Search Results (60)

Risk management has become increasingly important in the financial world. Considering its importance, it is necessary to measure these risks. The financial market uses two risk measures: Value at Risk (VaR) and Expected Shortfall (ES). After the subprime crisis, the market began to emphasize ES instead of VaR. The hypothesis of this paper to be tested is that longer periods provide better information than shorter, more recent periods for measuring ES volatility to hedge trades. The ES can be adopted using parametric, semi-parametric, and non-parametric methods, and the analyses of the log return indicators started on 3 January 2000 and ended on 5 May 2023. The analyses carried out to evaluate these log return indicators covered the period from 6 May 2023 to 1 August 2025, where it was found that the exchange rate volatility of the Brazilian Real exceeded the VaR limits and even reached the Expected Shortfall risk zone. Then, a different analysis was performed, starting on 11 March 2020 and ending on 5 May 2023. This second analysis, as the first analysis, was carried out to evaluate these log return indicators that covered the period from 6 May 2023 to 1 August 2025. In this latest period analysis, the exchange rate volatility of the Brazilian Real reached the Exchange Shortfall risk zone in a different way compared to the first way. All three types of methods—parametric, non-parametric, and semi-parametric—show distinct behaviors depending on the period evaluated. The hypothesis was rejected, but the hedging strategies should account for asset volatility. The software used to calculate the estimators was Microsoft Excel 365 and Stata 14.2. Full article

This paper examines bank failures during the subprime mortgage crisis, emphasizing sibling dynamics within multi-bank holding companies (MBHCs). While traditional risk indicators effectively predict failures for one bank holding companies (OBHCs), they exhibit limited explanatory power for MBHCs, where internal capital markets and interdependencies across affiliates shape risk outcomes. We extend the standard failure framework by incorporating group-level characteristics that capture sibling network structure and the distribution of risk across affiliates. Using pre-crisis data from 2006 to 2007, we show that group structure significantly influences failure risk. Larger sibling networks reduce individual bank failure risk through diversification, while greater size dispersion across affiliates increases vulnerability by constraining internal resource allocation. Beyond these aggregate effects, we introduce a weakest link approach that identifies the most distressed affiliate based on extreme tail risk in capitalization, asset quality, liquidity, earnings, and income volatility, capturing organizational fragility that aggregate measures miss. Concentrated vulnerabilities at a single affiliate significantly amplify failure risk throughout the holding company, even after controlling for traditional bank-level fundamentals and parent-level characteristics. These findings, derived from the 2007–2010 crisis, a severe stress test of holding company structures, identify organizational dynamics: resource competition among siblings and concentrated vulnerabilities at the weakest affiliate. Supervisory frameworks should explicitly account for within-group interdependencies rather than relying solely on individual bank metrics or aggregate indicators when monitoring bank holding company structures. Full article

The implications of digital finance for financial stability has come under serious scrutiny since the aftermath of the 2008 global financial crisis (GFC). Empirical evidence on this nexus are somewhat inconsistent and ambiguous. This study therefore attributes this puzzle to multiple structural breaks (MSBs) which were long neglected by previous studies. Consequently, this study aims to identify possible MSBs in the digital finance–stability nexus and examine if its impact is consistent/weakened in the presence of MSBs in a sample of 41 developing African economies for the 2004–2023 periods. Results from the PCA index generation report that instability is more susceptible to bank crisis/Z-score. Again, the panel extension of BP98 MSBs detection identified three breaks with their confidence intervals overlapping the periods of the 2006–2011 GFC/subprime mortgage crises, the 2012–2016 Br-exit referendum and the 2017–2021 COVID 19 pandemic/Ukraine war. The quantile regression methodology also shows that these breaks weaken the impact of digital finance (i.e., mobile banking and internet banking) on financial stability, particularly for economies at lower quantiles of financial stability but with marginal effects for economies at higher quantiles. The study concludes that digital finance can stabilize the financial system of developing economies when shocks from structural breaks are controlled. Therefore, the study contributes to knowledge by developing a new econometric model for BP98 panel extension of MSBs detection, calibrating an index for financial stability and detecting valid break dates for three major breaks. Structural and financial development through policy coordination to forestall the effects of structural breaks were recommended. Full article

Under the background of intensified global economic fluctuations, to prevent the systemic risk of real estate (e.g., the U.S. subprime crisis), this study constructs a linkage network of the real estate industry in the U.S. based on the complex network method, reveals the fluctuation diffusion mechanism, identifies the key pivotal industries through the network characteristic indicators, and analyses the characteristics of the fluctuation conduction paths by applying the industrial fundamental association trees. The study found that (1) the U.S. real estate industry is a ‘supply hub’ industry, with first-order and second-order weighted degrees of mean 6.78, 3.98, and significant asymmetry in the supply structure of the industrial network; (2) industries like architectural, engineering, and related services (541300), nonresidential maintenance and repair (230301), and electric power generation, transmission, and distribution (221100) show high degree centrality and betweenness centrality. Their strong propagation and control capabilities form real estate fluctuations’ core transmission mechanisms; (3) foundational association trees reveal long, broad propagation paths where financial investment and energy-supply sectors act as “traffic hubs,” decisively influencing risk diffusion depth and breadth. Targeted policy recommendations address four dimensions: optimizing industrial chain structures, strengthening financial risk isolation, improving housing supply systems, and enhancing policy coordination. This aims to help China avoid U.S.-style real-estate-bubble risks and achieve coordinated real estate macroeconomy development. Full article

This study explores how machine learning can optimize financial risk management for non-profit organizations by evaluating various algorithms aimed at mitigating loan default risks. The findings indicate that ensemble learning models, such as random forest and LightGBM, significantly improve prediction accuracy, thereby enabling non-profits to better manage financial risk. In the context of the 2008 subprime mortgage crisis, which underscored the volatility of financial markets, this research assesses a range of risks—credit, operational, liquidity, and market risks—while exploring both traditional machine learning and advanced ensemble techniques, with a particular focus on stacking fusion to enhance model performance. Emphasizing the importance of privacy and adaptive methods, this study advocates for interdisciplinary approaches to overcome limitations such as stress testing, data analysis rule formulation, and regulatory collaboration. The research underscores machine learning’s crucial role in financial risk control and calls on regulatory authorities to reassess existing frameworks to accommodate evolving risks. Additionally, it highlights the need for accurate data type identification and the potential for machine learning to strengthen financial risk management amid uncertainty, promoting interdisciplinary efforts that address broader issues like environmental sustainability and economic development. Full article

This article merges evaluations of Black life through the Southern Gothic and the intersection of Black studies to conceptualize the “Black Gothic”. The Black Gothic conceives of a future that requires closely examining the past and the present primarily through a Southern Gothic and Black horror lens. Much of Black Gothic’s analytics depended upon the framework outlined within Afro-pessimism and the subprime; however, it differs in its pursuits of reparations as a way forward. The Black Gothic focuses on intermingling the lived anti-Black experiences of Black existence with supernatural gothic traditions, forcing readers to determine which experience is more horrific. The Black Gothic functions as a mode of interaction with the Southern Gothic and the Black horror visual genres; its definition invokes literary and visual modes and genres that expand the many depictions of Black life in America when it is constantly threatened by elimination and devaluation. The Black horror genre seeks to expose the “afterlife of slavery” through actual and speculative means. Meanwhile, Southern Gothic’s ability to cross temporal bounds makes these the ideal genres to present the enslaved’s repressed and debted history. Southern Gothic replaced ruined gothic castles with plantations; Black Gothic replaced plantations and the monolithic “South” with northern sundown towns, redlining, and subprime mortgages. The Black Gothic’s methodology uses a systemic fiscal devaluation of Black ownership, self, and property through the subprime. In company with Fred Moten’s conceptualization of the subprime, the Black Gothic views being marked as “subprime” as an antecedent to predatory housing practices; it is instead the moment that captured Africans experience social death. Using Toni Morrison’s Beloved and Misha Green’s HBO adaptation of Matt Ruff’s novel Lovecraft Country, I define the Black Gothic and then outline its capacity to function as an analytic to further both the Southern Gothic and Black horror genres. The Black Gothic transcends gothic traditions by including films and texts that are not categorically gothic or horror and exposes the horrific and gothic modes primarily exhibited through the treatment of the descendants of enslaved Africans. Comprehensively, this article argues for a space to view the future re-evaluation of Black life through speculative and practical reparations. Full article

We employ wavelet analysis using the maximum overlap discrete wavelet transform (MODWT) to examine the return and volatility interconnectedness between the German equity market (a prominent representative of the Eurozone market) and the BRICS countries over the period 2005–2017. Specifically, we investigate the presence of the pure form of financial contagion in the stock markets of Brazil, Russia, India, China, and South Africa subsequent to the Eurozone Sovereign Debt Crisis (EZDC). Our results indicate the presence of financial contagion between the Eurozone equity market and its counterparts in South Africa and Russia, characterised by co-movement and volatility spillover effects. This contagion is particularly evident at higher frequencies, suggesting that the transmission of shocks occurs rapidly across these markets in the short term. No financial contagion is observed in the Brazilian, Chinese, and Indian stock markets during the European Sovereign Debt Crisis. The absence of financial contagion observed in these three BRICS countries during the European Sovereign Debt Crisis suggests that policymakers in these countries should prioritise addressing idiosyncratic shock channels. Full article

Stock market indices are important tools to measure and compare stock market performance. The Selective Stock Price (SSP) index reflects fluctuations in a set value of financial instruments of Santiago de Chile’s stock exchange. Stock indices also reflect volatility linked to high uncertainty or potential investment risk. However, economic shocks are altering volatility. Evidence of long memory in SSP time series also exists, which implies long-term persistence. In this paper, we studied the volatility of SSP time series from January 2010 to September 2023 using fractionally heteroskedastic models. We considered the Autoregressive Fractionally Integrated Moving Average (ARFIMA) process with Generalized Autoregressive Conditional Heteroskedasticity (GARCH) innovations—the ARFIMA-GARCH model—for SSP log returns, and the fractionally integrated GARCH, or FIGARCH model, was compared with a classical GARCH one. The results show that the ARFIMA-GARCH model performs best in terms of volatility fit and predictive quality. This model allows us to obtain a better understanding of the observed volatility and its behavior, which contributes to more effective investment risk management in the stock market. Moreover, the proposed model detects the influence volatility increments of the SSP index linked to external factors that impact the economic outlook, such as China’s economic slowdown in 2012 and the subprime crisis in 2008. Full article

This study aims to answer the question about the interactions between “investors’ fear”, two factors proposed by Fama & French, the Carhart momentum factor, andthe risk premium, and how these interactions were affected by two financial crises, the Dot-Com and Sub-Prime crises. This paper is the first empirical study that considers the effects of these financial crises. It is of critical importance as it changes the specificity of the empirical models for different periods, significantly affecting the results compared to previous research work. The main findings include a general negative change in fear over all of the sub-periods. Secondly, no consistent positive trend was observed in any of the risk premiums over time. After each crisis, the relationships between the endogenous variables had significant changes. More specifically, investors’ fear, on the first day of the week, appears to be systematically higher across all sub-periods except during the Sub-Prime crisis. Finally, after the Sub-Prime financial crisis, there is an almost complete loss of the explanatory power of the VAR models. Although fear does not seem to affect risk premiums or momentum, it was nevertheless found that the results are sensitive to the specification of the models. Full article

This paper extends the literature on the relationship between oil price shocks and financial markets by examining the effect of supply and demand oil shocks on emerging energy markets, stocks of emerging markets, and gold and exploring the impact of unpredictable oil events on the degree of connectedness among these markets. We show that the effect of supply oil price disturbances drives volatility spillovers in emerging markets with prominent medium- and long-term effects, unlike demand oil price unanticipated changes, particularly during turbulent periods such as the 2008 subprime crisis, the COVID-19 pandemic, and the 2015 oil price crash. These volatility spillover effects are influenced by a marked relationship between supply oil disturbances and emerging energy markets. We also expose that the COVID-19 pandemic volatility spillover consequences in emerging markets are unprecedented compared to the 2008 financial crisis. This can be attributed to the different nature of the related oil price disturbances and financial crises. Overall, the findings highlight the role of crude oil supply shocks as drivers not only of volatility dynamics in energy and equity emerging markets but also of financial connectedness patterns in these economies. Full article

Corruption influences firm behavior and performance even in relatively transparent countries like the United States. In this paper, we examine whether corruption at the state level affected bank failures during the subprime mortgage crisis. Our measure of corruption is the number of corruption convictions of government employees (adjusted for population) based on the Public Integrity Section (PIN) reports from the Department of Justice, capturing the degree of “public corruption” in the US. After disaggregating the data based on bank size and geography, we find that corruption is associated with more bank failures for smaller banks and fewer bank failures for banks located in the South. This research marks a pioneering attempt to examine the connection between corruption and bank failures while underscoring the significance of political risk for financial institutions. Given the recent setbacks experienced by Silicon Valley Bank, Signature Bank, and First Republic Bank, this research provides valuable recommendations for policymakers. The findings suggest the need for regulators to mandate greater transparency regarding banks’ exposure to undisclosed risks, such as political risk. It also advocates for implementing internal control mechanisms to curb corrupt activities. Full article

The objective of this study was to determine the influence of hempseed meal (HSM) on goat meat characteristics. Goats (N = 10/treatment) were allocated to a diet concentration (0, 10, 20, or 30%) of HSM, fed for 60 days, and harvested. Carcass measurements were collected after chilling, and subsequently fabricated into wholesale subprimals. From the subprimals of the shoulder and leg, steaks were cut 2.54 cm thick, vacuum packaged, and assigned to laboratory methods: cook yield, instrumental color, lipid oxidation, microbial spoilage, and instrumental tenderness. HSM did not alter (p > 0.05) carcass characteristics, microbial spoilage, cook loss, or the thiobarbituric acid reactive substance (TBARS). However, a decrease in objective tenderness measurements (p < 0.05) was observed with greater concentrations of HSM supplementation in the diet. Instrumental surface color values for lightness (L*) indicated that steaks became lighter and less red (a*) as storage time increased (p < 0.05). Results suggest that HSM and storage time do not alter some goat meat traits, but HSM or storage time separately may influence goat meat quality. HSM may be an effective feed ingredient that does not alter carcass quality or meat yield. Full article

Plant-derived smoke and smoke water (SW) can stimulate seed germination in numerous plants from fire-prone and fire-free areas, including cultivated plants and agricultural weeds. Smoke contains thousands of compounds; only several stimulants and inhibitors have been isolated from smoke. Among the six karrikins present in smoke, karrikin 1 (KAR₁) seems to be key for the stimulating effect of smoke. The discovery and activity of highly diluted SW and KAR₁ at extremely low concentrations (even at ca. 10⁻⁹ M) inducing seed germination of a wide array of horticultural and agricultural plants have created tremendous opportunities for the use of these factors in pre-sowing seed treatment through smoke- or KAR₁-priming. This review presents examples of effects exerted by the two types of priming on seed germination and seedling emergence, growth, and development, as well as on the content of some compounds and enzyme activity. Seed biotechnology may involve both SW and KAR₁. Some examples demonstrate that SW and/or KAR₁ increased the efficiency of somatic embryogenesis, somatic embryo germination and conversion to plantlets. It is also possible to stimulate in vitro seed germination by SW, which allows to use in orchid propagation. Full article

With the rise of Industry 4.0, its pillars (which include Internet of Things, “Big Data”, data analytics, augmented reality, cybersecurity, etc.) have become unavoidable tendencies for the automated manufacturing industry. Equipment upgrade is required to match the new standards of digitally assisted automation. However, not all factories in the medium to small range (or independent manufacturers) can afford to upgrade their equipment. Therefore, the availability of affordable Industry 4.0 upgrades for now-outdated devices is necessary for manufacturers in the SME range (Small-Medium Enterprises) to stay relevant and profitable. More specifically, this work revolves around the automation of printed circuit board (PCB) manufacturing, which is one of the most popular and profitable areas involved in this movement; and within it, the large majority of manufacturing defects can be traced to the soldering or “reflow” stage. Manufacturing research must, thus, aim towards improving reflow ovens and, more specifically, aim to improve their autonomous capabilities and affordability. This work presents the design and results of a controlling interface utilizing a Raspberry Pi 4 as a coupling interface between an MQTT Broker (which monitors the overall system) and the oven itself (which is, intentionally, a sub-prime model which lacks native IoT support), resulting in successful, remote, network-based controlling and monitoring of the oven. Additionally, it documents the design and implementation of the network adaptations necessary for it to be considered a cybersecure IIoT Module and connect safely to the Production Cell’s Subnet. All of this to address the inclusion of specific Industry 4.0 needs such as autonomous functioning, data collection and cybersecurity in outdated manufacturing devices and help enrich the processes of SME PCB manufacturers. Full article

The development of globalization has brought about obvious differences in the resilience of different regions against economic crises. Regional economic resilience refers to the ability of a region’s economy to resist shocks when faced with external disturbances or to break away from its existing growth model in favor of a better path, Resilience represents the region’s adaptability, innovation, and sustainability. This paper describes an empirical analysis on the 60 designated industrial park developments under the Industrial Development Bureau in Taiwan. Over a period of short-term disturbances, the industrial parks are analyzed from four aspects: industrial structure, regional development foundation, enterprise competitiveness and labor conditions, and government governance and policy systems. Through discriminant analysis, we analyze the characteristics of factors that mainly affect the economic resilience of 60 industrial parks faced with shocks such as the subprime mortgage crisis in 2008, the five-day work week in 2016, and the COVID-19 outbreak in 2019. We found that industrial structure, specifically diversified industrial structure, is the major factor behind enhanced regional economic resilience. If the scale of specialized industries is large enough, they can form sufficient capacity to resist external changes and also be economically resilient. Under the negative impact, the amount of innovation can be an important part of post-disaster recovery, and stable innovation input will become a main factor for the sustainable development of industrial parks. The pressure of the uncertainty of global economic development and the transformation and upgrading of the domestic economy underscore that enterprises urgently need automation and digital transformation to enhance their competitiveness. In order to enhance economic resilience to adapt to changes in the overall environment, the industrial parks need to adjust adaptively, improve their industrial structure, and promote innovation, hoping that the regional economy will move towards a more stable and sustainable development path. Full article