Search Results (4,223)

This paper proposes a new model with the goal of improving several aspects of the modern portfolio theory: (i) investor behavior, (ii) depiction of behavior in the fractal stochastic differential equations about price efficiency in chaotic dynamics (Tsallis statistics) and the fractal market hypothesis, (iii) the introduction of the novel Evolving Returns Integrated System (ERIS) in portfolio selection in the fractal behavioral convolution, and (iv) the selection of an accurate classifier (ERIS) among three neuro-genetic hybrids of 66 models: 22 modular, 22 Jordan–Elman and 22 generalized feedforward networks. Our model demonstrates superior classification performance across the Greek (1996–1998) and NYSE (2008–2010) equity market datasets examined in this study. Full article

This study investigates the role of big data analytics (BDA) on the relationship between environmental, social, and governance (ESG) scoring and Saudi listed firm value over the four-year period from 2021 to 2024. We employed structural equation modeling (SEM) as a path analysis and a 5000-replication bootstrap method to evaluate the mediation effect of BDA and to enhance inferential robustness. The findings indicate a partial mediation effect of BDA on the relationship between ESG scoring and Tobin’s Q, indicating that ESG contributes to firm value partly through BDA capabilities. The findings underscore the role of leverage ratio and firm size as predictors of BDA effect on firm value. The study is grounded in stakeholder, signaling, and resource-based theories, arguing that ESG performance builds stakeholder trust, ESG scores signal firm value, and BDA capabilities act as strategic assets that enhance market valuation. The findings emphasize the importance of Saudi investors supporting the integration of BDA within ESG practices to maximize firm value, consistent with stakeholder theory. This study contributes to the literature in two ways. First, it demonstrates the mediating role of BDA in the ESG–firm value nexus, reinforcing the market relevance of ESG signals in line with signaling and resource-based perspectives. Second, it extends empirical evidence on the strategic role of BDA in ESG contexts within emerging markets. For policymakers, the results suggest that ESG initiatives require complementary investments in BDA capabilities to achieve their value potential. Full article

Carry strategies in developed markets are well studied, but their effectiveness in emerging government bond markets remains less well understood. This study analyzes cross-curve carry strategies in the Indonesian government bond market from June 2009 to June 2025. The findings indicate that a term spread-based carry long–short portfolio delivers positive returns and exhibits persistence across rolling 10-year horizons throughout the sample period. However, performance tends to weaken during episodes of local currency depreciation. Duration-matched long-only carry portfolios also outperform the market benchmark after transaction costs, indicating practical value for investors. Overall, the findings suggest that carry strategies can be effective in the Indonesian government bond market and that the term spread-based carry measure provides a more robust signal than the alternative specification that incorporates roll-down effects. Full article

The relationship between financial literacy and capital market participation remains a central focus of both theoretical and empirical research in behavioral finance. However, existing research has predominantly relied on direct-effect, mediation, or moderation frameworks, thereby offering only a partial understanding of how individuals make investment decisions under uncertainty. To address this limitation, this study develops a sequential cognitive–affective framework by integrating the Theory of Planned Behavior (TPB) and the Risk-as-Feelings Hypothesis (RFH). Within this framework, investment intention is conceptualized as the outcome of cognitive evaluations and affective responses, with financial literacy influencing these processes by shaping perceived risk and institutional trust. Utilizing a multistage sampling strategy, survey data were collected from 449 individual investors and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that financial literacy is positively associated with investment intention, both directly and indirectly through a sequential mediation pathway. Specifically, higher financial literacy is associated with lower perceived risk, which subsequently strengthens trust in financial institutions and ultimately increases investment intention. These findings suggest that financial literacy functions not only as a cognitive resource but also as a psychological mechanism that influences how individuals interpret and respond to financial uncertainty. By validating a sequential cognition–affect pathway, this study provides a more comprehensive behavioral explanation for the inconsistent findings reported in prior research. The findings further suggest that financial literacy initiatives designed to address risk perceptions and institutional trust may be more effective in promoting capital market participation than programs focused solely on information provision. Full article

This study examines how investors’ perceptions of artificial intelligence (AI) are associated with investor behavior, focusing on short-term and long-term investment strategies and their implications for investor resilience. While prior research has primarily emphasized the technical capabilities of AI in financial decision making, less is known about how investors perceive these technologies in practice. Using survey data from 221 individual investors and partial least squares structural equation modeling (PLS-SEM), the study analyzes how different dimensions of AI perception affect investment strategies. The results show that perceived efficiency and positive expectations regarding the future role of AI positively influence both short-term and long-term investment strategies. In contrast, perceived accuracy is associated with lower engagement in short-term strategies, suggesting greater reliance on AI-generated recommendations. Most notably, perceived forecasting ability is negatively related to long-term investment strategies, indicating that stronger belief in AI’s predictive capabilities may encourage a shift toward shorter investment horizons. The findings demonstrate that different dimensions of AI perception are associated with investment behavior in different ways. While some AI-related perceptions may support more disciplined and potentially resilient investment behavior, others may encourage greater dependence on automated forecasts and reduced long-term orientation. The study contributes to understanding the behavioral implications of AI in financial decision making. Full article

Sustainable innovation constitutes the cornerstone of firms’ long-term competitive edge, yet the underlying mechanisms via which patient capital facilitates corporate sustainable innovation remain understudied. Based on a sample of Chinese A-share listed firms spanning 2013 to 2024, this study operationalizes patient capital through two proxies: relational debt and stable institutional ownership. We systematically investigate the impact of patient capital on sustainable innovation, alongside the mediating pathway of internal control quality and the moderating role of climate policy uncertainty. The empirical outcomes indicate that both forms of patient capital exert a significant positive effect on sustainable innovation, with internal control quality serving as a partial mediator in this relationship. Additionally, climate policy uncertainty reinforces the promotional influence of patient capital on sustainable innovation. We further stratify heterogeneity analyses into two dimensions: firm-inherent heterogeneity and external environmental heterogeneity. From the perspective of endogenous firm attributes, the innovation-stimulating effect of patient capital differs markedly across enterprises with distinct ownership types, life-cycle stages, and total asset sizes. Externally, the observed positive impact varies considerably conditional on industrial factor intensity and the regional marketization degree of the firm’s location. These findings expand the existing literature concerning long-term capital and sustainable innovation, and yield actionable implications for corporate management, institutional investors, and policymakers. Full article

This paper examines stock market reactions to corporate blockchain adoption announcements and explores whether the visibility of such initiatives shapes investor response. While prior research documents strong valuation effects during early phases of technological hype, evidence from more mature stages of diffusion remains limited. Accordingly, this study provides exploratory evidence on investor behavior in a later-stage adoption context. We construct a hand-collected dataset of 51 announcements by publicly traded firms across multiple industries and employ a standard event-study methodology to estimate abnormal returns over short announcement windows, using both market-model and Fama–French factor specifications. Adoption visibility is conceptualized as a multidimensional construct capturing (i) the intensity of communication surrounding the initiative and (ii) whether the application is customer-facing or internally oriented. The results indicate that average abnormal returns around announcement dates are positive but economically modest and statistically insignificant. These findings suggest that blockchain adoption announcements no longer trigger uniform market repricing effects. Instead, investors appear to respond more selectively, potentially differentiating based on the perceived informational content and strategic relevance of the initiatives. Overall, the analysis offers exploratory evidence consistent with a shift in investor response as emerging technologies move beyond hype-driven phases toward more mature stages of diffusion. The results should be interpreted with appropriate caution and motivate further research using larger samples and complementary empirical approaches. Full article

Objective: Contrary to the traditional notion of risk–return trade-off, prior studies document that financially distressed stocks tend to earn lower future returns than their healthier peers. Extending this strand of literature, this study revisits the distress risk anomaly in UK stocks and further examines whether proximity to the 52-week high and lottery-like characteristics of stocks help explain the financial distress anomaly, if any. Data and methods: In this paper, we analyse the distress risk anomaly using a sample of 4514 UK stocks over the period 2000–2021. The analysis is conducted using both the portfolio-sorting method and Fama–MacBeth cross-sectional regressions. Key findings: The empirical findings confirm the persistence of the financial distress anomaly, showing that high-distress stocks earn lower returns than their low-distress counterparts. Consistent with a mispricing explanation, this inverse distress–return relationship is more pronounced for stocks that are difficult to arbitrage and is stronger following periods of market optimism. Furthermore, the analysis reveals that both the 52-week high effect and lottery-like trading, independently and jointly, contribute to the poor performance of financially distressed stocks. This suggests that underreaction and overreaction interact to shape the observed overvaluation of distressed stocks. These findings remain robust to a battery of robustness checks. The results have several important implications for investors, researchers, and regulators. Full article

The present contribution provides a systematic review of the international scientific literature on the relationship between contaminated sites and real estate market dynamics. The objective is to investigate whether and to what extent the presence of environmental risk sources—both active or decommissioned—affects the value of surrounding residential properties. In particular, the review is focused on an examination of the methods commonly used in relevant studies to measure, interpret, and represent this impact across different geographical contexts, identifying the main magnitude ranges found in the selected contributions. Several studies consistently confirm a statistically significant negative relationship between proximity to polluting sites and real estate values, although the relevance of this effect varies considerably across case studies. Other records highlight non-notable impacts or even positive effects following remediation and redevelopment interventions. The evidence suggests that this relationship is complex and influenced by factors such as site type, contamination severity, specificities of the local urban context and community perception. Moreover, the findings underscore regional variations in the extent and nature of price impacts, reflecting diverse regulatory frameworks and remediation efforts. The outcomes of the literature review provide a robust foundation for developing more effective evaluation tools able to support decision-making processes, enabling policymakers, planners, and investors to promote sustainable urban regeneration, improve environmental justice, and reduce spatial inequalities. Ultimately, this study highlights the critical need for integrating environmental, social, and economic dimensions to fully capture the multifaceted effects of contaminated sites on property markets, thereby orienting more informed and equitable urban development strategies worldwide. Full article

Drawing on institutional theory and agency theory, this study examines whether venture capital (VC) and private equity (PE) ownership acts as a complement to, or substitute for, investor protection in shaping equity financing, debt financing, and leverage decisions in high-tech entrepreneurial firms. The analysis is based on a panel dataset of 403 high-tech entrepreneurial firms from 11 European countries over the period 2009–2013. To address potential endogeneity and reverse causality between external finance and VC/PE investment, the study employs two-stage least squares (2SLS) regression models using an instrumental-variable approach. The results provide tentative evidence that VC/PE ownership is associated with stronger debt-related financing outcomes, particularly leverage, in countries characterised by weaker investor protection, suggesting a possible substitutive relationship in debt-related financing outcomes. However, these findings should be interpreted cautiously given the limitations associated with the instrumental-variable strategy. The study contributes to the literature on entrepreneurial finance, corporate governance and law and finance by showing how firm-level governance mechanisms interact with national institutional settings in shaping financing decisions. Full article

The rapid growth of the green bond market has intensified the need for transparent and reliable monitoring systems, particularly in circular-economy environments characterized by complex, multi-stakeholder, and dynamic interactions. However, existing monitoring approaches still rely heavily on static, issuer-driven disclosures, which sustain information asymmetry and increase the risk of greenwashing. This study systematically reviews the role of digital technologies in enhancing green bond monitoring within circular economy systems. A systematic literature review (SLR) was conducted using the Scopus database, covering publications from 2022 to 2026 and yielding 56 eligible studies. A bibliometric analysis using VOSviewer identified major research trends, thematic clusters, and collaboration patterns within the field. The findings reveal four dominant technological pillars—blockchain, artificial intelligence (AI), Internet of Things (IoT), and digital twin—that support data verification, automated analytics, real-time environmental monitoring, and system-wide integration. Although these technologies show significant potential, the literature remains fragmented and lacks comprehensive monitoring architectures that integrate technological, governance, and regulatory dimensions. This study contributes to the literature by synthesizing these technologies through a business informatics perspective and highlighting digital twin architectures as a promising foundation for integrated green bond monitoring. The findings provide practical insights for regulators, issuers, and investors seeking interoperable, transparent, and trustworthy monitoring ecosystems that strengthen accountability and credibility in sustainable finance. Full article

The move to sustainable energy systems has increased the requirement for comprehensive decision support frameworks that are uncertainty-aware to guide the selection of solar power plant sites. The rapid growth of investments in solar energy has increased the demand for systematic and accurate decision-support tools to choose the best sites for photovoltaic (PV) power facilities. The selection of solar power plant sites is a complicated multi-criteria decision-making (MCDM) problem that involves technical, economic, environmental, social, and technological aspects. The process is typically associated with ambiguity and incomplete knowledge of experts. To overcome these problems, this paper offers an interval-valued neutrosophic fuzzy TOPSIS (IVN-TOPSIS) method, which extends the standard TOPSIS methodology by including truth, indeterminacy, and falsity membership degrees as interval values. The methodology is utilized in a real case study in the Mediterranean region of Türkiye, comprising three provinces with great potential: Antalya, Mersin, and Adana. An assessment of a complete set of environmental, economic, social, and technological criteria is performed using expert judgments stated in interval-valued neutrosophic language assessments. They were incorporated into a Geographic Information System (GIS) to produce a suitability map indicating the most suitable sites for the facility. The suggested approach is different from the traditional crisp or fuzzy MCDM techniques since it clearly models the degrees of truth, indeterminacy, and falsehood, thus providing a more detailed representation of the expert evaluations. According to the data, Mersin is the most ideal site for the construction of a solar power plant, followed by Antalya, and the least suitable site is Adana. The results suggest that sustainable solar energy planning must go beyond technical resource potential and include integrated and uncertainty-aware assessments. The suggested IVN-TOPSIS framework can serve as a powerful decision-support tool to policymakers, planners, and investors that wish to encourage regionally balanced and sustainable renewable energy development. Full article

This study examines the impact of ESG disclosure, leverage, and profitability on firm value, measured by Tobin’s Q, among 67 non-financial Tadawul-listed companies in Saudi Arabia over the period 2015–2024. ESG disclosure is captured through a manual content-analysis index that scores the proportion of expected environmental, social, and governance items reported by each firm. The study further investigates whether board independence moderates these relationships while controlling for liquidity, firm size, current ratio, capital expenditure, and board size. Methodologically, the study employs the two-step system generalized method of moments (system GMM) estimator, which addresses dynamic persistence, endogeneity, and unobserved heterogeneity. The findings reveal that ESG disclosure has a positive and significant effect on firm value, indicating that the Saudi market increasingly rewards firms that provide broader sustainability-related information. Profitability also exerts a positive influence on Tobin’s Q, while leverage has a negative and significant effect, suggesting that higher debt weakens market valuation. Among the moderating effects, board independence significantly reduces the negative impact of leverage on firm value, although it does not significantly strengthen the positive ESG disclosure–firm value relationship. The results also show that liquidity, firm size, capital expenditure, and board size positively influence firm value. The study’s novelty lies in being the first, to our knowledge, to integrate ESG disclosure, financial structure, profitability, and board independence within a single dynamic firm-value framework over a decade-long panel that brackets the Saudi Exchange’s 2021 ESG disclosure guideline. In doing so, it advances emerging-market ESG research by showing that, under Saudi Arabia’s largely voluntary disclosure regime and concentrated-ownership structure, board independence operates primarily as a risk-monitoring mechanism rather than as an amplifier of disclosure value. The findings imply that regulators should strengthen and progressively mandate ESG reporting frameworks, that investors should treat ESG transparency as value-relevant information, and that firms should view ESG transparency and prudent governance as strategic tools for enhancing market value in line with Vision 2030. Full article

With the global rise in sustainable investment concepts, environmental, social, and governance (ESG) factors have increasingly become important criteria influencing investment decisions. Although institutional investors are paying greater attention to corporate ESG performance, limited evidence exists regarding its impact within the Chinese A-share market. Using panel data from Chinese listed firms during the period 2010–2023, this study employs fixed-effects models with clustered standard errors as the baseline estimation method. To improve the robustness of the findings, Tobit regression, Logit regression, lagged-variable models, heterogeneity analysis, and Hausman tests are further conducted. The empirical findings indicate that the overall ESG score and the individual environmental (E), social (S), and governance (G) dimensions do not exhibit statistically significant effects on institutional ownership in the baseline fixed-effects regressions. The results suggest that ESG performance has not yet become a dominant determinant of institutional investment decisions in China’s capital market. However, the robustness tests based on Tobit and Logit models provide limited evidence that ESG performance may still influence institutional investor behavior under alternative empirical specifications. Furthermore, the heterogeneity analysis reveals that the relationship between ESG dimensions and institutional ownership differs across environmentally related and non-environmentally related firms, although the effects are generally weak and statistically limited. The study contributes to the ESG and institutional investment literature in three important ways. First, it provides updated evidence from the Chinese A-share market over the 2010–2023 period, reflecting the evolving stage of ESG development in emerging economies. Second, it comparatively examines the differentiated roles of environmental, social, and governance dimensions rather than relying solely on aggregated ESG indicators. Third, it highlights the limited and transitional nature of ESG integration among institutional investors in China, where traditional financial indicators continue to play a more important role in investment decisions. The findings provide important implications for policymakers, listed firms, and institutional investors seeking to promote sustainable finance development and improve the effectiveness of ESG disclosure practices in emerging markets. Full article

With intensifying measures related to investor and policy requirements, corporate governance and sectoral environmental performance became a focal point for sustainability disclosure, especially in energy-intensive industries with high environmental externalities. This study evaluates whether corporate environmental governance practices in key sectors correspond to their pollution intensity and economic output, analysing a panel dataset across EU member states, for the 2000–2021 period. The empirical methodology includes ordinary least squares (OLS), fixed- and random-effects models, and dynamic system generalised method of moments (GMM) panel estimation to account for sectoral heterogeneity. Results prove that sectoral value added is an influential factor of greenhouse gas emissions, with carbon dioxide exhibiting the highest elasticity to economic activity, followed by methane emissions, and nitrous oxide displaying cross-country variations due to structural and regulatory differences. While services and manufacturing sectors partially decouple via cleaner technologies, overall growth positively correlates with emissions, and renewable energy offers limited mitigation due to scale and integration challenges. Conclusions emphasise robust governance frameworks in high-value energy sectors to meet EU climate-neutrality goals, as stronger environmental accountability attracts capital and supports sustainable development, underscoring the needs for targeted decarbonisation, regulatory coordination, and accelerated technological innovation within persistent industry disparities. Full article