Raphael Schilling, Milena Pavlova and Andrea Karaman

Risks 2023, 11(12), 216; https://doi.org/10.3390/risks11120216 - 12 Dec 2023

Viewed by 1837

Abstract

German health insurance companies increasingly strive to position themselves as health partners to their customers to improve customers’ health and contain costs. However, there is uncertainty about customers’ preferences for health services offered by health insurance companies. Therefore, this paper studies consumer preferences [...] Read more.

German health insurance companies increasingly strive to position themselves as health partners to their customers to improve customers’ health and contain costs. However, there is uncertainty about customers’ preferences for health services offered by health insurance companies. Therefore, this paper studies consumer preferences for health services that are or could be provided by health insurance companies in Germany. An online survey was conducted using two stated preference techniques to collect and analyze the data (namely, rating and ranking of health services considered by insurance companies). A sample of 880 German health insurance customers between 18 and 65 years old filled out the online questionnaire, of which 860 submitted complete responses. Ordinal logistic regression analysis was used for the rating and ranking. Preliminary examinations, care management, and health programs were the three health services most important to the respondents. The results suggest that people want their health insurance to support them with preventive health services that offer direct therapeutic value and not just informational, economic, access-related, or convenience-related benefits. These preferences for health services are homogeneous for most subgroups of the population, implying that health insurance companies could consider an overall strategy to address these preferences for all clients by focusing on the important health services. Full article

(This article belongs to the Special Issue Advancements in Actuarial Mathematics and Insurance Risk Management)

9 pages, 550 KiB

Open AccessArticle

The Estimation of Risk Premia with Omitted Variable Bias: Evidence from China

by Jie Mao and Tianliang Xia

Risks 2023, 11(12), 215; https://doi.org/10.3390/risks11120215 - 11 Dec 2023

Viewed by 1424

Abstract

The Chinese stock market is replete with numerous omitted variables that can introduce biases in the standard estimation of risk premiums when traditional linear asset pricing models are applied. The three-pass method enables the estimation of risk premiums for observable factors even when [...] Read more.

The Chinese stock market is replete with numerous omitted variables that can introduce biases in the standard estimation of risk premiums when traditional linear asset pricing models are applied. The three-pass method enables the estimation of risk premiums for observable factors even when not all relevant factors are explicitly specified or observed within the model. Accordingly, we have applied this method to construct portfolios with stocks from China’s A-share market as the test assets. Empirical research findings indicate that the three-pass method could be more effective than traditional linear asset pricing models in estimating risk premiums. Full article

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36 pages, 15235 KiB

Open AccessArticle

Effectiveness of Green Bonds in Selected CEE Countries: Analysis of Similarities

by Maria Czech, Monika Hadaś-Dyduch and Blandyna Puszer

Risks 2023, 11(12), 214; https://doi.org/10.3390/risks11120214 - 08 Dec 2023

Viewed by 1470

Abstract

Green bonds are an increasingly important area not only in the financing of investments important to the environment, but recently also as an object of investment. From the investors point of view, the key aspect still remains the efficiency of the investment and [...] Read more.

Green bonds are an increasingly important area not only in the financing of investments important to the environment, but recently also as an object of investment. From the investors point of view, the key aspect still remains the efficiency of the investment and its profitability. The subject of this research is to evaluate changes in the efficiency of green bonds issued in the selected CEE countries (Poland, Slovakia, Czech Republic, and Hungary), in the short and long term. Poland is the largest issuer of green bonds in this group, followed by the Czech Republic, Hungary, and Slovakia. Individual green bonds in these group of countries are characterized by varying levels of green bond yields, duration of the investment, issue size and counterparty risk. These factors greatly hinder their comparability, especially in terms of investment efficiency. This manuscript fits into this area, as the main purpose of the manuscript is to show similarities in the yields of green bonds issued in Poland and green bonds issued in CEE countries. The hypothesis that will be tested is that changes in the effectiveness of green bonds issued in Poland are strongly correlated with changes in the effectiveness of green bonds issued in CEE countries. The results of the research positively verified the hypothesis, and the objectives of the research were achieved. It was shown that green bonds issued in the Czech Republic and Slovakia demonstrate a high similarity in terms of effectiveness to green bonds issued in Poland. At the same time, the results confirmed that of all the bonds analysed, the one bond issued by the Hungarian government is the least related to green bonds issued in Poland in terms of effectiveness for investors. The study used multiresolution analysis and Dynamic Time Warping. The Dynamic Time Warping algorithm measures the similarity between two sequences that can change over time. The analysis was carried out over a wide temporal cross-section, analysing the similarity between the effectiveness in both the short and long term. Full article

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17 pages, 446 KiB

Open AccessFeature PaperArticle

The Applications of Generalized Poisson Regression Models to Insurance Claim Data

by Pouya Faroughi, Shu Li and Jiandong Ren

Risks 2023, 11(12), 213; https://doi.org/10.3390/risks11120213 - 07 Dec 2023

Viewed by 1638

Abstract

Predictive modeling has been widely used for insurance rate making. In this paper, we focus on insurance claim count data and address their common issues with more flexible modeling techniques. In particular, we study the zero-inflated and hurdle-generalized Poisson and negative binomial distributions [...] Read more.

Predictive modeling has been widely used for insurance rate making. In this paper, we focus on insurance claim count data and address their common issues with more flexible modeling techniques. In particular, we study the zero-inflated and hurdle-generalized Poisson and negative binomial distributions in a functional form for modeling insurance claim count data. It is shown that these models are useful in addressing the problem of excess zeros and over-dispersion of the claim count variable. In addition, we show that including the exposure as a covariate in both the zero and the count part of the model is an effective approach to incorporating exposure information in zero-inflated and hurdle models. We illustrate the effectiveness and versatility of the introduced models using three real datasets. The results suggest their promising applications in insurance risk classification and beyond. Full article

(This article belongs to the Special Issue Risks Journal: A Decade of Advancing Knowledge and Shaping the Future)

22 pages, 2763 KiB

Open AccessFeature PaperArticle

Enhancing Sustainable Finance through Green Hydrogen Equity Investments: A Multifaceted Risk-Return Analysis

by Cristiana Tudor

Risks 2023, 11(12), 212; https://doi.org/10.3390/risks11120212 - 06 Dec 2023

Viewed by 1408

Abstract

Amidst the global push for decarbonization, green hydrogen has gained recognition as a versatile and clean energy carrier, prompting the financial sector to introduce specialized investment instruments like Green Hydrogen Exchange-Traded Funds (ETFs). Despite the nascent nature of research on green hydrogen portfolio [...] Read more.

Amidst the global push for decarbonization, green hydrogen has gained recognition as a versatile and clean energy carrier, prompting the financial sector to introduce specialized investment instruments like Green Hydrogen Exchange-Traded Funds (ETFs). Despite the nascent nature of research on green hydrogen portfolio performance, this study examines two key green hydrogen ETFs (i.e., HJEN and HDRO) from April 2021–May 2023, aiming at conducting a multifaceted exploration of their performance, isolating and measuring their sensitivity to the primary market factor, and assessing the capabilities of systematic trading strategies to preserve capital and minimize losses during market downturns. The results spotlight lower returns and higher risks in green hydrogen investments compared to conventional equity (proxied by ETFs offering exposure to developed markets—EFA and emerging markets—EEM) and green energy portfolios (proxied by the ETF ICLN). To comprehensively evaluate performance, an array of risk-adjusted metrics, including Std Sharpe, ES Sharpe, VaR Sharpe, Information ratio, Sortino ratio, Treynor ratio, and various downside risk metrics (historical VaR, modified VaR, Expected Shortfall, loss deviation, downside deviation, and maximum drawdown) are employed, offering a nuanced understanding of the investment landscape. Moreover, single-factor models highlight significant systematic market risk, reflected in notably high beta coefficients, negative alphas, and active premia, underscoring the sensitivity of green hydrogen investments to market fluctuations. Despite these challenges, a silver lining emerges as the study demonstrates the efficacy of implementing straightforward Dual Moving Average Crossover (DMAC) trading strategies. These strategies significantly enhance the risk-return profile of green hydrogen portfolios, offering investors a pathway to align financial and social objectives within their equity portfolios. This research is motivated by the need to provide market players, policymakers, and stakeholders with valuable insights into the benefits and risks associated with green hydrogen investment, considering its potential to reshape the global energy landscape. Full article

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13 pages, 1597 KiB

Open AccessArticle

Performance of the Realized-GARCH Model against Other GARCH Types in Predicting Cryptocurrency Volatility

by Rhenan G. S. Queiroz and Sergio A. David

Risks 2023, 11(12), 211; https://doi.org/10.3390/risks11120211 - 06 Dec 2023

Viewed by 1583

Abstract

Cryptocurrencies have increasingly attracted the attention of several players interested in crypto assets. Their rapid growth and dynamic nature require robust methods for modeling their volatility. The Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) model is a well-known mathematical tool for predicting volatility. Nonetheless, [...] Read more.

Cryptocurrencies have increasingly attracted the attention of several players interested in crypto assets. Their rapid growth and dynamic nature require robust methods for modeling their volatility. The Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) model is a well-known mathematical tool for predicting volatility. Nonetheless, the Realized-GARCH model has been particularly under-explored in the literature involving cryptocurrency volatility. This study emphasizes an investigation on the performance of the Realized-GARCH against a range of GARCH-based models to predict the volatility of five prominent cryptocurrency assets. Our analyses have been performed in both in-sample and out-of-sample cases. The results indicate that while distinct GARCH models can produce satisfactory in-sample fits, the Realized-GARCH model outperforms its counterparts in out of-sample forecasting. This paper contributes to the existing literature, since it better reveals the predictability performance of Realized-GARCH model when compared to other GARCH-types analyzed when an out-of-sample case is considered. Full article

(This article belongs to the Special Issue Technology, Digital Transformation, and Financial Economics)

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15 pages, 2108 KiB

Open AccessArticle

From Transition Risks to the Relationship between Carbon Emissions, Economic Growth, and Renewable Energy

by Elisa Di Febo, Eliana Angelini and Tu Le

Risks 2023, 11(12), 210; https://doi.org/10.3390/risks11120210 - 05 Dec 2023

Viewed by 1383

Abstract

Currently, energy consumption has increased exponentially. Using fossil fuels to produce energy generates high shares of carbon dioxide emissions and greenhouse gases. Moreover, financial authorities at the global and European levels have recognized that climate change poses new risks for individual financial institutions [...] Read more.

Currently, energy consumption has increased exponentially. Using fossil fuels to produce energy generates high shares of carbon dioxide emissions and greenhouse gases. Moreover, financial authorities at the global and European levels have recognized that climate change poses new risks for individual financial institutions and financial stability. The analysis contributes to the literature in two critical ways. First, the research attempts to develop a map of the transition risk of the EU. In detail, it defines an indicator that will identify the transition risk the EU bears. Second, it analyzes any relationships between the CO₂ emissions, economic growth, and the renewable energy of each European country from 1995 to 2020, highlighting the short and long-run relationships. The methodology used is the ARDL. The results show the long-run relationship between GDP, renewable energy consumption, and CO₂ emissions is evident. Indeed, economic growth may increase environmental pollution in Europe, while an increase in using renewable energy may reduce CO₂ emissions. Therefore, this implies the trade-off between economic development and CO₂ emissions. Furthermore, the results indicate the difference in the short-run relationship across countries. However, the results demonstrate that the choice of the European Union to increase the use of renewable energies is more than fair. Full article

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24 pages, 459 KiB

Open AccessArticle

Research on the Impact of Digital Inclusive Finance on the Financial Vulnerability of Aging Families

by Xingqi Wang and Zhenhua Mao

Risks 2023, 11(12), 209; https://doi.org/10.3390/risks11120209 - 29 Nov 2023

Cited by 1 | Viewed by 1557

Abstract

In recent years, the issue of population aging has been a challenge for China’s economic and social development. Due to factors such as the imperfect pension security system, the financial vulnerability of families has been greatly impacted by population aging. Digital inclusive finance [...] Read more.

In recent years, the issue of population aging has been a challenge for China’s economic and social development. Due to factors such as the imperfect pension security system, the financial vulnerability of families has been greatly impacted by population aging. Digital inclusive finance is a financial model that utilizes digital technology and innovative approaches to provide financial services to low-income groups and impoverished areas. With the rapid development of the concept of digital inclusive finance, an increasing number of households are beginning to use digital inclusive finance products. It is worth exploring whether this financial model can help alleviate the financial vulnerability of aging families. Therefore, it is of both theoretical and practical significance to study the role of digital inclusive finance in improving the financial vulnerability of aging families. This study assembled unbalanced panel data using both 2016 and 2018 China Household Tracking Survey (CFPS) data and the digital financial inclusion index. An empirical analysis was conducted using the ordered probit panel model. The research findings indicate the following: First, the increasing elderly population intensifies the financial vulnerability of families. Second, digital inclusive finance plays a significant role in improving the financial stability of aging families. Third, digital inclusive finance helps alleviate the impact of population aging on family financial vulnerability by mitigating credit constraints and increasing household income. Fourth, a heterogeneity analysis suggests that in female-headed households, the financial vulnerability caused by population aging is more severe, and the role of digital inclusive finance in improving family financial vulnerability is more prominent. Additionally, the purchase of commercial insurance can effectively alleviate the financial vulnerability of families caused by population aging. Full article

18 pages, 462 KiB

Open AccessArticle

Disentangling Trend Risk and Basis Risk with Functional Time Series

by Yanxin Liu and Johnny Siu-Hang Li

Risks 2023, 11(12), 208; https://doi.org/10.3390/risks11120208 - 28 Nov 2023

Viewed by 1180

Abstract

In recent multi-population stochastic mortality models, one critical scientific issue is the vague distinction between trend risk and population basis risk. In particular, the cross- and auto-correlations between the innovations of the latent factors representing the common trend and the population-specific trends are [...] Read more.

In recent multi-population stochastic mortality models, one critical scientific issue is the vague distinction between trend risk and population basis risk. In particular, the cross- and auto-correlations between the innovations of the latent factors representing the common trend and the population-specific trends are often assumed to be non-existent, although they are possibly statistically significant. While it is theoretically possible to capture such correlations by treating the latent factors as a vector time series, the resulting model would contain a large number of parameters, which may in turn lead to robustness problems. In this paper, we address these issues by the use of the product–ratio model. Contrary to the prevalent assumption of non-existent correlations, the latent factors under the product–ratio model are approximately uncorrelated. This permits us to disentangle trend risk and population basis risk, thereby sparing us from the need to use a heavily parameterized vector time-series process. Compared to the augmented common factor model, our approach demonstrates improved robustness in terms of correlation structures and hedging performance, offering a new perspective on treating cross- and auto-correlations between latent factors in mortality modeling. Full article

(This article belongs to the Special Issue Longevity/Mortality Risk Measurement and Management in Actuarial Sciences)

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25 pages, 555 KiB

Open AccessArticle

Nonlinear Modeling of Mortality Data and Its Implications for Longevity Bond Pricing

by Huijing Li, Rui Zhou and Min Ji

Risks 2023, 11(12), 207; https://doi.org/10.3390/risks11120207 - 28 Nov 2023

Viewed by 1233

Abstract

Human mortality has been improving faster than expected over the past few decades. This unprecedented improvement has caused significant financial stress to pension plan sponsors and annuity providers. The widely recognized Lee–Carter model often assumes linearity in its period effect as an integral [...] Read more.

Human mortality has been improving faster than expected over the past few decades. This unprecedented improvement has caused significant financial stress to pension plan sponsors and annuity providers. The widely recognized Lee–Carter model often assumes linearity in its period effect as an integral part of the model. Nevertheless, deviation from linearity has been observed in historical mortality data. In this paper, we investigate the applicability of four nonlinear time-series models: threshold autoregressive model, Markov switching model, structural change model, and generalized autoregressive conditional heteroskedasticity model for mortality data. By analyzing the mortality data from England and Wales and Italy spanning the years 1900 to 2019, we compare the goodness of fit and forecasting performance of the four nonlinear models. We then demonstrate the implications of nonlinearity in mortality modeling on the pricing of longevity bonds as a practical illustration of our findings. Full article

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18 pages, 537 KiB

Open AccessArticle

On Risk Management of Mortality and Longevity Capital Requirement: A Predictive Simulation Approach

by Shuai Yang and Kenneth Q. Zhou

Risks 2023, 11(12), 206; https://doi.org/10.3390/risks11120206 - 27 Nov 2023

Viewed by 1241

Abstract

In the insurance industry, life insurers are required by regulators to meet capital requirements to avoid insolvency caused by, for example, sudden mortality changes due to the COVID-19 pandemic. To prevent any large movements in this required capital, insurance companies are motivated to [...] Read more.

In the insurance industry, life insurers are required by regulators to meet capital requirements to avoid insolvency caused by, for example, sudden mortality changes due to the COVID-19 pandemic. To prevent any large movements in this required capital, insurance companies are motivated to establish hedging strategies to mitigate the inherent risk exposures they face. Nonetheless, devising and implementing risk mitigation solutions to risk managing capital requirement is frequently impeded by the computational complexities stemming from the extensive simulations required. In this paper, we delve into a simulation quandary concerning the management of solvency capital risk associated with mortality and longevity. More specifically, we introduce a thin-plate regression spline method as a surrogate alternative to the standard nested simulation approach. Using this efficient simulation method, we further investigate hedging strategies that utilize mortality-linked securities coupled with stochastic mortality dynamics. Our simulation results provide a numerical justification to the market-making of mortality-linked securities in the context of mortality and longevity capital risk management. Full article

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14 pages, 396 KiB

Open AccessArticle

Inconsistency in Managers’ Disclosure Tone: The Signalling Perspective

by Azam Pouryousof, Farzaneh Nassirzadeh and Davood Askarany

Risks 2023, 11(12), 205; https://doi.org/10.3390/risks11120205 - 21 Nov 2023

Viewed by 1514

Abstract

This article examines the factors contributing to the disparity in managers’ disclosure tone from a signalling perspective. According to this viewpoint, managers intentionally choose their tone to convey information to the market. To determine the origin of tone inconsistency, we explored the association [...] Read more.

This article examines the factors contributing to the disparity in managers’ disclosure tone from a signalling perspective. According to this viewpoint, managers intentionally choose their tone to convey information to the market. To determine the origin of tone inconsistency, we explored the association between future financial performance (as measured by the rate of return on assets (ROA) and rate of return on equity (ROE)) and future financial risk (as measured by the standard deviation of ROA and ROE) with the tone of management discussion and analyses (MD&As). The Loughran and McDonald dictionaries were utilised to assess managers’ tone in the MD&As. Our dataset consisted of 1510 MD&As from 156 companies listed on the Tehran Stock Exchange, covering 2013 to 2022. Multiple regression analysis was employed, controlling for industry and year fixed effects. The findings revealed a significant relationship between future financial performance, future financial risk, and MD&A tone inconsistency. Thus, the biased tone observed in Iranian managers’ MD&As can be explained by signalling theory. This study contributes to the existing literature by being the first to investigate signalling as a source of inconsistency in managers’ disclosure tone. Full article

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Risks, Volume 11, Issue 12 (December 2023) – 17 articles

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