Risks

35 pages, 1388 KiB

Open AccessArticle

CEO Social Capital and the Value Relevance of Accounting Metrics

by Michael S. Luehlfing, William R. McCumber and Huan Qiu

Risks 2023, 11(4), 78; https://doi.org/10.3390/risks11040078 - 18 Apr 2023

Viewed by 1808

Equity investors value CEO social capital when pricing firm equity. When CEO social capital is high, the value relevance of the book value of equity declines, whereas the value relevance of earnings measures increases. Results are stronger for firms in high-tech industries where [...] Read more.

Equity investors value CEO social capital when pricing firm equity. When CEO social capital is high, the value relevance of the book value of equity declines, whereas the value relevance of earnings measures increases. Results are stronger for firms in high-tech industries where information asymmetries are higher. Social capital may be deconstructed into informational and reputational effects and we report that social capital is a meaningful determinant of value relevance in both scenarios. Results are robust to alternative variable definitions, controls and tests for endogeneity. The results strongly suggest that CEO social capital improves the information environment around firms, benefiting users of accounting metrics. Full article

(This article belongs to the Special Issue Accounting, Financial Reporting, and Disclosure)

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21 pages, 7037 KiB

Open AccessArticle

Optimizing Pension Participation in Kenya through Predictive Modeling: A Comparative Analysis of Tree-Based Machine Learning Algorithms and Logistic Regression Classifier

by Nelson Kemboi Yego, Juma Kasozi and Joseph Nkurunziza

Risks 2023, 11(4), 77; https://doi.org/10.3390/risks11040077 - 18 Apr 2023

Viewed by 2120

Abstract

Pension plans play a vital role in the economy by impacting savings, consumption, and investment allocation. Despite declining mortality rates and increasing life expectancy, pension enrollment remains low, affecting the long-term financial stability and well-being of populations. To address this issue, this study [...] Read more.

Pension plans play a vital role in the economy by impacting savings, consumption, and investment allocation. Despite declining mortality rates and increasing life expectancy, pension enrollment remains low, affecting the long-term financial stability and well-being of populations. To address this issue, this study was conducted to explore the potential of predictive modeling techniques in improving pension participation. The study utilized three tree-based machine learning algorithms and a logistic regression classifier to analyze data from a nationally representative 2019 Kenya FinAccess Household Survey. The results indicated that ensemble tree-based models, particularly the random forest model, were the most effective in predicting pension enrollment. The study identified the key factors that influenced enrollment, such as National Health Insurance Fund (NHIF) usage, monthly income, and bank usage. The findings suggest that collaboration among the NHIF, banks, and pension providers is necessary to increase pension uptake, along with increased financial education for citizens. The study provides valuable insight for promoting and optimizing pension participation. Full article

(This article belongs to the Special Issue Machine Learning and Artificial Intelligence in Non-life Insurance: Theory, Methods and Applications)

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25 pages, 707 KiB

Open AccessArticle

The Impact of Intellectual Capital on the Firm Performance of Russian Manufacturing Companies

by Angi Skhvediani, Anastasia Koklina, Tatiana Kudryavtseva and Diana Maksimenko

Risks 2023, 11(4), 76; https://doi.org/10.3390/risks11040076 - 13 Apr 2023

Cited by 1 | Viewed by 2871

Abstract

The manufacturing industry makes a significant contribution to Russia’s GDP and exports, but it faces problems that hinder its development. The aim of this study is to estimate the relationship between intellectual capital and performance indicators of Russian manufacturing companies. The study analysed [...] Read more.

The manufacturing industry makes a significant contribution to Russia’s GDP and exports, but it faces problems that hinder its development. The aim of this study is to estimate the relationship between intellectual capital and performance indicators of Russian manufacturing companies. The study analysed a sample of 23,494 observations of Russian manufacturing companies for the 2017–2020 period. The value-added intellectual coefficient (VAIC) and its components were used to evaluate the impact of intellectual capital on firm performance using polled ordinary least squares, fixed, and random effects models. Intellectual capital significantly and positively affects the performance of companies in both structural and human terms—both through the integrated coefficient VAIC and in the context of individual components of intellectual capital. However, the impact of structural and human capital on performance indicators is significantly lower than the impact of capital employed. There is a distinct focus of enterprises on making profit through the use of company assets, while in the case of Russian manufacturing companies, the potential for profit generation from structural and human capital remains unfulfilled. Full article

(This article belongs to the Special Issue Risk Analysis and Management in the Digital and Innovation Economy)

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25 pages, 539 KiB

Open AccessArticle

Underwriting Cycles in Property-Casualty Insurance: The Impact of Catastrophic Events

by Annette Hofmann and Cristina Sattarhoff

Risks 2023, 11(4), 75; https://doi.org/10.3390/risks11040075 - 11 Apr 2023

Viewed by 2524

Abstract

This paper challenges the question of existence and predictability of underwriting cycles in the U.S. property and casualty insurance industry. Using an approach in the frequency domain, we demonstrate the existence of a hidden periodic component in annual aggregated loss ratios. The data [...] Read more.

This paper challenges the question of existence and predictability of underwriting cycles in the U.S. property and casualty insurance industry. Using an approach in the frequency domain, we demonstrate the existence of a hidden periodic component in annual aggregated loss ratios. The data support an underwriting cycle length of 8–9 years. Going beyond previous research and studying almost 30 years of quarterly underwriting data, we can improve forecasting performance by (dis)connecting cycles and catastrophic events. Superior out-of-sample forecast results from models with intervention variables flagging the time point of catastrophic outbreaks is achieved in terms of mean squared/absolute forecast errors. We evaluate model confidence sets containing the most accurate model with a certain confidence level. The analysis suggests that reliable forecasts can be achieved net of the irregular major peaks in loss distributions that arise from natural catastrophes as well as unusual “black swan” events. Full article

(This article belongs to the Special Issue Risks: Feature Papers 2023)

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11 pages, 995 KiB

Open AccessArticle

Financial Risk Management of the Russian Economy during the COVID-19 Pandemic

by Sergey Kolchin, Nadezda Glubokova, Mikhail Gordienko, Galina Semenova and Milyausha Khalilova

Risks 2023, 11(4), 74; https://doi.org/10.3390/risks11040074 - 11 Apr 2023

Cited by 2 | Viewed by 1801

Abstract

The research objects are the tax and budgetary policies of the Russian Federation. In this research, financial (budgetary) risks are understood as a decrease in the balance of the state (national) budget resulting from a reduction in revenues or an increase in expenditures. [...] Read more.

The research objects are the tax and budgetary policies of the Russian Federation. In this research, financial (budgetary) risks are understood as a decrease in the balance of the state (national) budget resulting from a reduction in revenues or an increase in expenditures. This research considers production in the main sectors of the economy as a key factor of financial risk during the COVID-19 pandemic. The research aims to analyze the main directions of the budgetary and tax policy of the Russian Federation that aimed at supporting the economy and the population during the spread of COVID-19, which is especially relevant in connection with the expected recession in a number of sectors of the economy and a decrease in the level of employment and, accordingly, the well-being of citizens. In these conditions, it is necessary to adjust the budgetary and tax policy to preserve the state’s social obligations and expand social and economic support for businesses and citizens to smooth out the negative consequences of the impact of restrictive measures. The authors applied systemic and institutional approaches and statistical methods. The main results of the research reflect the need to (1) implement support measures (tax and budgetary incentives) for small and medium-sized enterprises, on which the crisis provoked by the COVID-19 pandemic has had the most destructive impact, and (2) to expand the volume of budgetary financing of social programs for financial risk management of the Russian economy during the COVID-19 pandemic. Compositionally, the article consists of the following sections: the introduction, which provides an overview of the publication activity in the field of financing measures to overcome the spread of COVID-19 and substantiates the relevance and purpose of the study; the literature review, which lists modern authors whose works were aimed at studying similar issues as well as the methodological apparatus used by them, which are suitable for adaptation; the section ‘materials and methods’, which provides more adaptive methods of other people’s research and the authors selected in accordance with them are listed; the results section, in which the authors present the main array of statistical data, which is then discussed. At the end of the article, the authors draw conclusions about the applied fiscal policy tools that can be used effectively in the new economic reality. Full article

(This article belongs to the Special Issue The COVID-19 Crisis: Datasets and Data Analysis to Reduce Risks)

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17 pages, 483 KiB

Open AccessArticle

Whoops! It Happened Again: Demand for Insurance That Covers Multiple Risks

by Liang Hong, Harris Schlesinger and Boyi Zhuang

Risks 2023, 11(4), 73; https://doi.org/10.3390/risks11040073 - 10 Apr 2023

Viewed by 1131

Abstract

This article studies insurance demand in a two-period framework in which an individual faces risks in both current and future periods. Models for insurance with and without the presence of endogenous saving are both discussed. In contrast to what most literature suggests, when [...] Read more.

This article studies insurance demand in a two-period framework in which an individual faces risks in both current and future periods. Models for insurance with and without the presence of endogenous saving are both discussed. In contrast to what most literature suggests, when decisions on insurance and saving are made separately, insurance alone does not always unambiguously reduce risk, and decision makers might demand more insurance when there is a positive loading on the premium than when the insurance price is actuarially fair. We compare the demand for insurance in our framework with that in a two-period model where risk is concentrated in the second period and derive the conditions under which these demands differ. We examine the effects of risk aversion and derive the conditions under which a more risk-averse individual demands more or less insurance. Full article

(This article belongs to the Special Issue Frontiers in Quantitative Finance and Risk Management)

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22 pages, 908 KiB

Open AccessArticle

Heuristic Biases as Mental Shortcuts to Investment Decision-Making: A Mediation Analysis of Risk Perception

by Jinesh Jain, Nidhi Walia, Himanshu Singla, Simarjeet Singh, Kiran Sood and Simon Grima

Risks 2023, 11(4), 72; https://doi.org/10.3390/risks11040072 - 03 Apr 2023

Cited by 3 | Viewed by 7343

Abstract

In the last two decades, research on behavioural biases has grown dramatically, fuelled by rising academic interest and zeal for publication. The present study explores the mediating role of risk perception on the relationship between heuristic biases and individual equity investors’ decision-making. The [...] Read more.

In the last two decades, research on behavioural biases has grown dramatically, fuelled by rising academic interest and zeal for publication. The present study explores the mediating role of risk perception on the relationship between heuristic biases and individual equity investors’ decision-making. The study uses Partial Least Square Structural Equation Modelling (PLS–SEM) to examine the survey data from 432 individual equity investors trading at the National Stock Exchange (NSE) in India. Risk perception is found to play a partial mediating role in the relationship amid overconfidence bias and investment decision-making, availability bias and investment decision-making, gamblers’ fallacy bias and investment decision-making and anchoring bias and investment decision-making, whereas it is found to play the full mediating role in the relationship between representativeness bias and investment decision-making. The result of the present study provides valuable insights into the different behavioural biases of capital market participants and other stakeholders such as equity investors, financial advisors, and policymakers. The present study solely relied on the heuristic biases of individual equity investors. However, in the real world, many other factors may impact the investment decision of individual equity investors. This has been considered a limitation of the study. The present study solely relied on the heuristic biases of individual equity investors. However, in the real world, many other factors may impact the investment decision of individual equity investors. This has been considered a limitation of the study. Full article

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17 pages, 4296 KiB

Open AccessArticle

Machine Learning Algorithm for Mid-Term Projection of the EU Member States’ Indebtedness

by Silvia Zarkova, Dimitar Kostov, Petko Angelov, Tsvetan Pavlov and Andrey Zahariev

Risks 2023, 11(4), 71; https://doi.org/10.3390/risks11040071 - 03 Apr 2023

Cited by 2 | Viewed by 1928

Abstract

The main research question addressed in the paper is related to the possibility of medium-term forecasting of the public debts of the EU member states. The analysis focuses on a broad range of indicators (macroeconomic, fiscal, monetary, global, and convergence) that influence the [...] Read more.

The main research question addressed in the paper is related to the possibility of medium-term forecasting of the public debts of the EU member states. The analysis focuses on a broad range of indicators (macroeconomic, fiscal, monetary, global, and convergence) that influence the public debt levels of the EU member states. A machine learning prediction model using random forest regression was approbated with the empirical data. The algorithm was applied in two iterations—a primary iteration with 33 indicators and a secondary iteration with the 8 most significant indicators in terms of their influence and forecasting importance regarding the development of public debt across the EU. The research identifies a change in the medium term (2023–2024) in the group of the four most indebted EU member states, viz., that Spain will be replaced by France, which is an even more systemic economy, and will thus increase the group’s share of the EU’s GDP. The results indicate a logical scenario of rising interest rates with adverse effects for the fiscal imbalances, which will require serious reforms in the public sector of the most indebted EU member states. Full article

(This article belongs to the Special Issue Risk Management in Economics and Finance for Sustainable Development in the Digital Ecosystem)

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5 pages, 275 KiB

Open AccessEditorial

Data Analysis for Risk Management—Economics, Finance and Business: New Developments and Challenges

by Krzysztof Jajuga

Risks 2023, 11(4), 70; https://doi.org/10.3390/risks11040070 - 30 Mar 2023

Viewed by 1647

Abstract

The development of the theory and practice of risk management is closely related to the emergence of different risks [...] Full article

(This article belongs to the Special Issue Data Analysis for Risk Management – Economics, Finance and Business)

19 pages, 1037 KiB

Open AccessArticle

Validating the Financial Literacy Index of Hungarian SMEs during the COVID-19 Pandemic and the Russian–Ukrainian War

by Robert Toth, Richard Kasa and Csaba Lentner

Risks 2023, 11(4), 69; https://doi.org/10.3390/risks11040069 - 29 Mar 2023

Cited by 1 | Viewed by 2738

Abstract

The effects of the COVID-19 pandemic and the Russian–Ukrainian war have had a significant impact on economies around the world, with pivotal implications for the activities of companies. The issue of corporate financial literacy has been within our scope of interest for a [...] Read more.

The effects of the COVID-19 pandemic and the Russian–Ukrainian war have had a significant impact on economies around the world, with pivotal implications for the activities of companies. The issue of corporate financial literacy has been within our scope of interest for a matter of years now, and this study aims at re-enforcing our previous overall theoretical and literacy-based analysis from a methodological approach. We use our own previous databases to explore and analyze the importance of corporate financial literacy, taking into account the economic factors inside and outside the organization that affect the businesses. For this, a confirmative factor analysis (CFA) model has been created. The article aims at two things with this. On the one hand, we intend to introduce the wider scope of the fit tests applicable in the CFA, thus giving a direction to other authors. It also allows for adequate verification for their models, while at the same time conducting the fit test for our corporate financial literacy model as well as a valid model framework suitable for making measurements and deductions. With the resulting model, this paper aims to examine the corporate financial literacy, the current economic challenges, and the issues faced by managers during crises. In addition to all this, with our article, we also want to make some contribution to the methodology of empirical data analysis: in the article we collect the fit tests that can be used to validate confirmatory factor models, the way they are determined, and most importantly, we try to sort out the literature approaches to the acceptable values of these tests, giving the reader a kind of guide and a reference base. The results of the research identify response measures that can contribute to increasing companies’ resilience based on the principles of financial awareness. Full article

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22 pages, 478 KiB

Open AccessArticle

The Nexus of Competition, Loan Quality, and Ownership Structure for Risk-Taking Behaviour

by Syed Moudud-Ul-Huq, Md. Abdul Halim, Farid Ahammad Sobhani, Ziaul Karim and Zinnatun Nesa

Risks 2023, 11(4), 68; https://doi.org/10.3390/risks11040068 - 29 Mar 2023

Cited by 2 | Viewed by 1872

Abstract

“The core purpose is to explore the relationship between competition, loan quality, ownership structure, and risk for MENA economies.” In addition, this study examines the financial stability level of dual banking and explores the bidirectional causality of competition and risk concerning the impact [...] Read more.

“The core purpose is to explore the relationship between competition, loan quality, ownership structure, and risk for MENA economies.” In addition, this study examines the financial stability level of dual banking and explores the bidirectional causality of competition and risk concerning the impact of ownership structure. This study uses 748 observations from 2011 to 2020 in MENA countries. The Generalized Method of Moments (GMM) is an econometric technique used to estimate the parameters of a statistical model. The study findings indicate a negative (positive) relationship between MENA bank competition and risk (financial stability). It indicates that lower bank competition reduces bank credit risk and increases financial stability in MENA countries. Regarding ownership structure, Islamic banks display a stronger position in MENA economies than that of Commercial banks and Specialized Government Institutions. In contrast, specialized government institutions are riskier than commercial banks and Islamic banks. Loan quality shows the two-way causality between the degree to which banks compete and the quality of their loans to customers in the MENA markets. This study sets itself apart from other studies by creating a new segmented literature review portion. Finally, a significant policy implication is provided for academics, researchers, and policymakers interested in applying these findings. Full article

16 pages, 433 KiB

Open AccessArticle

A Semi-Markov Dynamic Capital Injection Problem for Distressed Banks

by Luca Di Persio, Luca Prezioso and Yilun Jiang

Risks 2023, 11(4), 67; https://doi.org/10.3390/risks11040067 - 28 Mar 2023

Viewed by 1023

Abstract

Our study investigates the optimal dividend strategy for a bank, taking into account the potential for government capital injections. We explore different types of government interventions, such as liberal, transparent, or uncertain strategies, and consider both single and multiple types of interventions. Our [...] Read more.

Our study investigates the optimal dividend strategy for a bank, taking into account the potential for government capital injections. We explore different types of government interventions, such as liberal, transparent, or uncertain strategies, and consider both single and multiple types of interventions. Our approach differs from others as it focuses on interventions that aim to maintain the overall stability of the financial system, rather than just addressing banks that have already sought government assistance or are in dire need of it. Specifically, we focus on situations where the government is more likely to assist banks that have not requested its intervention or that are not too difficult to save. To accomplish this, we conduct a comprehensive examination of all possible scenarios involving a single, one-time capital injection and derive explicit solutions for the associated optimal control problem. Furthermore, we expand the model to include semi-Markov dynamic capital injection processes and show that the optimal control is the unique viscosity solution of a Hamilton–Jacobi–Bellman equation. The government’s strategy also takes into account the bank’s solvency and any past government interventions. Full article

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23 pages, 488 KiB

Open AccessArticle

Economic Uncertainty and Firms’ Capital Structure: Evidence from China

by Chenglin Gao and Takuji W. Tsusaka

Risks 2023, 11(4), 66; https://doi.org/10.3390/risks11040066 - 27 Mar 2023

Cited by 2 | Viewed by 2586

Abstract

This article assesses the effects of economic uncertainty on the corporate capital structure of Chinese-listed firms using a panel dataset of 1138 firms with A-shares traded on the Shanghai Stock Exchange and Shenzhen Stock Exchange for the period 2006–2020 and fixed-effect regression analysis. [...] Read more.

This article assesses the effects of economic uncertainty on the corporate capital structure of Chinese-listed firms using a panel dataset of 1138 firms with A-shares traded on the Shanghai Stock Exchange and Shenzhen Stock Exchange for the period 2006–2020 and fixed-effect regression analysis. Economic uncertainty had a negative influence on Chinese firms’ debt ratios, especially for non-state-owned enterprises. Furthermore, firms’ leverage decreased on average during the 2008 Great Recession, whereas it increased during the 2018–2019 US–China Trade War and the 2020 COVID-19 pandemic. The findings provide quantitative evidence of the effects of economic uncertainty on the capital structure of firms in a transition economy. Full article

(This article belongs to the Special Issue Financial Risk Management in Companies during the World Crisis)

24 pages, 489 KiB

Open AccessArticle

A Comparison of Competing Asset Pricing Models: Empirical Evidence from Pakistan

by Eleftherios Thalassinos, Naveed Khan, Shakeel Ahmed, Hassan Zada and Anjum Ihsan

Risks 2023, 11(4), 65; https://doi.org/10.3390/risks11040065 - 24 Mar 2023

Cited by 1 | Viewed by 2709

Abstract

In recent years, the rapid and significant development of emerging markets has globally led to insight from potential investors and academicians seeking to assess these markets in terms of risk inheritance. Therefore, this study aims to explore the validity and applicability of the [...] Read more.

In recent years, the rapid and significant development of emerging markets has globally led to insight from potential investors and academicians seeking to assess these markets in terms of risk inheritance. Therefore, this study aims to explore the validity and applicability of the capital asset pricing model (henceforth CAPM) and multi-factor models, namely Fama–French models, in Pakistan’s stock market for the period of June 2010–June 2020. This study collects data on 173 non-financial firms listed on the Pakistan stock exchange, namely the KSE-100 index, and follows Fama-MacBeth’s regression methodology for empirical estimation. The empirical findings of this study conclude that small portfolios (small-size companies) earn considerably higher returns than big portfolios (large-size companies). Ultimately, the risk associated with portfolio returns is reported to be higher for small portfolios (small-size companies) than for big portfolios (large-size companies). According to the regression output, the CAPM was found to be valid for explaining the market risk premium above the risk-free rate. Similarly, the FF three-factor model was found to be valid for explaining time-series variation in excess portfolio returns. Later, we added human capital into FF three- and five-factor models. This study found that the human capital base six-factor model outperformed the other competing asset pricing models. The findings of this study indicate that small portfolios (small-size companies) earn more returns than big portfolios (large-size companies) to reward the investor for taking extra risks. Investors may benefit by timing their investments to maximize stock returns. Company investment in human capital adds reliable information, replicates the value of the company and, in the long term, helps investors make rational decisions. Full article

(This article belongs to the Special Issue Computational Technologies for Financial Security and Risk Management)

16 pages, 620 KiB

Open AccessArticle

Asymptototic Expected Utility of Dividend Payments in a Classical Collective Risk Process

by Sebastian Baran, Corina Constantinescu and Zbigniew Palmowski

Risks 2023, 11(4), 64; https://doi.org/10.3390/risks11040064 - 23 Mar 2023

Viewed by 1137

Abstract

We find the asymptotics of the value function maximizing the expected utility of discounted dividend payments of an insurance company whose reserves are modeled as a classical Cramér risk process, with exponentially distributed claims, when the initial reserves tend to infinity. We focus [...] Read more.

We find the asymptotics of the value function maximizing the expected utility of discounted dividend payments of an insurance company whose reserves are modeled as a classical Cramér risk process, with exponentially distributed claims, when the initial reserves tend to infinity. We focus on the power and logarithmic utility functions. We also perform some numerical analysis. Full article

(This article belongs to the Special Issue Interplay between Financial and Actuarial Mathematics II)

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