This paper attempts to apply the vine copulas methodology to assess the interdependence among the exchange rate market, equity indices, precious metals and energy resources within the selected BRICS economies. Using the ARFIMA-GJR-GARCH model, the residuals of the daily returns from foreign exchange rates, precious metals, equity indices, and energy prices of the BRICS economies for the period from January 1, 2003, to August 2023 were filtered. The empirical findings reveal a persistence of shocks and an asymmetric response to positive and negative news. Elevated volatility was observed across equity, precious metals, and energy markets, indicating substantial risks that necessitate robust risk management strategies. The results illustrate the heightened sensitivity of BRICS economies to external shocks, such as the Global Financial Crisis and the COVID-19 pandemic, which have triggered market volatility across currencies, stock market returns, and energy prices. This study emphasises the crucial importance of diversification, given the strong co-movement among asset classes, particularly during periods of extreme market volatility. Furthermore, the vine copulas analysis reveals intricate co-movements between assets, contributing to enhanced portfolio management strategies. Assets such as oil and gold serve as effective hedges. At the same time, foreign exchange rates play a significant role in investment decisions, underscoring the necessity for meticulous risk assessment and diversification strategies. These findings emphasize the vulnerability of BRICS economies to external shocks and highlight the imperative of effective risk management and diversification in navigating these dynamic markets. • ARFIMA-GJR-GARCH and C/D-vine copulas capture BRICS multi-asset dependence • C-vine fits Brazil, Russia, China; D-vine suits India and South Africa • Silver is central node; lower-tail dependence links silver with BRICS assets. • Oil and gold hedge; weak tau pairs provide diversification • Asymmetric tail risks stress need for volatility-aware BRICS risk management

Purpose This study examines the valuation of European-listed real estate companies by assessing the value relevance of accounting-based performance metrics – earnings per share (EPS), return on equity (ROE) and dividend per share (DPS) – as complementary or alternative indicators to the traditionally dominant net asset value (NAV). Design/methodology/approach Using a panel dataset of 102 firms from 2005 to 2024, the study applies three regression models – share price, price change and share return – alongside a difference-in-differences (DiD) approach to capture structural shifts during the 2008–09 financial crisis and the 2021–23 COVID-19 and interest rate hike period. Findings The findings reveal that EPS and DPS are the most consistent and significant predictors of share prices, with DPS showing the highest explanatory power, particularly during the COVID-19 and interest rate hike period. ROE is the strongest predictor of share returns, especially in times of economic stress. Sectoral effects are generally weak, indicating that firm-level financial performance outweighs industry classification in explaining market valuation. Research limitations/implications The study is subject to potential biases in sample selection such as firm size, geographic and market classification, language. The sample is representative of large, liquid and internationally oriented firms, the findings may not generalize to smaller, less liquid or emerging market companies. Practical implications For analysts, integrating accounting metrics alongside NAV enhances valuation accuracy and comparability. For generalist investors, understanding which factors consistently influence prices can inform long-term valuation models, portfolio construction and risk assessment. For practitioners, it provides a robust, multi-metric valuation framework that enhances decision-making by integrating familiar financial indicators with traditional asset-based measure. Originality/value The DiD framework is employed to capture how investor responds to financial metrics shift across crisis and COVID-19 and interest rate hike periods (2008–2009 and 2021–2023). Use of three regression models – share price, share price change and share return – isolates the explanatory power of each financial metric under varying market conditions. Sector-level analysis offers insights into performance heterogeneity. For academic research, it fills a gap in European real estate literature by empirically testing the relevance of accounting metrics in stock valuation, an area previously dominated by NAV-based approaches.

This study aims to analyze the Islamic economic perspective on riba and its implications in the modern financial system. Riba is strictly prohibited in Islam as it involves elements of injustice and economic exploitation. This research employs a qualitative approach with a normative method through library research. The data used are secondary data obtained from the Qur’an, Hadith, books, and scientific journals related to Islamic economics and riba. The findings indicate that riba has substantial similarities with interest in the modern financial system, particularly due to the predetermined additional payment without risk-sharing. Furthermore, riba has negative impacts on economic and social structures, such as increasing wealth inequality, debt burdens, and the potential for financial crises. As an alternative, Islamic economics offers a profit and loss sharing system that is more just and sustainable. Therefore, the prohibition of riba is not only normative but also relevant in creating a stable and equitable economic system.

This study will analyze the relationship between two variables: the independent variable, the number of bank accounts in Iraq, and the dependent variable, the volume of bank deposits. The research hypothesis assumes a direct relationship between these two variables. After collecting data on four Iraqi banks and their deposit volumes over a decade (2015–2025) and comparing the change in deposit volume with the number of bank accounts in Iraq, the hypothesis was not supported. An increase in the number of bank accounts in Iraq does not necessarily mean an increase in the amount of money held in them, because most of these accounts were opened recently to transfer public sector employee salaries, and in most cases, the funds are withdrawn only once. In addition, other bank accounts are subject to influences such as financial or health crises or even negative rumors, which lead depositors to withdraw their money and hoard it or convert it into foreign currencies or precious metals.

Europe has experienced multiple crises, including inflation, rising food and living costs, the COVID-19 pandemic, and the 2007-2009 financial crisis, which have contributed to widening social inequalities. These economic pressures may threaten the material well-being of adults aged 50 and older, yet little is known about how they affect those who provide care. This study examined the risk of material deprivation among those with different caring roles in 2021-2022 using the SHARE data. The findings show that co-resident family caregivers, those experiencing financial strain, and individuals with a migrant background are particularly vulnerable to material deprivation. Women carry a disproportionate share of caregiving responsibilities and face higher deprivation risks than men. In contrast, individuals who provide care outside their households or care for grandchildren tend to exhibit better material well-being than those without these roles. Targeted policy measures that both alleviate energy poverty and financial strain are needed.

Abstract: Predicting systemic financial crises and executing optimal asset reallocation during severe market stress remains a formidable challenge in algorithmic trading and quantitative risk management. Traditional classification models frequently fail in these environments due to high false-positive rates (the “boy who cried wolf” paradigm) and severe class imbalance, which often manifests as a rigid bias toward historically dominant safe havens like Gold. This paper proposes a personal-level, non-commercial Hybrid Machine Learning pipeline designed to resolve these structural flaws. The architecture consists of two stages: a Random Forest Classifier trained to detect Black Swan events using a refined set of 11 macroeconomic indicators, and a Multi-Output Random Forest Regressor that forecasts the 3-month expected returns of four primary asset classes (S&P 500, Gold, US Dollar, and 10-Year Treasury Bonds). By forecasting exact percentage returns rather than categorising “winning” assets, the framework natively circumvents safe-haven bias without relying on synthetic data generation techniques such as SMOTE. Stress testing against historical scenarios, including the 2020 pandemic crash and theoretical deflationary liquidity crunches, demonstrates that the model executes highly rational, dynamic reallocations. Validated through strict time-series cross-validation over a 26-year timeline, the framework effectively preserves capital while maintaining a near-zero false-positive detection threshold. Keywords: Black Swan Detection · Random Forest · Multi-Output Regression · Asset Allocation · Systemic Risk · Macroeconomic Indicators · Quantitative Finance · Walk-Forward Validation

Purpose This study aims to examine whether the start of Ramadan is associated with abnormal stock market returns across global financial markets and whether these effects vary over time and across different financial conditions. Design/methodology/approach Using daily stock index data from 78 countries for 2006–2025, the study uses an event-study methodology centered on the first trading day of Ramadan. To isolate the direct impact of localized cultural practices, the study attempts to contrast the global aggregate analysis with a dedicated sub-sample of 20 Muslim-majority countries. Abnormal returns (ARs) are calculated using a constant mean return model, and cumulative average abnormal returns (CAARs) are evaluated across multiple event windows. A statistical inference is conducted using the Wilcoxon signed-rank test. Findings The results show that Ramadan-related ARs are time-varying rather than persistent. While the magnitude and statistical significance of these returns are substantially amplified in Muslim-majority markets, the direction of the effect remains fundamentally state-dependent across all sub-samples. Significant ARs are often observed in pre-event windows, suggesting that investors anticipate events. The magnitude and direction of these effects vary across years and are amplified during periods of financial stress, such as the global financial crisis and the COVID-19 period. Research limitations/implications The analysis relies on aggregate market indices and does not examine firm-level heterogeneity or directly measure behavioral channels such as investor sentiment or liquidity changes. Practical implications The findings highlight the importance of incorporating cultural and religious calendar events into financial risk assessment and portfolio management, particularly during periods of heightened market uncertainty. Originality/value To the best of the authors’ knowledge, this study provides the first comprehensive global event-study analysis of Ramadan effects across 78 countries over two decades. It demonstrates that religious calendar effects are conditional, time-varying and shaped by broader financial environments.

Depression is an extremely common psychiatric condition, for which many neurochemical theories exist. Environmental stressors can be closely related to the onset or worsening of depressive symptoms. Among these are grief over the loss of important people in the individual's life, marital or financial crises, abrupt changes in social or cultural patterns, adaptive difficulties, physical and psychological trauma, diagnosis of serious or chronic illness, etc. Depressive syndromes are complex and involve biological, behavioral, psychological, social, and cultural factors. There are two distinct types of depressive syndrome: unipolar depression (major depression) and bipolar depression. Depression is the most common mood disorder, ranging from very mild alterations bordering on normality to severe depression accompanied by hallucinations and delusions, standing out worldwide as a significant cause of disability and premature death. The general objective of this study is to understand the importance of pharmaceutical care in the treatment of patients with depression. This is a literature review that uses the SCIELO, LILACS, Google Scholar, Medline, and PUB-MED databases, including articles published between 2016 and 2026. Among the main treatments used for this pathology, antidepressants stand out, aiming to improve the quality of life or even cure patients with this condition. Research has demonstrated the importance of pharmaceutical care within the multidisciplinary team in the care of patients with depression, preventing problems and possible medication errors, thus improving adherence, effectiveness, and the quality of life of the depressed patient.

ABSTRACT This paper examines the political-economic drivers of federalization and de-federalization, focusing on how historical and institutional factors influence multilevel governance. By comparing the European Union (EU), Switzerland, and the Italian Autonomous Region of Trentino-Alto Adige (TAA), we analyze how multilingual systems manage policy competences across different government levels, especially during crises. Despite differences in size and context, these entities show similar trends in the forces behind federalization and de-federalization. Their multilingual populations and multilevel systems complicate political coordination and administrative structures, with policy competency distributions often driven by political rather than theoretical motivations. We propose that better alignment with political-economic theory could enhance efficiency, accountability at decentralized levels, and institutional resilience during major shocks like the global financial crisis or the COVID-19 pandemic. Our findings indicate that Switzerland aligns quite closely with fiscal federalism principles, while the EU shows more inconsistent patterns in this regard, while gradually moving towards a more federal political structure. By comparison, TAA reflects part of (federalizing) EU subnational trends.

In the context of political and financial market turmoil, effectively forecasting financial market trends is crucial for investment decisions. Large language models (LLMs) have been applied in extant research to predict market trends, analyze investor sentiments and interpret financial news, all aiming to help investment decision making. However, LLMs face limitations due to training data heterogeneity, restricting multidimensional perspectives and hindering comparative analysis for optimization. This study proposes a “Dual-Agent LLM Debate Mechanism” framework using a Proponent (LLM1: Gemini Pro 3) and an Opponent (LLM2: ChatGPT 5.2) to address single-LLM forecasting gaps: The Proponent generates a baseline forecast (F1) from an Integrated Context, while the Opponent validates and resolves conflicts with the Proponent via up to three rounds of cross-debate to produce a consensus forecast (F2). A controlled experiment was conducted to analyze 75 financial market indicators (FMIs) across five asset categories, revealing that F2 outperforms F1 in accuracy and directional stability, particularly in highly volatile assets like Cryptocurrencies and 10-Year Government Bonds. Paired-sample t-tests confirmed statistical significance, validating the mechanism’s effectiveness. Our study results demonstrate how cross-debate between LLMs enhances forecasting accuracy through structured optimization.

Efficiency refers to the performance level corresponding to using minimal inputs to achieve the maximum possible outputs. Despite its importance to the Canadian economy, such performance assessments has rarely been undertaken in the hardware retail industry in recent years. We present the results of a recent study of the relative efficiencies for three major chains of hardware and renovation retail stores operating in Canada (Home Depot, Lowe’s and Rona). We use the classic and bootstrap data envelopment analysis (DEA) models to measure performance levels over the 22 years from 2000 to 2021. Overall, the firms exhibited high efficiency during this period, and operations management was the primary source of inefficiency. However, an analysis of trends over the 22 years shows that all three companies experienced periods of declining efficiency at the beginning of the study period, followed by a phase of recovery that appears to have accelerated towards the end of the study period. Our longitudinal analysis also indicates that recent shocks and crises have impacted the firms. The succession of crises at the end of the 2000s, the 2007 forestry crisis in Canada, and the 2008 global financial crisis led to the lowest period of efficiency for all the firms, from which they started rebounding in 2011. The specific impact on Rona can explain Lowe’s acquisition of Rona in 2015. However, such a move did not seem to have had a significant improvement beyond accelerating a recovery that had started a few years earlier. This may explain Lowe’s sale of all its Canadian operations in 2022, leading to a new firm called Rona+. Finally, the COVID-19 pandemic also seems to have had a similar effect: accelerating the recovery from the 2008 financial crisis that the firms had started in 2011.

ABSTRACT Our study aims to explore the potential impact of natural disasters on corporate dividend policies. This research encompasses 128 global countries from 1990 to 2023. We demonstrate a significant positive correlation between natural disasters and corporate dividends. To mitigate endogeneity concerns, we apply ITCV, Oster (2019), Two‐Stage Least Squares (2SLS), Lewbel (2012) methodology, and Entropy Balance (EB), and difference‐in‐differences (DID), which yielded consistent results. Our analysis also reveals that cash holdings and leverages are crucial channels that mediated natural disasters on dividend policies. Further investigation reveals that the positive relationship between natural disasters and increased corporate dividends is more amplified during non‐crisis periods but becomes negligible during financial crises. This effect is stronger in Asia and the Americas than in other regions and is more evident in BRICS countries than in OECD countries.

Abstract Enhanced index tracking (EIT) problem seeks to construct a portfolio that not only mirrors the market index movements but also delivers superior returns. In formulating this problem, historical data are typically treated as scenarios. However, this view may lead to information loss, as historical patterns are not guaranteed to recur in the future. To account for potential deviations from historical scenarios, this paper presents a robust formulation for the EIT problem. Two error functions are considered to quantify the deviation of the portfolio return from the index return: the mean‐squared deviation (MSD) and the mean‐squared downside deviation (MSDD). The robust formulation of the problem for the MSD tracking error presents significant challenges. This paper, first, discusses the difficulties associated with incorporating the MSD error and clarifies why the methods used for the MSDD‐based formulation cannot be directly applied to the MSD‐based model. Then, the problem with the MSD error is formulated as a bi‐level optimization model and is solved with a decomposition‐based heuristic, employing a least‐absolute‐shrinkage‐and‐selection‐operator (LASSO)‐based technique to handle the cardinality constraint. To assess the robustness of the proposed model under extreme market conditions, we evaluate its performance on the 2008 financial crisis and the Corona‐virus‐desease‐2019 (COVID‐19) pandemic. Experimental results on major international stock market data highlight the superiority of the MSD‐based model over MSDD‐based robust models. Furthermore, the proposed model is also compared with three recently developed and well‐established EIT models, and the results demonstrate that the proposed approach delivers good performance in comparison to other models as well.

ABSTRACT During the financial crisis of 2008, the US economy experienced a sharp contraction in mortgage credit supply. Previous research indicates that voters responded to the 2007–2008 financial crisis by punishing the incumbent party in the presidential election of 2008. To further investigate the electoral consequences of the crisis, we use an individual‐level data set comprising millions of loan application outcomes to study the impact of mortgage credit contractions on the 2008 House and Gubernatorial elections. We employ a two‐stage approach to estimate the effect of mortgage market conditions on election outcomes. In the first stage, we construct a measure of the change in mortgage credit supply from 2004 to 2008, controlling for demand‐side factors. In the second stage, we estimate the effect of this change on the change in the challenger party's vote share. Our results indicate no statistically significant impact of mortgage credit contractions on House or Gubernatorial election outcomes. This finding suggests that voters primarily hold the president accountable for changes in mortgage credit conditions, while lower level officials are not perceived as responsible for these shifts.

Abstract This Symposium analyses how European Union (EU) member states have adjusted domestic policies in response to the evolving governance of the single market since the 2008 financial crisis and subsequent EU shocks. Confronted with new opportunities and constraints, countries have adopted diverse forms of domestic agency that have, in turn, reshaped the de facto governance of the single market. We focus on Central and Eastern Europe (CEE), where such forms of agency have been novel and unexpected, given the region's high transnational dependency and their traditional position as passive EU rule‐takers. We show that CEE states have engaged creatively with EU‐level changes, often mobilising actors beyond central governments to tackle domestic economic challenges. This editorial introduction traces the evolving interdependence between CEE agency and the EU's institutional regime, whilst the four empirical contributions examine how CEE countries have leveraged new EU incentives and limitations in practice, with a focus on the manufacturing and finance sectors. Our findings reveal a critical tension: the EU's governance shifts since 2008 have produced a hybrid regulatory framework that combines tighter supranational constraints in some domains with expanded scope for adaptive and experimental domestic agency in others. CEE states have leveraged this uneven regulatory space in creative ways, but outcomes in terms of economic upgrading and convergence remain mixed and uncertain. We conclude that this hybrid governance framework risks entrenching fragmentation within the single market and reinforcing the socio‐economic challenges of the EU's Eastern periphery. By questioning assumptions of minimal CEE agency in managing transnational dependencies and by identifying the specific forms of domestic agency that have emerged in the region since 2008, the Symposium underscores the need to balance national experimentation with strategic economic cohesion and co‐ordination at the EU level.

The present study explores the forecasting performance of two distinct methods: Historical Simulation (HS) and Monte Carlo (MC). The aforementioned approaches find application in the estimation of VaR of the CBOE Volatility Index (VIX), a benchmark of paramount importance in the assessment of market risk. As financial institutions increasingly rely on VaR models to quantify volatility risk, the choice between computationally efficient but potentially oversimplified HS approaches and MC methods, though more sophisticated, is a key operational decision. This study employs a rolling-window framework with 10-year calibration periods to analyse a three-decade period of VIX data (1990-2023). This methodology is utilised in order to draw comparisons between standard HS, crisis-adjusted HS, and MC simulation incorporating Ornstein-Uhlenbeck processes. The findings reveal that the MC approach attained a statistically significant 12.7% reduction (p <0.01) in 95% VaR forecast errors when compared against HS during normal volatility periods (VIX <25). Furthermore, the MC approach exhibited superior crisis performance, with breach rates deviating 8.2% from theoretical expectations, in contrast to the HS approach, which deviated 31.4%. However, it is important to note that this was achieved at a substantial computational cost of 117 times the processing time (9.4 seconds vs. 0.08 seconds per estimation). The findings of the study provide a decision framework grounded in empirical evidence. It is asserted that the implementation of weighted HS is to be recommended for scenarios involving high-frequency monitoring, and that MC is to be employed for stress testing scenarios. The robustness of the decision framework has been demonstrated to be reliable on multiple occasions, as evidenced by its application during significant market events. These include the 2008 financial crisis and the 2020 pandemic volatility spike. The present text provides practitioners with guidance for the implementation of volatility risk management systems, which has been empirically validated.

International energy price changes can lead energy-importing economies to adjust their input factor choices, and Korea provides a useful case given its very high dependence on imported primary energies. This study estimates a primary energy input-demand system for Korea using quarterly data from 2000 to 2021, covering coal; crude oil; natural gas; labor; and others, including non-primary energy inputs. Our analysis uses LA-AIDS specifications. Breakpoint unit-root and cointegration tests support structural change around the global financial crisis, and this shift is incorporated through period-specific parameters within a unified demand system. The compensated elasticities indicate that crude oil becomes more price sensitive after the break, while coal and natural gas become less responsive to their own prices. Cross-price relationships also change, with weaker substitution among the primary energies and greater substitution between crude oil and others. These findings suggest that the ability to adjust inputs and the economic effects of international price changes can vary over time, which should be taken into account in energy policy evaluation.

This study examines the time–frequency dynamics between CO2 emissions and their determinants—oil prices, renewable energy deployment, and climate policy uncertainty—in Türkiye from 1987Q2 to 2024Q1. We integrate a rolling-window Nonlinear Autoregressive Distributed Lag (NARDL) model with wavelet coherence analysis to capture evolving asymmetric effects and multi-scale transmission mechanisms. Our findings reveal pronounced, persistent asymmetries. Oil price decreases stimulate CO2 emissions substantially more than equivalent price increases reduce them, yielding a negative asymmetry effect. Renewable energy demonstrates a stable, negative long-run relationship with emissions, with wavelet analysis indicating this effect concentrates over medium-to-long-term horizons, underscoring its structural decarbonization role. Climate policy uncertainty exerts fragmented, episodic influences, disrupting short-to-medium-term emission trajectories. Rolling-window estimates confirm these asymmetric relationships shift markedly around structural breaks, including the 2001 domestic crisis and the 2008 global financial crisis. The study concludes that effective decarbonization requires temporally calibrated policies: counter-cyclical carbon pricing to offset oil price asymmetries, and credible long-term frameworks to sustain renewable energy investments. Methodologically, the results demonstrate the value of combining time-domain and frequency-domain techniques to diagnose complex, evolving interactions in the energy–environment nexus.

ABSTRACT This study examines the relationship between internationalization and environmental, social, and governance (ESG) controversies, focusing on whether foreign directors on corporate boards influence this relationship. Drawing on resource dependence theory, we argue that internationalization increases ESG controversies due to the complexity of managing diverse regulatory environments and stakeholder expectations. Although foreign directors may contribute valuable global expertise and networks, they can either mitigate or exacerbate these controversies depending on their advising and monitoring capabilities. Using a sample of 5834 firm‐year observations from US companies, we find a positive association between internationalization and ESG controversies. Additionally, foreign directors significantly exacerbate the effect of internationalization on ESG controversies. Our results, which underscore the adverse impact of internationalization and culturally diverse boards on ESG controversies, remain consistent after a battery of sensitivity tests and the addressing of potential endogeneity concerns. Our results are also robust to external shocks, such as the global financial crisis and the COVID‐19 pandemic. This research advances the literature on corporate governance and sustainability, offering practical insights for policymakers and firms on the importance of strategic board composition and effective governance structures for managing ESG risks across global operations.

Abstract Asset managers, private equity firms and other institutional investors have assumed an increasingly important role in the ownership and management of housing and infrastructure since the Global Financial Crisis. This article analyses how social housing in London is being transformed into a financial asset through an analysis of ‘income strip’ leases, long‐term contractual arrangements between institutional investors and local authorities. Building on insights from urban political economy and the social studies of finance, we explore the moral politics, temporal logics and forms of obligation and risk embedded in these financial arrangements. We situate the rise of income strips within a longer arc of state–market entanglements and argue that they exemplify a recursive and cyclical tendency in the local state's experimentation with private finance. At the level of the contract and the asset, we show how value and risk are distributed and negotiated, and how income strips produce hierarchies of obligation and indebtedness. While institutional investment into social housing is narrated as a ‘common sense’ policy solution that promises to fill the ‘housing gap’ and secure returns for workers’ retirement savings, we show how income strips erode security of tenure, increase rents and entangle states and tenants in new forms of financial obligation, foreclosing alternative political imaginaries.