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Journal Description

Risks

Risks is an international, scholarly, peer-reviewed, open access journal for research and studies on insurance and financial risk management. Risks is published monthly online by MDPI.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High visibility: indexed within Scopus, ESCI (Web of Science), EconLit, EconBiz, RePEc, and other databases.
Journal Rank: JCR - Q2 (Business, Finance) / CiteScore - Q1 (Economics, Econometrics and Finance (miscellaneous))
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.5 days after submission; acceptance to publication is undertaken in 4.6 days (median values for papers published in this journal in the second half of 2024).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers for a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done

Impact Factor: 2.0 (2023); 5-Year Impact Factor: 1.7 (2023)

Imprint Information Journal Flyer Open Access ISSN: 2227-9091

Latest Articles

19 pages, 784 KiB

Open AccessArticle

Determinants of Firms’ Propensity to Use Intercorporate Loans: Empirical Evidence from India

by Biswajit Ghose, Prasenjit Roy, Yeshi Ngima, Kiran Gope, Pankaj Kumar Tyagi, Premendra Kumar Singh and Asokan Vasudevan

Risks 2025, 13(4), 71; https://doi.org/10.3390/risks13040071 (registering DOI) - 2 Apr 2025

Several studies have investigated the determinants of firms’ capital structure choices. Though an intercorporate loan is an essential source of corporate debt, there are no studies that examine the determinants of firms’ preference to use the intercorporate loan as a source of debt. [...] Read more.

Several studies have investigated the determinants of firms’ capital structure choices. Though an intercorporate loan is an essential source of corporate debt, there are no studies that examine the determinants of firms’ preference to use the intercorporate loan as a source of debt. This study examines the relevance of the conventional capital structure determinants in explaining firms’ tendency to use intercorporate loans. The study is based on a dataset of 53,112 firm-year observations comprising 3739 non-financial listed Indian firms for 21 years from 2002 to 2022. The random effect logistic regression model is used to investigate the objectives. The conventional capital structure determinants are relevant in explaining firms’ decisions to use intercorporate loans. Firm size, asset tangibility, and earnings volatility favorably influence the tendency to use intercorporate loans, whereas profitability, growth, uniqueness, dividend payment, ownership concentration, and foreign promoter holdings adversely affect the same. The results reveal that the influence of firm size, uniqueness, earnings volatility, and ownership concentration are not unidirectional for group-affiliated and standalone firms. The findings are mostly consistent with the arguments of conventional capital structure theories. The results of this study will be pragmatic for financial managers in their capital structure decisions. Full article

(This article belongs to the Special Issue Valuation Risk and Asset Pricing)

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27 pages, 497 KiB

Open AccessArticle

Minimal Entropy and Entropic Risk Measures: A Unified Framework via Relative Entropy

by Moritz Sohns

Risks 2025, 13(4), 70; https://doi.org/10.3390/risks13040070 - 1 Apr 2025

We introduce a new coherent risk measure, the minimal-entropy risk measure, which is built on the minimal-entropy

σ

-martingale measure—a concept inspired by the well-known minimal-entropy martingale measure used in option pricing. While the minimal-entropy martingale measure is commonly used for pricing and [...] Read more.

We introduce a new coherent risk measure, the minimal-entropy risk measure, which is built on the minimal-entropy

σ

-martingale measure—a concept inspired by the well-known minimal-entropy martingale measure used in option pricing. While the minimal-entropy martingale measure is commonly used for pricing and hedging, the minimal-entropy

σ

-martingale measure has not previously been studied, nor has it been analyzed as a traditional risk measure. We address this gap by clearly defining this new risk measure and examining its fundamental properties. In addition, we revisit the entropic risk measure, typically expressed through an exponential formula. We provide an alternative definition using a supremum over Kullback–Leibler divergences, making its connection to entropy clearer. We verify important properties of both risk measures, such as convexity and coherence, and extend these concepts to dynamic situations. We also illustrate their behavior in scenarios involving optimal risk transfer. Our results link entropic concepts with incomplete-market pricing and demonstrate how both risk measures share a unified entropy-based foundation. Full article

(This article belongs to the Special Issue Stochastic Modelling in Financial Mathematics, 2nd Edition)

24 pages, 1066 KiB

Open AccessArticle

Interest Rate Sensitivity of Callable Bonds and Higher-Order Approximations

by Scott S. Dow and Stefanos C. Orfanos

Risks 2025, 13(4), 69; https://doi.org/10.3390/risks13040069 - 1 Apr 2025

Certain fixed-income securities, such as callable bonds and mortgage-backed securities subject to prepayment, typically exhibit negative convexity at low yields and cannot be adequately immunized through duration and convexity-matching alone. To address this residual risk, we examine the concepts of bond tilt and [...] Read more.

Certain fixed-income securities, such as callable bonds and mortgage-backed securities subject to prepayment, typically exhibit negative convexity at low yields and cannot be adequately immunized through duration and convexity-matching alone. To address this residual risk, we examine the concepts of bond tilt and bond agility. We provide explicit calculations and derive several approximation formulas that incorporate higher-order terms. With the help of these methods, we are able to track the price-yield dynamics of callable bonds remarkably well, achieving mean absolute errors below 2.5% across a wide variety of callable bonds for parallel yield shifts of up to ±200 basis points. Full article

(This article belongs to the Special Issue Financial Risk, Actuarial Science, and Applications of AI Techniques)

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21 pages, 385 KiB

Open AccessArticle

Nonlinear Nexus Between ESG Scores and Corporate Performance of Insurance Companies in the MENAT Region: Moderating the Effect of Institutional Quality

by Rewayda Tobar

Risks 2025, 13(4), 68; https://doi.org/10.3390/risks13040068 - 1 Apr 2025

Although the relationship between ESG performance and firm performance has been the subject of several studies, the nonlinear relationship between ESG performance and the corporate performance of insurance companies remains less explored, specifically in the Middle East, North Africa, and Turkey (MENAT) region. [...] Read more.

Although the relationship between ESG performance and firm performance has been the subject of several studies, the nonlinear relationship between ESG performance and the corporate performance of insurance companies remains less explored, specifically in the Middle East, North Africa, and Turkey (MENAT) region. Moreover, the moderating effect of institutional quality on this relationship has not been examined. To fill this gap, this paper investigates the nonlinear impact of ESG performance on the financial performance of insurance companies in the MENAT region, as well as the moderating effect of institutional quality. To achieve this, a sample of 31 insurance companies located in the seven MENAT countries was constructed over the period 2017–2022. The sample was selected based on the completeness and availability of ESG-related data. This ensured a standardized dataset to enhance the reliability of the results. To estimate this relationship, the System Generalized Method of Moments (SGMM) was used. This technique was used to address endogeneity issues. The empirical results indicate that the performance of the insurance companies is better for those with better ESG performance. Moreover, the quality of institutions is an even more important factor in enhancing the ESG practices–corporate performance nexus. More in-depth analysis is needed to show how these various relationships might be altered with ESG criteria. The findings of this research would, therefore, be beneficial to insurers in terms of an increased understanding of how effective integration of ESG practices, both at the institutional and company level, could be streamlined to enhance their long-term competitiveness and profitability. Full article

24 pages, 696 KiB

Open AccessArticle

ESG Controversies and Firm Investment Efficiency: Impact and Mechanism Examination

by Shijin Ma and Tao Ma

Risks 2025, 13(4), 67; https://doi.org/10.3390/risks13040067 - 1 Apr 2025

In the context of increasingly severe global climate change, both companies and investors are placing greater emphasis on investment philosophies centered around environmental protection, social responsibility, and corporate governance (ESG). This paper, based on data from 847 Chinese A-share listed companies over the [...] Read more.

In the context of increasingly severe global climate change, both companies and investors are placing greater emphasis on investment philosophies centered around environmental protection, social responsibility, and corporate governance (ESG). This paper, based on data from 847 Chinese A-share listed companies over the period 2007–2022, employs a two-way fixed effects model to investigate the relationship between ESG controversies and firm investment efficiency. The results indicate that ESG controversies significantly reduce overall firm investment efficiency. Further analysis reveals that ESG controversies affect investment efficiency by exacerbating agency costs and reducing audit quality. Meanwhile, financing constraints and robust internal control quality mitigate these negative effects. Heterogeneity analysis shows that the impact is more pronounced for firms with higher pollution levels, non-state-owned enterprises, those with higher analyst coverage, and firms with lower levels of digitalization. The findings have significant implications for encouraging companies to fulfill their social responsibilities and promote high-quality economic development. Full article

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25 pages, 2502 KiB

Open AccessArticle

Transition Risk in Climate Change: A Literature Review

by Elisa Di Febo and Eliana Angelini

Risks 2025, 13(4), 66; https://doi.org/10.3390/risks13040066 - 28 Mar 2025

Climate risk is the negative effect of climate change on several aspects of the environment, business, and society. There are two categories of climate risks: physical risks include direct impacts due to extreme events and chronic changes due to climate modifications that have [...] Read more.

Climate risk is the negative effect of climate change on several aspects of the environment, business, and society. There are two categories of climate risks: physical risks include direct impacts due to extreme events and chronic changes due to climate modifications that have become commonplace; the transition risk arises from the economic and regulatory adjustments required to shift toward reducing greenhouse gas emissions and the transition to renewable energy. The problem, in financial terms, is the correct assessment and quantification of transition risk, as it is not univocal in the literature. This research aims to provide a literature review on transition risk that permits filling this gap and identifying the proxies used for its representation and evaluation. Moreover, the analysis considers the critical aspect of the connection between transition and credit risk, as firms exposed to high transition risks may face challenges in maintaining creditworthiness. Results highlight the most commonly used proxies, including carbon pricing, CO₂ or GHG emissions, and metrics from various databases. However, the findings emphasize the importance of integrating these indicators with broader factors, such as a company’s negative environmental impacts (e.g., waste production and water usage) and delays in technological adaptation from a forward-looking perspective. Full article

(This article belongs to the Special Issue Integrating New Risks into Traditional Risk Management)

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25 pages, 1023 KiB

Open AccessArticle

The Exponential Dispersion Family (EDF) Chain Ladder and Data Granularity

by Greg Taylor

Risks 2025, 13(4), 65; https://doi.org/10.3390/risks13040065 - 27 Mar 2025

This paper is concerned with the choice of data granularity for application of the EDF (Exponential Dispersion Family) chain ladder model to forecast a loss reserve. As the duration of individual accident and development periods is decreased, the number of data points increases, [...] Read more.

This paper is concerned with the choice of data granularity for application of the EDF (Exponential Dispersion Family) chain ladder model to forecast a loss reserve. As the duration of individual accident and development periods is decreased, the number of data points increases, but the volatility of each point increases. This leads to a question as to whether a decrease in time unit leads to an increase or decrease in the variance of the loss reserve estimate. Is there an optimal granularity with respect to the variance of the loss reserve? A preliminary question is that of whether an EDF chain ladder that is valid for one duration (here called mesh size) remains so for another. The conditions under which this is so are established. There are various ways in which the mesh size of a data triangle may be varied. The paper identifies two of particular interest. For each of these two types of variation, the effect on variance of loss reserve is studied. Subject to some technical qualifications, the conclusion is that an increase in mesh size always increases the variance. It follows that one should choose a very high degree of granularity in order to maximize efficiency of loss reserve forecasting. Full article

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41 pages, 897 KiB

Open AccessArticle

Do Board Characteristics Matter with Greenwashing? An Investigation in the Financial Sector with the Integration of Entropy Weight and TOPSIS Multicriteria Decision-Making Methods

by Eleni Poiriazi, Georgia Zournatzidou and George Konteos

Risks 2025, 13(4), 64; https://doi.org/10.3390/risks13040064 - 27 Mar 2025

Financial industry executives are sincerely concerned about the potential effects of greenwashing on their organizations. The primary objective of this research is to investigate the impact of board features on greenwashing and the strategies that executives may develop to mitigate the effects of [...] Read more.

Financial industry executives are sincerely concerned about the potential effects of greenwashing on their organizations. The primary objective of this research is to investigate the impact of board features on greenwashing and the strategies that executives may develop to mitigate the effects of corporate washing phenomena. A novel set of criteria was evaluated for 359 listed European financial institutions. Data were acquired from the Refinitiv Eikon database for the Fiscal Year 2024. The entropy weight and TOPSIS multicriteria decision-making methodologies were used to assess the data. These assist us in determining the relative importance of each chosen criteria about the board’s attributes and their impact on greenwashing. The study indicates that governance is the primary factor affecting greenwashing. Furthermore, findings indicate that the board of directors significantly influences the increased prevalence of greenwashing among financial firms. This suggests that the relationship between board size and greenwashing is debatable. The problem of greenwashing has primarily elevated the standards for evaluating board effectiveness and conflicts of interest, which are listed third on the list. The study results may inform the establishment of a new research agenda in the examined area. Full article

(This article belongs to the Special Issue ESG and Greenwashing in Financial Institutions: Meet Risk with Action)

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18 pages, 1003 KiB

Open AccessArticle

Evaluating Financial Performance of Airline Companies Through Liquidity and Debt Ratios: An Accounting Approach

by Faizah Alsulami

Risks 2025, 13(4), 63; https://doi.org/10.3390/risks13040063 - 26 Mar 2025

This research indicates that accounting is essential for assessing South Asian airline companies via financial ratio analysis from 2011 to 2022. The accounting measurements delineate informing and facilitating strategic decision-making from 2011 to 2022. The analysis utilizing GARCH and PARCH models indicates that [...] Read more.

This research indicates that accounting is essential for assessing South Asian airline companies via financial ratio analysis from 2011 to 2022. The accounting measurements delineate informing and facilitating strategic decision-making from 2011 to 2022. The analysis utilizing GARCH and PARCH models indicates that liquidity ratios have a positive impact on financial performance, supported by statistically significant evidence (p < 0.05) under both symmetric and asymmetric conditions. Effective liquidity management and the strategic implementation of debt through accounting practices should be prioritized, as they enhance financial outcomes for South Asian airlines while adhering to long-term accounting standards. Future research should examine the responses of various airlines to these ratios, considering external factors, as this will yield valuable insights to enhance financial practices and promote aviation development in the region. Full article

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28 pages, 4029 KiB

Open AccessSystematic Review

Integrative Analysis of Traditional and Cash Flow Financial Ratios: Insights from a Systematic Comparative Review

by Dimitra Seretidou, Dimitrios Billios and Antonios Stavropoulos

Risks 2025, 13(4), 62; https://doi.org/10.3390/risks13040062 - 23 Mar 2025

This systematic review analyzes and compares the predictive power between traditional financial ratios and cash flow-based ratios in estimating performance. Although traditional ratios of return on assets and debt to equity have received extensive application, cash flow ratios are increasingly valued by their [...] Read more.

This systematic review analyzes and compares the predictive power between traditional financial ratios and cash flow-based ratios in estimating performance. Although traditional ratios of return on assets and debt to equity have received extensive application, cash flow ratios are increasingly valued by their dynamic insights into both liquidity and financial health. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, this review systematically analyzes 21 studies spread across various industries and regions. The results reveal that cash flow ratios usually dominate the traditional metrics during forecasting financial performance, especially in the presence of the use of machine learning models. Among the identified variables of the logistic regression model and gradient boosting model predictors, key indicators are those showing the return on investment, the current ratio, and the debt-to-asset ratio. The bottom line of the findings is that a combination of cash flow and traditional ratios gives a better understanding of a company’s financial stability. These results may serve as a starting point for investors, regulators, and entrepreneurs and may further facilitate informed decisions with a reduced chance of miscalculations that enhance proactive financial planning. In addition, future prediction models should integrate non-financial factors such as governance quality and market conditions to enhance financial health assessments. Additionally, longitudinal studies examining the evolution of financial ratios over time, along with hybrid statistical and machine learning approaches, can improve forecasting accuracy. Integrating cutting-edge analytical tools with the strength of financial metrics gives this study actionable insights that allow stakeholders to understand financial performance in a more nuanced sense. Full article

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27 pages, 463 KiB

Open AccessFeature PaperArticle

An Optional Semimartingales Approach to Risk Theory

by Mahdieh Aminian Shahrokhabadi, Alexander Melnikov and Andrey Pak

Risks 2025, 13(4), 61; https://doi.org/10.3390/risks13040061 - 21 Mar 2025

This paper aims to develop optional semimartingale methods in risk theory to allow for a larger class of risk models. Optional semimartingales are left-continuous with right-limit stochastic processes defined on a probability space where the usual conditions—completeness and right-continuity of the filtration—are not [...] Read more.

This paper aims to develop optional semimartingale methods in risk theory to allow for a larger class of risk models. Optional semimartingales are left-continuous with right-limit stochastic processes defined on a probability space where the usual conditions—completeness and right-continuity of the filtration—are not assumed. Three risk models are formulated, accounting for inflation, interest rates, and claim occurrences. The first model extends the martingale approach to calculate ruin probabilities, the second employs the Gerber–Shiu function to evaluate the expected discounted penalty from financial oscillations or jumps, and the third introduces a Gaussian risk model using counting processes to capture premium and claim cash flow jumps in insurance companies. Full article

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

19 pages, 1025 KiB

Open AccessArticle

COVID-19 Intensity, Resilience, and Expected Returns

by Elham Daadmehr

Risks 2025, 13(3), 60; https://doi.org/10.3390/risks13030060 - 20 Mar 2025

This paper provides a model to interpret the relative behavior of expected returns of high- and low-resilience assets from the time of the COVID-19 pandemic, including a novel definition of disaster based on COVID-19 intensity. The setup allows us to disentangle the probability [...] Read more.

This paper provides a model to interpret the relative behavior of expected returns of high- and low-resilience assets from the time of the COVID-19 pandemic, including a novel definition of disaster based on COVID-19 intensity. The setup allows us to disentangle the probability of disaster and investors’ updating probability at each point in time which sheds light on how long-memory investors react to disaster risk and play a role in future prices. The theoretical results show higher revisions in expected return differentials in the case of any perception of a higher possibility of disaster or, equivalently, higher COVID-19 intensity. The intensity of COVID-19 can directly exacerbate the heterogeneity in expected returns for high- and low-resilience assets and their corresponding differentials. More importantly, an increase in COVID-19 intensity increases the expected returns of low-resilience assets more than those of high-resilience ones. Full article

(This article belongs to the Special Issue Risk and Return Analysis in the Stock Market)

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19 pages, 1836 KiB

Open AccessArticle

The Impact of Nature Restoration Law on Equity Behavior: How Biodiversity Risk Affects Market Risk

by Paolo Capelli, Lorenzo Gai, Federica Ielasi and Marco Taddei

Risks 2025, 13(3), 59; https://doi.org/10.3390/risks13030059 - 19 Mar 2025

This study examines the market reaction to the approval of the Nature Restoration Law, a key component of the EU Biodiversity Strategy, and its implications for biodiversity-related financial risks. Using an event study methodology, we analyze the equity price movements of companies listed [...] Read more.

This study examines the market reaction to the approval of the Nature Restoration Law, a key component of the EU Biodiversity Strategy, and its implications for biodiversity-related financial risks. Using an event study methodology, we analyze the equity price movements of companies listed in the MSCI Europe Index that are equally weighted in relation to the announcement. We select the RepRisk Due Diligence Score, focusing on incidents linked to landscapes, ecosystems, and biodiversity, as a measure of biodiversity risk. At first, it seems that companies with a high RepRisk Due Diligence Score show limited or positive abnormal returns, suggesting that biodiversity risks are already priced for companies that have experienced incidents linked to this issue. Conversely, firms with lower biodiversity risk exposure see null or negative impacts, reflecting heightened investor concerns about new environmental regulations or compliance costs. Although the event does not have a systemic impact on European companies in the index, it seems that some sectors are affected when analyzed using parametric and non-parametric distributions. Full article

(This article belongs to the Special Issue Integrating New Risks into Traditional Risk Management)

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19 pages, 4542 KiB

Open AccessArticle

Forecasting Volatility of the Nordic Electricity Market an Application of the MSGARCH

by Muhammad Naeem, Hothefa Shaker Jassim, Kashif Saleem and Maham Fatima

Risks 2025, 13(3), 58; https://doi.org/10.3390/risks13030058 - 19 Mar 2025

This paper studies the volatility of electricity spot prices in the Nordic market (Sweden, Finland, Denmark, and Norway) under regime switching. Utilizing Markov-switching GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models, we provide strong evidence of nonlinear regime shifts in the volatility dynamics of these [...] Read more.

This paper studies the volatility of electricity spot prices in the Nordic market (Sweden, Finland, Denmark, and Norway) under regime switching. Utilizing Markov-switching GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models, we provide strong evidence of nonlinear regime shifts in the volatility dynamics of these prices. Using in-sample criteria, we find that regime-switching models have lower AIC (Akaike information criterion) than single-regime GARCH models. In addition, out-of-sample forecasts indicate that regime-switching GARCH models have superior Value-at-Risk (VaR) prediction ability relative to single-regime models, which is directly pertinent to risk management. These findings highlight the importance of incorporating regime shifts into volatility models for accurately assessing and mitigating risks associated with electricity price fluctuations in deregulated markets. Full article

(This article belongs to the Special Issue Modern Statistical and Machine Learning Techniques for Financial Data)

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43 pages, 6594 KiB

Open AccessArticle

Towards Examining the Volatility of Top Market-Cap Cryptocurrencies Throughout the COVID-19 Outbreak and the Russia–Ukraine War: Empirical Evidence from GARCH-Type Models

by Ștefan-Cristian Gherghina and Cristina-Andreea Constantinescu

Risks 2025, 13(3), 57; https://doi.org/10.3390/risks13030057 - 19 Mar 2025

The cryptocurrency market, known for its inherent volatility, has been significantly influenced by external shocks, particularly during periods of global crises such as the COVID-19 pandemic and the Russia–Ukraine war. This study investigates the volatility of the top seven cryptocurrencies by market capitalization—Bitcoin [...] Read more.

The cryptocurrency market, known for its inherent volatility, has been significantly influenced by external shocks, particularly during periods of global crises such as the COVID-19 pandemic and the Russia–Ukraine war. This study investigates the volatility of the top seven cryptocurrencies by market capitalization—Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance Coin (BNB), USD Coin (USDC), XRP, and Cardano (ADA)—from 1 January 2020 to 1 September 2024, employing a range of GARCH models (GARCH, EGARCH, TGARCH, and DCC-GARCH). This research aims to examine the persistence of leverage effects, volatility asymmetry, and the impact of past price fluctuations on future volatility, with a particular focus on how these dynamics were shaped by the pandemic and geopolitical tensions. The findings reveal that past price fluctuations had a limited impact on future volatility for most cryptocurrencies, although leverage effects became evident during market anomalies. Stablecoins (USDC and USDT) showed a distinct volatility pattern, reflecting their peg to the US Dollar, while platform-associated BNB demonstrated unique volatility characteristics. The results underscore the market’s sensitivity to price movements, highlighting the varying reactions of investor profiles across different cryptocurrencies. These insights contribute to understanding volatility transmission within the cryptocurrency market during times of crisis and offer important implications for market participants, particularly in the context of risk management strategies. Full article

(This article belongs to the Special Issue Cryptocurrency Pricing and Trading)

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59 pages, 7152 KiB

Open AccessArticle

Dynamic Shock-Transmission Mechanism Between U.S. Trade Policy Uncertainty and Sharia-Compliant Stock Market Volatility of GCC Economies

by Mosab I. Tabash, Suzan Sameer Issa, Marwan Mansour, Mohammed W. A. Saleh, Maha Rahrouh, Kholoud AlQeisi and Mujeeb Saif Mohsen Al-Absy

Risks 2025, 13(3), 56; https://doi.org/10.3390/risks13030056 - 18 Mar 2025

This study endeavors to explore the shock-transmission mechanism between Trade Policy Uncertainty (TPU) and the volatility inherent in the Gulf Cooperation Council (GCC) Islamic stock markets by employing the novel Quantile Vector Auto Regression (QVAR) with “Extended Joint” and “Frequency” domain connectedness technique. [...] Read more.

This study endeavors to explore the shock-transmission mechanism between Trade Policy Uncertainty (TPU) and the volatility inherent in the Gulf Cooperation Council (GCC) Islamic stock markets by employing the novel Quantile Vector Auto Regression (QVAR) with “Extended Joint” and “Frequency” domain connectedness technique. Overall findings indicated a U-shaped pattern in the shock-transmission mechanism with the higher TPU shocks transmitted towards Islamic stock market volatility at the extreme quantiles and in the long term. The “Extended Joint” QVAR connectedness approach highlights that, in bearish and moderate-volatility conditions (τ = 0.05, 0.50), diversifying portfolios across less shock-prone equity markets like Qatar and UAE can mitigate risk exposure to TPU shocks. Specific economies receiving higher TPU shocks, like Bahrain, Kuwait, and Saudi Arabia, should implement strategic frameworks, including trade credit insurance and currency hedging, for risk reduction in trade policy shocks during the bearish and moderate-volatility conditions. Conversely, Qatar and Kuwait show the least transmission of error variance from TPU during higher-volatility conditions (τ = 0.95). Moreover, the application of the Frequency-domain QVAR technique underscores the need for short-term speculators to exercise increased vigilance during bearish and bullish volatile periods, as TPU shocks can exert a more substantial influence on the Islamic equity market volatility of Bahrain, Oman, Kuwait, and Saudi Arabia. Long-term investors may need to tailor their asset-allocation strategies by increasing allocations to more stable assets that are less susceptible to TPU shocks, such as Qatar, during bearish (τ = 0.05), moderate (τ = 0.50), and bullish (τ = 0.95) volatility. Full article

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16 pages, 1960 KiB

Open AccessArticle

Political Uncertainty-Managed Portfolios

by Thorsten Lehnert

Risks 2025, 13(3), 55; https://doi.org/10.3390/risks13030055 - 18 Mar 2025

Forward-looking metrics of uncertainty based on options-implied information should be highly predictive of equity market returns in accordance with asset pricing theory. Empirically, however, the ability of the VIX, for example, to predict returns is statistically weak. In contrast to other studies that [...] Read more.

Forward-looking metrics of uncertainty based on options-implied information should be highly predictive of equity market returns in accordance with asset pricing theory. Empirically, however, the ability of the VIX, for example, to predict returns is statistically weak. In contrast to other studies that typically analyze a short time-series of option prices, I make use of a ‘VIX-type’ but a text-based measure of uncertainty starting in 1890, which is constructed using the titles and abstracts of front-page articles of the Wall Street Journal. I hypothesize that uncertainty timing might increase Sharpe ratios because changes in uncertainty are not necessarily correlated with changes in equity risk and, therefore, not offset by proportional changes in expected returns. Using a major US equity portfolio, I propose a dynamic trading strategy and show that lagged news-based uncertainty explains future excess returns on the market portfolio at the short horizon. While policy- and war-related concerns mainly drive these predictability results, stock market-related news has no predictive power. A managed equity portfolio that takes more risk when news-based uncertainty is high generates an annualized equity risk-adjusted alpha of 5.33% with an appraisal ratio of 0.46. Managing news-based uncertainty contrasts with conventional investment knowledge because the strategy takes relatively less risks in recessions, which rules out typical risk-based explanations. Interestingly, I find that the uncertainty around governmental policy is lower and, by taking less risk, it performs better during periods when the Republicans control the senate. I conclude that my text-based measure is a plausible proxy for investor policy uncertainty and performs better in terms of predictability compared to other options-based measures. Full article

(This article belongs to the Special Issue Portfolio Selection and Asset Pricing)

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15 pages, 1079 KiB

Open AccessArticle

The Impact of Supply Chain Disruptions and Global Uncertainty on Inflation Rate in Saudi Arabia

by Abdulrahman A. Albahouth

Risks 2025, 13(3), 54; https://doi.org/10.3390/risks13030054 - 17 Mar 2025

Inflation rate is considered undesirable in the modern globalized world due to its adverse and long-lasting impacts. The Kingdom of Saudi Arabia (KSA, hereafter) has also experienced inflationary pressure during the last few years, specifically post-COVID-19. However, the empirical literature on the determinants [...] Read more.

Inflation rate is considered undesirable in the modern globalized world due to its adverse and long-lasting impacts. The Kingdom of Saudi Arabia (KSA, hereafter) has also experienced inflationary pressure during the last few years, specifically post-COVID-19. However, the empirical literature on the determinants of inflation is indeed very scarce in the context of KSA. Amid this backdrop, this research paper aims to figure out the true determinants of inflation by focusing on the role of supply chain disruptions and global uncertainty by focusing on KSA. Quantitative data were collected from credible sources on a monthly basis for the period of 1998M01 to 2024M02 and were analyzed through the “Autoregressive Distributed Lag Model (ARDL)”. Our findings indicate that inflation in KSA is positively impacted by supply chain disruptions, global uncertainty, inflation spillovers from the United States, and money supply in the long run. Similarly, in the short run, only money supply, supply chain disruptions, and global uncertainty are responsible for the prevailing inflation rate in KSA. Moreover, the real effective exchange rate is positively and significantly linked with inflation only in the long run. Furthermore, positive shocks in oil prices cure inflation, while negative shocks in oil prices accelerate inflation in the short run. Our results are expected to shape policy formulation regarding the management of the inflation rate in KSA significantly. Full article

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29 pages, 528 KiB

Open AccessArticle

Modeling Financial Bubbles with Optional Semimartingales in Nonstandard Probability Spaces

by Mohamed Abdelghani and Alexander Melnikov

Risks 2025, 13(3), 53; https://doi.org/10.3390/risks13030053 - 17 Mar 2025

Deviation of an asset price from its fundamental value, commonly referred to as a price bubble, is a well-known phenomenon in financial markets. Mathematically, a bubble arises when the deflated price process transitions from a martingale to a strict local martingale. This paper [...] Read more.

Deviation of an asset price from its fundamental value, commonly referred to as a price bubble, is a well-known phenomenon in financial markets. Mathematically, a bubble arises when the deflated price process transitions from a martingale to a strict local martingale. This paper explores price bubbles using the framework of optional semimartingale calculus within nonstandard probability spaces, where the underlying filtration is not necessarily right-continuous or complete. We present two formulations for financial markets with bubbles: one in which asset prices are modeled as càdlàg semimartingales and another where they are modeled as làdlàg semimartingales. In both models, we demonstrate that the formation and re-emergence of price bubbles are intrinsically tied to the lack of right continuity in the underlying filtration. These theoretical findings are illustrated with practical examples, offering novel insights into bubble dynamics that hold significance for both academics and practitioners in the field of mathematical finance. Full article

26 pages, 747 KiB

Open AccessArticle

An Integrated Risk Management Methodology for Deposits and Loans

by Gregory R. Hackworth, Weidong Tian and Michael R. Vandenberg

Risks 2025, 13(3), 52; https://doi.org/10.3390/risks13030052 - 13 Mar 2025

This paper presents an integrated risk management methodology for measuring and managing the economics, risks, and financial resources/constraints related to deposits and loans in a commercial bank. Within a comprehensive and integrated framework, we develop valuation and risk models for all financial products [...] Read more.

This paper presents an integrated risk management methodology for measuring and managing the economics, risks, and financial resources/constraints related to deposits and loans in a commercial bank. Within a comprehensive and integrated framework, we develop valuation and risk models for all financial products on the bank’s balance sheet. Our proposed methodology aligns with regulatory requirements while offering a practical implementation. Unlike traditional industry practices, which often rely on fragmented and siloed risk management solutions, our approach integrates risk modeling across all aspects of the bank’s balance sheet. This new perspective provides a more accurate and consistent assessment of financial risks, improving the bank’s ability to navigate regulatory and economic challenges. Full article

(This article belongs to the Special Issue Valuation Risk and Asset Pricing)

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