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J. Risk Financial Manag., Volume 17, Issue 7 (July 2024) – 46 articles

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15 pages, 466 KiB  
Article
Modeling and Forecasting Historical Volatility Using Econometric and Deep Learning Approaches: Evidence from the Moroccan and Bahraini Stock Markets
by Imane Boudri and Abdelhamid El Bouhadi
J. Risk Financial Manag. 2024, 17(7), 300; https://doi.org/10.3390/jrfm17070300 (registering DOI) - 13 Jul 2024
Viewed by 98
Abstract
This study challenges the prevailing belief in the necessity of complex models for accurate forecasting by demonstrating the effectiveness of parsimonious econometric models, namely ARCH(1) and GARCH(1,1), over deep learning robust approaches, such as LSTM and 1D-CNN neural networks, in modeling historical volatility [...] Read more.
This study challenges the prevailing belief in the necessity of complex models for accurate forecasting by demonstrating the effectiveness of parsimonious econometric models, namely ARCH(1) and GARCH(1,1), over deep learning robust approaches, such as LSTM and 1D-CNN neural networks, in modeling historical volatility within pre-emerging stock markets, specifically the Moroccan and Bahraini stock markets. The findings suggest reevaluating the balance between model complexity and predictive accuracy. Future research directions include investigating the potential existence of threshold effects in market capitalization for optimal model performance. This research contributes to a deeper understanding of volatility dynamics and enhances forecasting models’ effectiveness in diverse market conditions. Full article
(This article belongs to the Special Issue Financial Markets, Financial Volatility and Beyond (Volume III))
19 pages, 1052 KiB  
Article
An Investigation of the Co-Movement between Spot and Futures Prices for Chinese Agricultural Commodities
by Yongmei Fang, Bo Guan, Huang Xu, Hossein Hassani and Saeed Heravi
J. Risk Financial Manag. 2024, 17(7), 299; https://doi.org/10.3390/jrfm17070299 (registering DOI) - 13 Jul 2024
Viewed by 136
Abstract
We employed a non-parametric causality test based on Singular Spectrum Analysis (SSA) and used the Vector Error Correction Model (VECM) and Information Share Model (IS) to measure the relationship between the futures and spot prices for seven major agricultural commodities in China from [...] Read more.
We employed a non-parametric causality test based on Singular Spectrum Analysis (SSA) and used the Vector Error Correction Model (VECM) and Information Share Model (IS) to measure the relationship between the futures and spot prices for seven major agricultural commodities in China from 2009 to 2017. We found that the agricultural futures market has potential leading information in price discovery. The results of an Impulse Response Function (IRF) analysis also showed that the spot prices react to shocks from the future market and have a lasting impact. This confirms our findings reported for the causality test and information share analysis. Full article
(This article belongs to the Section Financial Markets)
15 pages, 793 KiB  
Article
The Real-Time Impact of Political Risk on Market Valuations: Evidence from Peru
by Juan Pablo Micozzi, Patricio Navia, Pablo Pinto and Sebastian Saiegh
J. Risk Financial Manag. 2024, 17(7), 298; https://doi.org/10.3390/jrfm17070298 (registering DOI) - 13 Jul 2024
Viewed by 99
Abstract
This study examines the impact of political risk on financial markets by leveraging high-frequency (minute-by-minute) price data and precise event timestamps from media outlets’ Twitter feeds during Pedro Castillo’s failed coup attempt in Peru. Unlike previous research that relies on low-frequency data and [...] Read more.
This study examines the impact of political risk on financial markets by leveraging high-frequency (minute-by-minute) price data and precise event timestamps from media outlets’ Twitter feeds during Pedro Castillo’s failed coup attempt in Peru. Unlike previous research that relies on low-frequency data and protracted political changes, our analysis demonstrates that daily closing prices may misleadingly suggest negligible impact. In contrast, high-frequency data reveal that markets promptly and accurately incorporated news of the coup attempt and, in turn, its failure into asset prices. Our analysis shows that breakdowns in democratic governance negatively affect asset prices, while the restoration of the rule of law, in the form Congressional checks on the Executive branch, boosts them. Moreover, our analyses suggest that domestic companies and sectors with less mobile assets are more vulnerable to these political risks. Our findings underscore the crucial role of high-frequency data in accurately capturing how institutions and political risk affects equity markets. Full article
(This article belongs to the Special Issue Political Risk Management in Financial Markets)
18 pages, 3256 KiB  
Review
The Conceptual, Social, and Intellectual Structure of the Financial Information/Accounting Manipulation Literature: A Bibliometric Analysis
by Mustafa Kıllı, Samet Evci and İlker Kefe
J. Risk Financial Manag. 2024, 17(7), 297; https://doi.org/10.3390/jrfm17070297 - 11 Jul 2024
Viewed by 328
Abstract
This study presents a comprehensive bibliometric analysis of studies on financial information/accounting manipulation. The dataset of research includes 1.266 studies from the Web of Science database for the period 1991–2023. All studies included in the research contain either the term ‘financial information manipulation’ [...] Read more.
This study presents a comprehensive bibliometric analysis of studies on financial information/accounting manipulation. The dataset of research includes 1.266 studies from the Web of Science database for the period 1991–2023. All studies included in the research contain either the term ‘financial information manipulation’ or ‘accounting manipulation’ in the topic (title, abstract, or keywords). The bibliometric network mapping technique was used for the analysis of the data. The analysis was conducted utilizing the Biblioshiny interface of the R package programs Bibliometrix and Vosviewer. The results pointed out a notable upward trend in the publication and citation rates of financial information/accounting manipulation studies over the last two decades. Several key findings were identified. Firstly, a substantial rise in research output on financial information/accounting manipulation was observed, particularly after 2000, driven by global financial scandals. Secondly, prolific contributors to this field include authors such as Valaskova and Durana. Thirdly, the United States leads in research output, with significant contributions from institutions like the State University System of Florida and the State University System of Ohio. Lastly, The Accounting Review was identified as the most prolific journal in this domain, with the Journal of Accounting Economics being the most impactful based on citations. The most frequently used keywords indicate that the research topics focus on earnings management as a method of manipulation, fraudulent financial reporting, and the relationship with corporate governance. The comprehensiveness of the bibliometric data lends itself to a further examination of how financial information/accounting manipulation has progressed as a subject in the literature since the 2000s. In addition, this study reveals the social and intellectual structures of the issue, the key research streams, and potential research directions for future research. Full article
(This article belongs to the Section Business and Entrepreneurship)
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16 pages, 295 KiB  
Article
Unpacking Environmental, Social, and Governance Score Disparity: A Study of Indonesian Palm Oil Companies
by Iwan Suhardjo, Chris Akroyd and Meiliana Suparman
J. Risk Financial Manag. 2024, 17(7), 296; https://doi.org/10.3390/jrfm17070296 - 11 Jul 2024
Viewed by 402
Abstract
This study investigates the inconsistencies in ESG scores assigned by different rating agencies. Focusing on two Indonesian palm oil companies, this paper examines the link between their reported sustainability performance and the resulting ESG scores. This study employs content analysis to assess how [...] Read more.
This study investigates the inconsistencies in ESG scores assigned by different rating agencies. Focusing on two Indonesian palm oil companies, this paper examines the link between their reported sustainability performance and the resulting ESG scores. This study employs content analysis to assess how the companies disclose information around double materiality, stakeholder engagement, and certifications. Additionally, the methodologies used by two rating agencies are reviewed to identify potential misalignments. The analysis reveals discrepancies in the ratings, suggesting factors like differences in the level of engagement with each company and scoring methodologies might be at play. This highlights the need for standardized sustainability reporting and more transparent rating methodologies within the palm oil industry. While limited to two companies and two agencies, the findings can inform efforts to improve transparency both in sustainability practices and scoring methodologies. This would ultimately lead to more reliable ESG scores, benefiting all related stakeholders. To goal of this study is to promote responsible practices in the palm oil industry by emphasizing the impact of reporting practices. Full article
(This article belongs to the Section Sustainability and Finance)
13 pages, 2278 KiB  
Article
Understanding Regulatory Changes: Deep Learning in Sustainable Finance and Banking
by Bogdan Ionut Anghel and Radu Lupu
J. Risk Financial Manag. 2024, 17(7), 295; https://doi.org/10.3390/jrfm17070295 - 10 Jul 2024
Viewed by 399
Abstract
This paper examines the regulatory impact on the European Banking Sector using advanced deep learning techniques to analyze the relationship between Sustainable Finance guidelines and the SX7P Index from January 2012 to December 2023. Utilizing Long Short-Term Memory Auto-encoder (LSTM-AE), Variational Autoencoder (VAE), [...] Read more.
This paper examines the regulatory impact on the European Banking Sector using advanced deep learning techniques to analyze the relationship between Sustainable Finance guidelines and the SX7P Index from January 2012 to December 2023. Utilizing Long Short-Term Memory Auto-encoder (LSTM-AE), Variational Autoencoder (VAE), and Convolutional Neural Network (CNN) for anomaly detection, the study compares anomalies and investigates their correlation with European Banking Authority (EBA) events and Sustainable Finance guidelines from January 2020 to December 2023. Through the analysis of 43 pertinent EBA documents, the research identifies patterns and variations in anomalies, assessing their association with regulatory changes. The results reveal significant anomalies aligning with regulatory events, indicating a potential causal relationship. Notably, the VAE methodology shows the strongest correlation between EBA Sustainable Finance events and anomalies. This research advances the understanding of deep learning applications in financial markets and offers valuable insights for policymakers and financial institutions regarding regulatory shifts in Sustainable Finance. Full article
(This article belongs to the Special Issue Smart Solutions for Sustainable Economics and Finance)
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20 pages, 1452 KiB  
Article
Volatility Persistence and Spillover Effects of Indian Market in the Global Economy: A Pre- and Post-Pandemic Analysis Using VAR-BEKK-GARCH Model
by Narayana Maharana, Ashok Kumar Panigrahi and Suman Kalyan Chaudhury
J. Risk Financial Manag. 2024, 17(7), 294; https://doi.org/10.3390/jrfm17070294 - 10 Jul 2024
Viewed by 376
Abstract
This study examines how the COVID-19 pandemic impacted stock market volatility and interconnectedness between India and other selected global economies. The analysis, using data from 2016 to 2024, reveals a substantial rise in volatility within both the Indian market and those of several [...] Read more.
This study examines how the COVID-19 pandemic impacted stock market volatility and interconnectedness between India and other selected global economies. The analysis, using data from 2016 to 2024, reveals a substantial rise in volatility within both the Indian market and those of several other countries after the pandemic. Interestingly, the volatility transmission patterns also changed. While the Indian market’s volatility significantly influenced Brazil, China, and Mexico throughout the entire period, the influence of the US market became negligible post-pandemic. In contrast, Russia exhibited a weak but statistically significant impact on India’s volatility only after the pandemic. These findings highlight the lasting impact of the pandemic on global financial markets and emphasize the need for investors and policymakers to adapt. By understanding these new dynamics, investors can make more informed decisions, and policymakers can develop stronger risk management strategies and international coordination during periods of increased volatility. This study offers valuable insights for navigating the current financial landscape and the interconnectedness of emerging economies. Full article
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16 pages, 5838 KiB  
Article
Assessing the Predictive Power of Transformers, ARIMA, and LSTM in Forecasting Stock Prices of Moroccan Credit Companies
by Karima Lahboub and Mimoun Benali
J. Risk Financial Manag. 2024, 17(7), 293; https://doi.org/10.3390/jrfm17070293 - 9 Jul 2024
Viewed by 283
Abstract
In this paper, we present a data-driven approach to forecasting stock prices in the Moroccan Stock Exchange. Our study tests three predictive models: ARIMA, LSTM, and transformers, applied to the historical stock price data of three prominent credit companies (EQD, LES, and SLF) [...] Read more.
In this paper, we present a data-driven approach to forecasting stock prices in the Moroccan Stock Exchange. Our study tests three predictive models: ARIMA, LSTM, and transformers, applied to the historical stock price data of three prominent credit companies (EQD, LES, and SLF) listed on the Casablanca Stock Exchange. We carefully selected and optimized hyperparameters for each model to achieve optimal performance. Our results showed that the LSTM model achieved high accuracy, with R-squared values exceeding 0.99 for EQD and LES and surpassing 0.95 for SLF. These findings highlighted the effectiveness of LSTM in stock price forecasting. Our study offers practical insights for traders and investors in the Moroccan Stock Exchange, demonstrating how predictive modeling can aid in making informed decisions. This research contributes to advancing stock market forecasting in Morocco, providing valuable tools for navigating the Casablanca Stock Exchange. Full article
(This article belongs to the Special Issue Applied Econometrics and Time Series Analysis (Volume II))
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31 pages, 557 KiB  
Article
Driving Venture Capital Interest: The Influence of the Big 4 Audit Firms on IPOs
by Manal Alidarous
J. Risk Financial Manag. 2024, 17(7), 292; https://doi.org/10.3390/jrfm17070292 - 9 Jul 2024
Viewed by 400
Abstract
This paper investigated how hiring one of the Big 4 auditing firms helps initial public offering (IPO) owners attract venture capitalists’ (VCs) backing when going public to address the gap in auditing and venture capital literature. For this, the paper examined a large [...] Read more.
This paper investigated how hiring one of the Big 4 auditing firms helps initial public offering (IPO) owners attract venture capitalists’ (VCs) backing when going public to address the gap in auditing and venture capital literature. For this, the paper examined a large dataset from 1995 to 2019 consisting of 33,536 IPO firms from 22 countries with diverse socioeconomic, political, and cultural contexts. The study found that hiring Big 4 auditors increases IPO owners’ chances of recruiting VCs by up to 50%. The analysis also supports prior findings, which state that IPO owners strategically choose Big 4 audit firms to lower agency costs and send quality signals to improve openness and disclosure as well as boost VCs’ confidence in the IPO market. This research offers multiple benefits to academics, policymakers, investors, and issuers. Full article
(This article belongs to the Special Issue Advances in Accounting & Auditing Research)
17 pages, 273 KiB  
Article
Friendly Boards and the Cost of Debt
by Hoontaek Seo, Sangho Yi and William McCumber
J. Risk Financial Manag. 2024, 17(7), 291; https://doi.org/10.3390/jrfm17070291 - 9 Jul 2024
Viewed by 293
Abstract
For a sample of public bond issues by U.S. firms between 2000 and 2019, sourced from the Securities Data Corporation (SDC) New Issues database, we examine the relationship between CEO-friendly boards and the cost of debt. To explore this relationship, we construct proxies [...] Read more.
For a sample of public bond issues by U.S. firms between 2000 and 2019, sourced from the Securities Data Corporation (SDC) New Issues database, we examine the relationship between CEO-friendly boards and the cost of debt. To explore this relationship, we construct proxies for board friendliness based on social connections sourced from the BoardEx database, classifying a board as friendly if it includes at least one outside director who has a social connection with the CEO. Our regression analysis reveals a negative association between CEO-friendly boards and yield spreads and a positive association between CEO-friendly boards and credit ratings. These effects exist after controlling for firm and bond characteristics based on prior literature. The results are robust to an alternative measure of board friendliness and potential endogeneity. These findings imply that firms with a CEO-friendly board experience a lower cost of bond financing. This supports the argument that effective communication between CEOs and directors contributes to the enhancement of creditor interests. Our results carry a practical implication that firms heavily reliant on debt should actively employ CEO-friendly boards. Despite the burgeoning literature on CEO-friendly boards, there is a lack of research on the relationship between CEO-friendly boards and the cost of debt. Our results fill this gap in the extant literature on CEO-friendly boards. Full article
(This article belongs to the Section Business and Entrepreneurship)
23 pages, 2467 KiB  
Article
Reforming Sustainability-Linked Bonds by Strengthening Investor Trust
by Frederic de Mariz, Pieter Bosmans, Daniel Leal and Saumya Bisaria
J. Risk Financial Manag. 2024, 17(7), 290; https://doi.org/10.3390/jrfm17070290 - 8 Jul 2024
Viewed by 324
Abstract
This paper explores the emergence of sustainability-linked bonds (SLBs) as an innovative instrument to finance sustainability objectives. SLBs are any type of bond instrument for which the financial characteristics vary depending on whether the issuer achieves predefined sustainability objectives. SLBs were launched in [...] Read more.
This paper explores the emergence of sustainability-linked bonds (SLBs) as an innovative instrument to finance sustainability objectives. SLBs are any type of bond instrument for which the financial characteristics vary depending on whether the issuer achieves predefined sustainability objectives. SLBs were launched in 2019, represent 7% of labeled bonds, and now exceed USD 250 billion. In the context of the growth of sustainable finance and concerns of greenwashing, this paper asks whether SLBs are an effective mechanism to attract sustainable finance. Drawing on a complete revision of the literature and interviews with practitioners, the findings highlight the potential of SLBs to contribute to sustainability financing, especially in hard-to-abate sectors. Recommendations include defining standardized KPIs based on a materiality assessment, requesting SPTs to be supported by science, and tailored step-up mechanisms. The academic literature and experts converge in their description of greenwashing risks posed by SLBs, their signaling effect, and the lack of sophistication in SLB pricing, in particular the optionality represented by step-ups. The literature differs from the practitioners’ perception on the existence of an issuance premium. Enhancing the design of SLBs represents an opportunity to add rigor to sustainable finance and better price externalities, where material topics have an explicit impact on the cost of funding. Full article
(This article belongs to the Special Issue Finance, Risk and Sustainable Development)
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20 pages, 301 KiB  
Article
Mapping Capital Ratios to Bank Lending Spreads: The Role of Efficiency and Asymmetry in Performance Indices
by Ali Golbabaei Pasandi, Mahmoud Botshekan, Abol Jalilvand, Mohammad Ali Rastegar and Mojtaba Rostami Noroozabad
J. Risk Financial Manag. 2024, 17(7), 289; https://doi.org/10.3390/jrfm17070289 - 8 Jul 2024
Viewed by 317
Abstract
Beyond the 2007–2008 financial crisis, the collapse of the Silicon Valley Bank and the acquisition of Credit Suisse by the Swiss investment bank UBS Group AG in 2023 have brought fresh attention to the need for new regulatory capital, liquidity risk management, and [...] Read more.
Beyond the 2007–2008 financial crisis, the collapse of the Silicon Valley Bank and the acquisition of Credit Suisse by the Swiss investment bank UBS Group AG in 2023 have brought fresh attention to the need for new regulatory capital, liquidity risk management, and leverage requirements. To meet tightened capital requirements, banks have to increase their capital ratios either by increasing equity or by decreasing risk-weighted assets. Both options lead to banks’ performance deterioration. One remedy for banks to recover is raising their lending spread. A critical question is how much the lending spread should be increased to offset the drop in the bank’s financial performance level. In this study, we focus on the asymmetries and efficiency consequences of performance indices such as economic value added (EVA) and the more commonly used return on equity (ROE) in determining the loan spread. Using data on the largest U.S. banks over the period 2018–2022, our results show that the ROE rule significantly overestimates the magnitude of the lending spreads required to offset the negative financial consequences of increases in capital ratios. The EVA approach, on the other hand, prescribes on average a significantly lower lending spread of 0.4505 basis points against a lending spread of 21.0441 basis points associated with the use of the ROE approach. The efficiency and the level of lending spreads should enable banks to maintain their competitive advantages in the loan markets impacting overall economic productivity and growth. Full article
(This article belongs to the Section Business and Entrepreneurship)
24 pages, 1072 KiB  
Article
Evaluation of Total Risk-Weighted Assets in Islamic Banking through Fintech Innovations
by Asma S. Alzwi, Jamil J. Jaber, Hani Nuri Rohuma and Rania Al Omari
J. Risk Financial Manag. 2024, 17(7), 288; https://doi.org/10.3390/jrfm17070288 - 8 Jul 2024
Viewed by 279
Abstract
The assessment of total risk-weighted assets (LTRWAs) in the banking sector is of the utmost importance. It serves as a critical component for regulatory compliance, risk management, and capital adequacy. By accurately assessing LTRWAs, banks can effectively meet regulatory requirements, efficiently allocate capital [...] Read more.
The assessment of total risk-weighted assets (LTRWAs) in the banking sector is of the utmost importance. It serves as a critical component for regulatory compliance, risk management, and capital adequacy. By accurately assessing LTRWAs, banks can effectively meet regulatory requirements, efficiently allocate capital resources, and proactively manage risks. Moreover, the accurate assessment of LTRWAs supports performance evaluation and fosters investor confidence in the financial stability of banks. This study presents statistical analyses and machine learning methods to identify factors influencing LTRWAs. Data from Bahrain, Jordan, Qatar, the United Arab Emirates, and Yemen, spanning from 2010 to 2021, was utilized. Various statistical tests and models, including ordinary least squares, fixed effect, random effect, correlation, variance inflation factor, tolerance tests, and fintech models, were conducted. The results indicated significant impacts of the unemployment rate, inflation rate, natural logarithm of the loan-to-asset ratio, and natural logarithm of total assets on LTRWAs in regression models. The dataset was divided into a training group (90% of the data) and a testing group (10% of the data) to evaluate the predictive capabilities of various fintech models, including an adaptive network-based fuzzy inference system (ANFIS), a hybrid neural fuzzy inference system (HyFIS), a fuzzy system with the heuristic gradient descent (FS.HGD), and fuzzy inference rules with the descent method (FIR.DM) models. The selection of the optimal model is contingent upon assessing its performance according to specific error criteria. The HyFIS model outperformed others with lower errors in predicting LTRWAs. Independent t-tests confirmed statistically significant differences between original and predicted LTRWA for all models, with HyFIS showing closer predictions. This study provides valuable insights into LTRWA prediction using advanced statistical and machine learning techniques, based on a dataset from multiple countries and years. Full article
(This article belongs to the Special Issue Emerging Issues in Economics, Finance and Business)
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26 pages, 364 KiB  
Article
Cost–Benefit Analysis of International Financial Reporting Standard and Russian Accounting Standard Integration: What Does Comparability Cost?
by Elizabeth H. Turner and Clark M. Wheatley
J. Risk Financial Manag. 2024, 17(7), 287; https://doi.org/10.3390/jrfm17070287 - 8 Jul 2024
Viewed by 274
Abstract
In Russia, firms with consolidated financial statements must produce financial statements in both RAS (Russian accounting standards) and IFRS (international financial reporting standards). Unconsolidated SMEs are only required to use RAS. Using hand-collected data from 2010–2013 (pre- and post-IFRS adoption periods), we find [...] Read more.
In Russia, firms with consolidated financial statements must produce financial statements in both RAS (Russian accounting standards) and IFRS (international financial reporting standards). Unconsolidated SMEs are only required to use RAS. Using hand-collected data from 2010–2013 (pre- and post-IFRS adoption periods), we find income measures under RAS are converging to income measures under IFRS. The quality of earnings exhibits no change under IFRS, while RAS earnings are being managed upward for firms that have adopted IFRS and downward for firms that have not adopted IFRS. The relative variation in market and book values differs more widely under IFRS when compared to RAS, implying more volatility and risk under IFRS. We attribute our findings to a monitoring effect derived from IFRS. Full article
(This article belongs to the Special Issue Advances in Accounting & Auditing Research)
24 pages, 300 KiB  
Article
Financial Distress Premium or Discount? Some New Evidence
by Ramya R. Aroul, Noura K. Kone and Sanjiv Sabherwal
J. Risk Financial Manag. 2024, 17(7), 286; https://doi.org/10.3390/jrfm17070286 - 7 Jul 2024
Viewed by 402
Abstract
This study investigates the contradiction in the finding of a positive distress risk premium in Vassalou and Xing’s study and the finding of a negative distress risk premium, i.e., a distress risk discount, in several other studies. Using the default likelihood measure calculated [...] Read more.
This study investigates the contradiction in the finding of a positive distress risk premium in Vassalou and Xing’s study and the finding of a negative distress risk premium, i.e., a distress risk discount, in several other studies. Using the default likelihood measure calculated following Vassalou and Xing’s procedure for 1965–2023, we show that excluding outliers and including the time period beyond the end of Vassalou and Xing’s sample period in 1999 makes a difference in the results. Overall, using portfolio sorting and Fama-MacBeth regressions, this study supports the existence of a distress risk discount. This study also documents that the financial distress risk is negatively reflected in security prices even after accounting for size and book-to-market risk factors. Furthermore, it demonstrates that the negative distress risk premium is strong and persistent across economic expansions, recessions, and the COVID-19 pandemic. Full article
(This article belongs to the Special Issue Bankruptcy Prediction, Equity Valuation and Stock Returns)
12 pages, 2040 KiB  
Article
The Relationship between Environmental, Social and Governance Factors, Economic Growth, and Banking Activity
by Ioan-Iulian Norocel and Eugen-Marian Vierescu
J. Risk Financial Manag. 2024, 17(7), 285; https://doi.org/10.3390/jrfm17070285 - 7 Jul 2024
Viewed by 348
Abstract
The sustainability-linked discussion has gained international importance, with the banking sector being an essential pillar of the new economy, particularly through channeling financial resources to environmentally friendly economic activities. It is, however, still unclear if ESG is profitable, both for the economy and [...] Read more.
The sustainability-linked discussion has gained international importance, with the banking sector being an essential pillar of the new economy, particularly through channeling financial resources to environmentally friendly economic activities. It is, however, still unclear if ESG is profitable, both for the economy and banks. This paper aims at filling this gap by presenting, from a macroeconomic perspective, the impact of ESG efforts and the banking sector’s contribution to a sustainable economy. Using panel regression models with fixed effects, the study investigates the impact of ESG factors and banking activity on economic growth. The results show a negative relationship between country-level ESG scores and economic growth, both in the short and long run, while increased financial intermediation by the banking sector, used as a proxy of potential green lending activity, does not necessarily enhance economic growth. Through delving into the interplay between the ESG score, economic development, and banking activity, this research could serve as a discussion point for economists, bankers, and policymakers when designing the economic and financial strategies for transitioning to a green economy. Full article
(This article belongs to the Special Issue Smart Solutions for Sustainable Economics and Finance)
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11 pages, 261 KiB  
Article
Do Investment Funds Audited by the Big Four Firms Exhibit Different Performances? Evidence from Brazil
by Rodrigo Fernandes Malaquias, Dermeval Martins Borges Junior and Pablo Zambra
J. Risk Financial Manag. 2024, 17(7), 284; https://doi.org/10.3390/jrfm17070284 - 6 Jul 2024
Viewed by 497
Abstract
Investment funds manage a portfolio composed of financial instruments; therefore, their accounting reports should undergo a careful process of preparation and auditing. The main purpose of this study is to analyze the effect of being audited by a Big Four audit company on [...] Read more.
Investment funds manage a portfolio composed of financial instruments; therefore, their accounting reports should undergo a careful process of preparation and auditing. The main purpose of this study is to analyze the effect of being audited by a Big Four audit company on funds’ risk-adjusted performance. The database is composed of equity funds from the Brazilian financial market, with daily returns spanning from January 2005 to March 2023. The funds’ performance was measured based on three indicators, including the Sharpe Ratio and Jensen’s Alpha. Fama and MacBeth regressions were used to test the hypotheses. The main findings indicate that the benefits of audit quality also include a positive effect on the risk-adjusted performance of investment funds, as the coefficient of the variable “Big Four” was positive and significant based on the proxies for risk-adjusted performance. This study advances this area of research by demonstrating the effects of the type of audit on the risk-adjusted performance indicators of investment funds. Full article
(This article belongs to the Special Issue Advances in Accounting & Auditing Research)
20 pages, 2011 KiB  
Article
Sovereign Credit Risk in Saudi Arabia, Morocco and Egypt
by Amira Abid and Fathi Abid
J. Risk Financial Manag. 2024, 17(7), 283; https://doi.org/10.3390/jrfm17070283 - 5 Jul 2024
Viewed by 450
Abstract
The purpose of this paper is to assess and predict sovereign credit risk for Egypt, Morroco and Saudi Arabia using credit default swap (CDS) spreads obtained from the DataStream database for the period from 2009 to 2022. Our approach consists of generating the [...] Read more.
The purpose of this paper is to assess and predict sovereign credit risk for Egypt, Morroco and Saudi Arabia using credit default swap (CDS) spreads obtained from the DataStream database for the period from 2009 to 2022. Our approach consists of generating the implied default probability and the corresponding credit rating in order to estimate the term structure of the implied default probability using the Nelson–Siegel model. In order to validate the prediction from the probability term structure, we calculate the transition matrices based on the implied rating using the homogeneous Markov model. The main results show that, overall, the probabilities of defaulting in the long term are higher than those in the short term, which implies that the future outlook is more pessimistic given the events that occurred during the study period. Egypt seems to be the country with the most fragile economy, especially after 2009, likely because of the political events that marked the country at that time. The economies of Morocco and Saudi Arabia are more resilient in terms of both default probability and credit rating. These findings can help policymakers develop targeted strategies to mitigate economic risks and enhance stability, and they provide investors with valuable insights for managing long-term investment risks in these countries. Full article
(This article belongs to the Special Issue Emerging Issues in Economics, Finance and Business)
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23 pages, 4491 KiB  
Article
A News Sentiment Index to Inform International Financial Reporting Standard 9 Impairments
by Yolanda S. Stander
J. Risk Financial Manag. 2024, 17(7), 282; https://doi.org/10.3390/jrfm17070282 - 4 Jul 2024
Viewed by 643
Abstract
Economic and financial narratives inform market sentiment through the emotions that are triggered and the subjectivity that gets evoked. There is an important connection between narrative, sentiment, and human decision making. In this study, natural language processing is used to extract market sentiment [...] Read more.
Economic and financial narratives inform market sentiment through the emotions that are triggered and the subjectivity that gets evoked. There is an important connection between narrative, sentiment, and human decision making. In this study, natural language processing is used to extract market sentiment from the narratives using FinBERT, a Python library that has been pretrained on a large financial corpus. A news sentiment index is constructed and shown to be a leading indicator of systemic risk. A rolling regression shows how the impact of news sentiment on systemic risk changes over time, with the importance of news sentiment increasing in more recent years. Monitoring systemic risk is an important tool used by central banks to proactively identify and manage emerging risks to the financial system; it is also a key input into the credit loss provision quantification at banks. Credit loss provision is a key focus area for auditors because of the risk of material misstatement, but finding appropriate sources of audit evidence is challenging. The causal relationship between news sentiment and systemic risk suggests that news sentiment could serve as an early warning signal of increasing credit risk and an effective indicator of the state of the economic cycle. The news sentiment index is shown to be useful as audit evidence when benchmarking trends in accounting provisions, thus informing financial disclosures and serving as an exogenous variable in econometric forecast models. Full article
(This article belongs to the Section Economics and Finance)
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15 pages, 1073 KiB  
Article
Resilience Benchmarking: How Small Hotels Can Ensure Their Survival and Growth during Global Disruptions
by Oleh Kolodiziev, Oleksandr Dorokhov, Valeriia Shcherbak, Liudmyla Dorokhova, Altan Ismailov and Ronnie Figueiredo
J. Risk Financial Manag. 2024, 17(7), 281; https://doi.org/10.3390/jrfm17070281 - 4 Jul 2024
Viewed by 316
Abstract
This study aimed to develop a resilient benchmarking system for small hotels in Ukraine, designed to ensure their survival and growth amid global disruptions and local crises. Given the severe challenges associated with the COVID-19 pandemic and military actions, the resilience of the [...] Read more.
This study aimed to develop a resilient benchmarking system for small hotels in Ukraine, designed to ensure their survival and growth amid global disruptions and local crises. Given the severe challenges associated with the COVID-19 pandemic and military actions, the resilience of the regional tourism business is particularly relevant. The methods used in this study, including factor and cluster analysis, taxonomy, and dendrograms, enabled the development of development programs for two clusters of hotels: those located in areas with increased military risk and those in relatively safe territories. The taxonomic analysis revealed significant differences in managerial practices and operational efficiency, largely determined by the geographic location of the hotels. Hotels in active combat zones experienced a 40% reduction in tourist flow and financial instability, while hotels in safe areas demonstrated a 30% higher level of customer satisfaction. The application of advanced security systems and modern marketing techniques led to a 40% reduction in incidents. Full article
(This article belongs to the Special Issue Advances in Financial and Hospitality Management Accounting)
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33 pages, 601 KiB  
Article
Would Managers Sacrifice Conservative Financial Reporting to Meet/Beat Market Earnings Expectations?
by Anthony C. Ng, Hua Christine Xin and Bikki Jaggi
J. Risk Financial Manag. 2024, 17(7), 280; https://doi.org/10.3390/jrfm17070280 - 3 Jul 2024
Viewed by 483
Abstract
Prior studies show that engaging in conservative financial reporting (CON) positively affects earnings quality. However, managers also manage earnings to meet/beat market earnings expectations (MBME). This study asks three questions regarding the earnings that MBME. First, it investigates whether managers are willing to [...] Read more.
Prior studies show that engaging in conservative financial reporting (CON) positively affects earnings quality. However, managers also manage earnings to meet/beat market earnings expectations (MBME). This study asks three questions regarding the earnings that MBME. First, it investigates whether managers are willing to sacrifice CON when adopting strategies to MBME. Second, it tests whether managers prefer to use other earnings management (EM) strategies to MBME instead of sacrificing CON. Third, it tests whether information asymmetry between managers and shareholders affects managers’ decisions to sacrifice CON. Results show that managers are more likely to sacrifice CON to MBME but are less likely to do so if they can manage earnings using accrual-based or real EM. Also, managers are more likely to do so when information asymmetry with shareholders is higher. These findings contribute to the literature by examining the circumstances in which managers would sacrifice CON to MBME. Full article
(This article belongs to the Special Issue Financial Reporting and Auditing)
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15 pages, 453 KiB  
Article
Advanced Statistical Analysis of the Predicted Volatility Levels in Crypto Markets
by Vadim Azhmyakov, Ilya Shirokov and Luz Adriana Guzman Trujillo
J. Risk Financial Manag. 2024, 17(7), 279; https://doi.org/10.3390/jrfm17070279 - 3 Jul 2024
Viewed by 330
Abstract
Our paper deals with an advanced statistical tool for the volatility prediction problem in financial (crypto) markets. First, we consider the conventional GARCH-based volatility models. Next, we extend the corresponding GARCH-based forecasting and calculate a specific probability associated with the predicted volatility levels. [...] Read more.
Our paper deals with an advanced statistical tool for the volatility prediction problem in financial (crypto) markets. First, we consider the conventional GARCH-based volatility models. Next, we extend the corresponding GARCH-based forecasting and calculate a specific probability associated with the predicted volatility levels. As the probability evaluation is based on a stochastic model, we develop an advanced data-driven estimation of this probability. The novel statistical estimation we propose uses real market data. The obtained analytical results for the statistical probability of the levels are also discussed in the framework of the integrated volatility concept. The possible application of the established probability estimation approach to the volatility clustering problem is also mentioned. Our paper includes a concrete implementation of the proposed volatility prediction tool and considers a novel trading and volatility estimation module for crypto markets recently developed by the 1ex Trading Board group in collaboration with GoldenGate Venture. We also briefly discuss the possible application of a model combined with the data-driven volatility prediction methodology to financial risk management. Full article
(This article belongs to the Special Issue Featured Papers in Mathematics and Finance)
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25 pages, 1423 KiB  
Article
Impact of Mandatory Audits of Small- and Medium-Sized Enterprises on Their Income Tax Compliance: Evidence from the Egyptian Small- and Medium-Sized Enterprise Stock Market
by Abouelghit Mahmoud Galal Mohamed and Shengdao Gan
J. Risk Financial Manag. 2024, 17(7), 278; https://doi.org/10.3390/jrfm17070278 - 3 Jul 2024
Viewed by 376
Abstract
Small- and medium-sized enterprises are essential to the economies of nearly all countries, as they directly influence the GDP and tax revenue. In 2019, the European Federation of Accountants and Auditors for SMEs surveyed SME account users, revealing that tax authorities were the [...] Read more.
Small- and medium-sized enterprises are essential to the economies of nearly all countries, as they directly influence the GDP and tax revenue. In 2019, the European Federation of Accountants and Auditors for SMEs surveyed SME account users, revealing that tax authorities were the most common recipients of the company’s accounts, accounting for 61.40% of cases. This study, from a macroeconomic perspective, aims to uncover evidence of the impact of mandatory audits of Egyptian SMEs on their income tax compliance. It also seeks to explore the Egyptian SME tax environment to fill the knowledge gap by exploring perceptions of SMEs’ tax performances and their levels of tax. This study provides evidence that the taxpayers’ tax compliance behavior is an essential and decisive factor in the compliance of Egyptian SMEs with income tax. The results show that SME management is less persuaded by the potential benefits of mandatory audits on tax compliance than auditors and academics. Also, the study found experimental evidence confirming that the mandatory auditing of SMEs positively impacts their compliance with income tax. Additionally, this study developed a tax compliance scale (the RTRP scale) that effectively suits the nature and characteristics of SMEs, enabling the quantitative measurement of their compliance levels with income tax, as well as comparisons between SMEs. Full article
(This article belongs to the Section Business and Entrepreneurship)
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23 pages, 1066 KiB  
Article
Bank Reputation and Trust: Impact on Client Satisfaction and Loyalty for Portuguese Clients
by António Cardoso and Marta Cardoso
J. Risk Financial Manag. 2024, 17(7), 277; https://doi.org/10.3390/jrfm17070277 - 2 Jul 2024
Viewed by 380
Abstract
The aim of this article is to assess the most relevant factors influencing customer trust in the Portuguese banking sector following the Global Financial Crisis. It also aims to evaluate the impact of trust on satisfaction and satisfaction on loyalty. To address the [...] Read more.
The aim of this article is to assess the most relevant factors influencing customer trust in the Portuguese banking sector following the Global Financial Crisis. It also aims to evaluate the impact of trust on satisfaction and satisfaction on loyalty. To address the research objectives and the hypotheses posed, a quantitative study with a descriptive design was conducted. Data was collected through an online survey administered to a sample of bank clients residing in Portugal. The findings indicate that respondents generally trust Portuguese banking institutions, although this trust has been affected by the Global Financial Crisis. The bank’s reputation and financial performance were identified as critical factors in the respondents’ choice of bank. Additionally, the results suggest that both global and domestic financial conditions, bank reputation, client satisfaction, and overall trust significantly influence client loyalty to the bank. This study provides valuable insights into client behavior and perceptions of banks, emphasizing the importance of factors such as trust, client satisfaction, and bank reputation in shaping client loyalty. Full article
(This article belongs to the Section Banking and Finance)
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43 pages, 2420 KiB  
Systematic Review
Blockchain for Accounting and Auditing—Accounting and Auditing for Cryptocurrencies: A Systematic Literature Review and Future Research Directions
by Ifigenia Georgiou, Svetlana Sapuric, Petros Lois and Alkis Thrassou
J. Risk Financial Manag. 2024, 17(7), 276; https://doi.org/10.3390/jrfm17070276 - 1 Jul 2024
Viewed by 488
Abstract
The aim of this study is to analyze and synthesize the key challenges that are prevalent in the application of blockchain in accounting and auditing, to study the approaches to account for cryptocurrencies, to study the effect of blockchain on the accounting and [...] Read more.
The aim of this study is to analyze and synthesize the key challenges that are prevalent in the application of blockchain in accounting and auditing, to study the approaches to account for cryptocurrencies, to study the effect of blockchain on the accounting and auditing profession, and to identify the current direction of research of blockchain in accounting and auditing, as well as identify potential avenues of future research. The research is based on 75 peer-reviewed academic studies on the topic of blockchain in accounting and auditing, followed by a descriptive and thematic analysis of the literature. Our results indicate that there is a need for more empirical studies to be carried out, which coincides with the notion of growing digitization and blockchain adoption in accounting and auditing. Based on our thematic analysis of the literature, we recommend that future research on blockchain in accounting and auditing should concentrate on the following specific areas: skills and education, governance, auditor independence, accounting standards and regulation, and the challenges faced by the accounting and auditing professions due to the adoption of blockchain technology. Full article
(This article belongs to the Special Issue Blockchain Applications in Finance)
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26 pages, 5452 KiB  
Article
The Impact of Economic Growth on the Ecological Environment and Renewable Energy Production: Evidence from Azerbaijan and Hungary
by Sugra Ingilab Humbatova, Nargiz Hajiyeva, Monika Garai Fodor, Kiran Sood and Simon Grima
J. Risk Financial Manag. 2024, 17(7), 275; https://doi.org/10.3390/jrfm17070275 - 30 Jun 2024
Viewed by 417
Abstract
This article reflects on the necessity of employing renewable energy sources in the modern era to mitigate the negative environmental impact caused by traditional energy sources and address environmental pollution. Through research conducted in Azerbaijan and Hungary, it analyses the influence of economic [...] Read more.
This article reflects on the necessity of employing renewable energy sources in the modern era to mitigate the negative environmental impact caused by traditional energy sources and address environmental pollution. Through research conducted in Azerbaijan and Hungary, it analyses the influence of economic growth on the ecological environment and renewable energy production. Due to limitations in the general dataset, the study considers the period of 1997–2022 for CO2 emissions causing environmental pollution, 2007–2022 for renewable energy production in Azerbaijan, and 2000–2021 for the same in Hungary. Information regarding wind and solar energy in Azerbaijan has been available since 2013. Temporal sequences have been utilised in the research, employing Augmented Dickey–Fuller and Phillips–Perron (PP) unit root tests to examine the stationarity of the time series. An Autoregressive Distributed Lag (ARDL) model has been constructed, and the credibility of the model has been verified using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) models. The findings reveal that in Azerbaijan, the long-term impact of economic growth on hydro-energy has been negative, while dependence on biomass and waste has been insignificant but positive. The influence on wind and solar energy production has also been negative and insignificant, akin to hydro-energy production. However, energy supply from renewable sources has been positively affected by the aggregate indicator of economic growth, albeit insignificantly. The impact of economic growth on carbon dioxide has been significant in two magnitudes, whereas in other cases, it has been insignificant but positive. In Hungary, economic growth has positively affected renewable energy production. However, the impact on carbon dioxide has been negative, meaning that this indicator has decreased as economic growth has increased. The study concludes that the impact of economic growth on indicators of both countries has been more effective in Hungary, which can be attributed to economic development. Full article
(This article belongs to the Section Energy and Environment: Economics, Finance and Policy)
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11 pages, 1092 KiB  
Communication
What’s Wrong with Enterprise Risk Management?
by John Fraser, Rob Quail and Betty Simkins
J. Risk Financial Manag. 2024, 17(7), 274; https://doi.org/10.3390/jrfm17070274 - 29 Jun 2024
Viewed by 388
Abstract
Enterprise risk management (ERM) was introduced in the 1990s and has since become expected by boards of directors and regulators as a sign of good management and good corporate governance. However, many organizations struggle to implement ERM, and still seek practical advice on [...] Read more.
Enterprise risk management (ERM) was introduced in the 1990s and has since become expected by boards of directors and regulators as a sign of good management and good corporate governance. However, many organizations struggle to implement ERM, and still seek practical advice on ERM implementation. This article explains many of the reasons why organizations are unsuccessful in their efforts at implementation and provides practical solutions provided by an experienced risk manager and consultant, an ex-Chief Risk Officer, and an academic, all of whom have written extensively on the subject. This article should be of interest to practitioners involved in implementing ERM, to consultants in ERM, and to academics teaching courses on ERM, risk management, and related topics. This article also provides a base against which further future research can be performed as ERM best practices continue to evolve. Full article
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27 pages, 696 KiB  
Article
The Role of Political Uncertainty in Climate-Related Disaster Impacts on Financial Markets
by Richard Paul Gregory
J. Risk Financial Manag. 2024, 17(7), 273; https://doi.org/10.3390/jrfm17070273 - 29 Jun 2024
Viewed by 236
Abstract
This research presents a new model for analyzing the effects of government policies on climatic disasters on financial markets. Using Fama–MacBeth rolling regressions and the construction of model-proposed risk factors, three major risk factors are found to be significant in explaining stock returns. [...] Read more.
This research presents a new model for analyzing the effects of government policies on climatic disasters on financial markets. Using Fama–MacBeth rolling regressions and the construction of model-proposed risk factors, three major risk factors are found to be significant in explaining stock returns. First, there is the risk of climate disasters. Second, there is the risk of uncertainty regarding government actions. Third, there is the risk of government response to climatic disasters. Through the increase in the cost of capital from climate disasters and the uncertainty of government response, the future cost of capital is higher, leading to less investment and lower productivity. However, the government’s actions to compensate for losses due to climate damage help offset the damages from disasters. This implies that the previous estimates of economic damages due to climate risk have been underestimated. This work adds to the literature by providing a fuller estimate of the economic implications of climate change. Full article
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21 pages, 3778 KiB  
Article
Perspectives on Migration and Financial Markets Research
by Juan David González-Ruiz, Camila Múnera-Sierra and Nini Johana Marín-Rodríguez
J. Risk Financial Manag. 2024, 17(7), 272; https://doi.org/10.3390/jrfm17070272 - 29 Jun 2024
Viewed by 281
Abstract
This study comprehensively analyzes the relationship between migration and financial markets. We examine existing research on this subject using a scientometric and bibliometric approach. By employing VOSviewer and Bibliometrix tools, we introduce a novel methodology that enhances comprehension of this intricate relationship. The [...] Read more.
This study comprehensively analyzes the relationship between migration and financial markets. We examine existing research on this subject using a scientometric and bibliometric approach. By employing VOSviewer and Bibliometrix tools, we introduce a novel methodology that enhances comprehension of this intricate relationship. The findings underscore two significant outcomes. Firstly, the impact of migration on financial markets is evident through the substantial flow of remittances and microfinance. Secondly, this study uncovers challenges hindering the integration of migrants into formal banking systems, thereby affecting financial market dynamics. This research deepens our understanding of migration’s implications on financial markets, offering practical insights that can guide policymakers and financial institutions in their decision-making processes. Full article
(This article belongs to the Special Issue Globalization and Economic Integration)
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48 pages, 461 KiB  
Article
COVID-19 and Non-Performing Loans in Europe
by John Hlias Plikas, Dimitrios Kenourgios and Georgios A. Savvakis
J. Risk Financial Manag. 2024, 17(7), 271; https://doi.org/10.3390/jrfm17070271 - 28 Jun 2024
Viewed by 311
Abstract
This study investigates the impact of COVID-19 on the non-performing loans (NPLs) in Europe, distinguishing by European subregion, country-level prosperity, NPL type, and NPL economic sector. We utilized panel data analysis covering the period 2015Q1–2021Q4 while controlling for macro, bank-specific, and regulatory indicators. [...] Read more.
This study investigates the impact of COVID-19 on the non-performing loans (NPLs) in Europe, distinguishing by European subregion, country-level prosperity, NPL type, and NPL economic sector. We utilized panel data analysis covering the period 2015Q1–2021Q4 while controlling for macro, bank-specific, and regulatory indicators. We derived that the COVID-19 deaths and the strictness of lockdown measures positively affected the NPLs, while the economic support policies exerted a negative effect. Profitable, capitalized banks fared better. The strictness of lockdown measures hindered the ability of SMEs to repay their loans, increasing their NPLs. Sectors involving physical work-related activities also experienced an increase in their NPLs. We also deduced that bank securitization and national culture significantly contributed to NPL reduction. Full article
(This article belongs to the Special Issue Featured Papers in Mathematics and Finance)
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