Search Results (519)

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

The study investigates the state-dependent dynamics of overconfidence in the Bangladesh equity market by exploring the relationship between market returns and trading volume within a nonlinear information-theoretic framework. Building up on the traditional return–volume literature, the study differentiates between total market returns and unexpected returns, with the latter representing unexpected information shocks obtained using the Market Index Model. Transfer Entropy with bootstrap inference estimates the directional and asymmetric information flows across five different market states, namely: bullish, bearish, crisis, extended crisis, and COVID-19. The evidence suggests that the overconfidence biases in aggregate market returns are small and intermittent and are reflected in poor and unstable information flow between market returns and trading volume. In comparison, unexpected market returns have a directionally significant impact on trading behavior, which supports the behavior of state-dependent overconfidence. The findings also reveal that overconfidence is higher in normal and bullish market situations but drops significantly in crisis-based situations. The asymmetric analysis indicates increased trading responses to negative returns shocks, as it is more evident that investors are more sensitive to losses and recovery expectations. The research adds to behavioral finance literature on frontier markets through an unexpected return decomposition with nonlinear causality model. The results have serious implications on market surveillance, assessment of investor behavior and design of regulatory policies. Full article

Purpose: This study investigates the multi-dimensional nature of corporate risk-taking by examining how governance mechanisms exert differing pressures on accounting-based stability versus market-perceived volatility in the Saudi context, as the biggest emerging market in the Middle East. Moreover, the research uses accounting conservatism as a critical moderating variable and the sample is partitioned into high-conservative and low-conservative groups. Design/methodology/approach: The research analyzed data from 69 non-financial listed firms from 2017 to 2024 using four statistical models. Corporate risk-taking values have been captured from both accounting-based and market-based perspectives. Moreover, managerial, institutional, and concentration ownership have been used to capture ownership structure. However, board size, independence, and CEO power have been used to capture board structure. Findings: The research findings reported three main results: (1) Ownership structures have an asymmetric impact on accounting-based corporate risk-taking, as managerial and institutional ownership take a U-shaped curve, but ownership concentration has a positive impact. Moreover, from market-based corporate risk-taking, managerial and institutional ownership have a negative impact, but ownership concentration has a positive impact. (2) Board structures have an asymmetric impact on accounting-based corporate risk-taking, as managerial and institutional ownership have a negative impact, but ownership concentration has an inverted U-shaped impact. Moreover, from market-based corporate risk-taking, managerial and institutional ownership have no significant impact, but ownership concentration has a negative impact. (3) Accounting conservatism can change the nexus between ownership structure, board structure, and corporate risk behavior. Research limitations/implications: The research has many implications. For policymakers, the results discovered the role of ownership and board structures in shaping corporate risk-taking behavior in the Saudi context. Moreover, we have provided evidence-based guidance for governance reforms and firm-level decision-making. Moreover, the results can be incorporated by investors and creditors into their risk assessment frameworks, improving portfolio allocation and credit evaluation. Originality/value: The research captured corporate risk-taking behavior in the Saudi context from two perspectives at the same time. Likewise, it provides new empirical evidence that accounting conservatism can have a role in risky behavior. Full article

From the perspective of interactions between energy firm behavior and government intervention strategies, this study develops a contagion control model for energy firm debt default risk utilizing cellular automata and complex network theory. This research investigates the spatio-temporal evolution of risk transmission and evaluates the efficacy of various mitigation protocols through computational simulation. The research results indicate that: (1) An escalation in both the transmission likelihood and the rate of immunity decay significantly amplifies the propagation strength of debt default risks. Conversely, the stability of the energy firm network is bolstered as the probabilities of immunity and recovery increase. (2) The contagion intensity for debt default risk is positively correlated with market noise, the risk appetite of energy firms, and their corporate influence. It is negatively correlated with risk awareness, creditworthiness, regulatory intensity, and policy subsidies. Furthermore, it exhibits an inverted U-shaped relationship with investor sentiment. (3) Within the interconnected network of energy firms, risk contagion can be effectively mitigated not only by enhancing risk perception and credit standing but also by guiding risk preference and managing firm influence. Furthermore, the integration and adjustment of government intervention strategies, such as regulatory intensity and policy subsidies, can more efficiently accelerate the eradication of debt default risk among energy firms. Full article

This study examines how green bond financing costs in China are jointly shaped by market pricing mechanisms and institutional investor behavior. It develops an integrated two-level framework linking issuance-level bond characteristics with investor decision-making to explain green bond pricing in an emerging market. Using a comprehensive dataset of Chinese green bond issuances, the results show that financing costs are driven mainly by conventional credit-related signals, including issuer and bond ratings, guarantee structures, issuance size, and maturity. However, market frictions such as liquidity constraints and rating inertia weaken the capitalization of environmental attributes in yields. A survey-based Logit analysis of institutional investors in Shanghai further shows that green bond investment is influenced more by trading activity, information transparency, and risk management than by environmental awareness alone. Institutional heterogeneity also suggests that securities firms display stronger participation than investment companies, reflecting differences in bond-market exposure, product familiarity, and institutional investment mandates. Overall, the findings reveal a feedback mechanism in which market signals shape investor behavior, which in turn reinforces or moderates pricing dynamics. The study clarifies the structural and behavioral drivers of green bond pricing and offers policy implications for improving transparency, liquidity, and investor incentives. Full article

The Behavioral Finance (BF) has undergone significant developments due to the transformative influence of Environmental, Social and Governance (ESG) practices. BF and Sustainable Investment (SI) are closely intertwined domains, both of which bring into line with the broader framework of ESG. Integrating BF into the field of SI expands the understanding of how psychological biases, emotional factors, and cognitive constraints influence investors decisions connected to sustainability focused assets. Despite their growing relevance, the existing literature lacks a comprehensive review that provides holistic reviewing of research integrating into these areas. To address this gap, we provide an overview of BF and SI research in Socially Responsible Investments (SRI). Using both co-citation and bibliometric-coupling analysis, we infer the thematic structure of key words of BF and SI for a period of 20 years starting from 2004 to September 2025. Additionally using performance analysis and co-occurrence analysis, we highlighted trends and research directions regarding BF and SI. Further, seven thematic clusters and coupling networks were also identified which are offering to the researchers a structured foundation to explore emerging trends and consolidate knowledge within the BF and SI field. This Bibliometric study aids in recognizing the emerging topics for research in the domain of BF and SI. Full article

Behavioral finance challenges classical rational-investor models by demonstrating that psychological biases shape financial decisions. Evidence indicates that overconfidence, herding, loss aversion, and the disposition effect are not uniformly distributed but are shaped by gender, age, financial literacy, income, and investment experience. However, the literature remains fragmented across contexts and geographies. This PRISMA 2020 systematic review synthesizes 57 empirical studies (2010–2025) screened from 172 Scopus records and appraised against eight quality criteria. Findings confirm overconfidence (31 studies) and herding (26) as the most prevalent biases, concentrated among younger, male, and less experienced investors, whereas loss and risk aversion are more common among female, older, and financially insecure investors. Financial literacy emerges as the strongest moderator, reducing most biases while paradoxically amplifying overconfidence at moderate levels, consistent with the Dunning–Kruger effect. Formal moderation analyses (14 studies) support literacy as a significant boundary condition, and investment experience exhibits a non-linear pattern favoring moderate levels. This review contributes a structured, quality-appraised synthesis and a research agenda addressing intersectionality, longitudinal designs, and geographic diversity. Full article

This study provides an empirical investigation into the impact of corporate sustainability practices on financial performance in Boursa Kuwait over the period 2015 to 2025. While existing literature has largely focused on firm-level analyses of ESG practices, limited attention has been given to their aggregated effect on market-level outcomes, particularly in emerging markets such as Kuwait. Moving beyond these gaps, the research conceptualizes sustainability as a potential systemic determinant of market behavior, examining its influence on the All Share, Main Market, and Premier Market indices. The study evaluates how variations in environmental performance, governance quality, and transparency of sustainability disclosures are transmitted into various market outcomes, including index returns, volatility, and market capitalization. Employing a combination of regression analysis and time-series modeling, the framework captures both short-term fluctuations and long-term structural dynamics, enabling a nuanced understanding of the complex interplay between ESG practices and market performance. Anticipated findings suggest that improvements in governance mechanisms and sustainability disclosure standards are likely to stabilize market dynamics, mitigate volatility, and support consistent index performance in the longer term, while short term expectations are more difficult to speculate upon. Additionally, the adoption of ESG practices is hypothesized exert positive influence on investor confidence and market participation, as it’s considered to reflect a gradual alignment of Kuwait’s capital market with global sustainability norms. Full article

Rapid digitalization has reshaped financial decision-making, and anxiety about later life is an important concern among middle-aged and older investors. Yet it remains unclear whether the traditional Big Three financial knowledge component captures the aspects of financial capability most closely associated with lower anxiety in digital financial environments. This study examines the association between old-age anxiety and digital financial literacy (DFL) components among digitally active Japanese retail investors aged 40–64. Using data from a large-scale survey of 94,695 investors, we estimate ordered probit models to examine overall DFL and its eight subdimensions. While overall DFL is negatively associated with anxiety about life after age 65, decomposing the index reveals substantial heterogeneity across components. The traditional Big Three financial knowledge component does not show a robust independent negative association with old-age anxiety once actionable and protective digital competencies are accounted for. In contrast, practical know-how, positive financial attitude, and self-protection are more consistently associated with lower anxiety. Supplementary heterogeneity analyses suggest that the positive conditional association between financial knowledge and anxiety is most visible among men aged 50–59, although these subgroup patterns should be interpreted cautiously. These findings do not imply that financial knowledge is unimportant. Rather, they suggest that Big Three financial knowledge alone may be an insufficient proxy for the dimensions of financial capability associated with lower self-reported old-age anxiety in digital financial environments. Given the cross-sectional design, the findings are interpreted as conditional associations rather than causal effects. Full article

Inflation expectations play an important role in monetary transmission, yet little is known about whether digital financial literacy (DFL) is associated with how individuals form such expectations across different forecasting horizons. This study examines the association between DFL and inflation expectations at the one-, three-, and five-year horizons using a large-scale online survey of more than 150,000 Japanese investors. DFL is measured as a multidimensional construct capturing digital and financial knowledge, awareness and use of digital financial services, financial attitudes and behaviors, and self-protection capabilities. Ordered probit models are employed to estimate the association between DFL and horizon-specific inflation expectations while controlling for demographic, socioeconomic, and behavioral characteristics. The results indicate a clear horizon-dependent pattern. Higher DFL is negatively associated with one-year-ahead inflation expectations but positively associated with inflation expectations at the three- and five-year horizons. Marginal-effects estimates indicate that higher DFL shifts the short-run distribution toward lower inflation categories, but shifts the medium- and long-run distributions toward higher inflation categories. These findings are consistent with the possibility that individuals with higher DFL process short-term and longer-term inflation-related information differently. However, because the analysis is based on cross-sectional observational data, the results should be interpreted as conditional associations rather than causal effects. Full article

Research Purpose: This study investigates the role of digital investor behavior, measured through Google Trends, alongside technical indicators such as RSI and Bollinger Bands, in forecasting volatility in the Dubai Financial Market. The aim is to develop a hybrid analytical framework that integrates behavioral and technical dimensions to enhance predictive accuracy in emerging markets. Study Methodology: Daily data from 2020 to 2025 were collected, covering both crisis and post-crisis periods. Digital attention was quantified using Google Trends search indices, while technical indicators included RSI and Bollinger Bands calculated over a 7-day horizon. Volatility was modeled using ARCH, GARCH, and EGARCH frameworks, with Max Drawdown employed as a complementary risk metric to capture extreme market movements. Findings: Digital investor attention shows a predictive association with volatility, particularly when combined with technical indicators. Models incorporating both behavioral and technical variables demonstrated superior predictive performance. The EGARCH model successfully captured the asymmetric impact of negative shocks (γ < 0, p < 0.05), while Max Drawdown provided additional insights into risk exposure during periods of heightened market stress, achieving an R² of 95.36%. Scientific value: This study positions digital attention as a complementary variable that improves forecasting, moving beyond conventional price-based models in volatility modeling; by integrating Google Trends with technical analysis, the research introduces a hybrid forecasting framework that can be adapted to other emerging markets. Practical Implications: The findings offer practical value for policymakers and investors. Regulators can use digital attention measures as early warning signals to anticipate volatility, while investors can integrate behavioral and technical indicators to improve risk management and trading strategies. From a foresight perspective, the study contributes to building more resilient financial systems by embedding behavioral data into predictive tools. Full article

Sustainable (ESG) investments have gained significant interest, prompting renewed attention to retail investors’ decision-making processes. ESG investing is motivated by both financial concerns and psychological factors. However, despite growing interest, the motivational underpinnings of sustainable asset allocation remain underexplored. This study bridges economic psychology and sustainable finance to examine drivers of ESG investment intentions and choices in the Italian market. Drawing on the Theory of Planned Behavior, it explores how attitudes, subjective norms, perceived behavioral control, and trust shape ESG investing intentions and choices. Results show that each factor significantly influences investing intentions when considered independently. In particular, the affective dimension of attitudes emerges as especially relevant. These findings challenge traditional views of financial rationality in ESG contexts, suggesting that the motivations of sustainability-oriented investors may differ meaningfully from those of traditional investors. Practical implications are that ESG communication should appeal to emotional and ethical dimensions of decisions, while educational initiatives should enhance investors’ ability to critically assess ESG-related information. Full article

Financial reporting standards aim to increase transparency; however, the expansion in disclosure volume may also create an information overload paradox for investors, an issue that remains underexplored in the context of institutional investors. Excess information beyond mandatory requirements may complicate decision environments and create cognitive burden. When information exceeds cognitive processing capacities, attention may become fragmented, making it more difficult to distinguish signal from noise and potentially leading to analysis paralysis and changes in risk perception. Drawing on bounded rationality and cognitive load theory, this study conceptualizes information overload as a behavioral constraint associated with perceived limitations in decision quality and speed and, accordingly, examines its influence on institutional investors’ decision processes through a phenomenological approach. The study employs thematic analysis based on in-depth interviews with 19 professionals in institutional investment organizations in Türkiye. The findings suggest that information overload is experienced as cognitive strain that may prolong decision processes, may be associated with analysis paralysis and perceived changes in decision quality, and may be associated with increased uncertainty and potential challenges in interpreting risk. These findings provide exploratory insight into how information density may influence risk interpretation and portfolio assessment, and how institutional investors perceive decision-making efficiency. Full article

The rapid development of the fintech sector has facilitated the emergence of digital multi-level marketing (MLM) schemes, raising concerns about investor protection. Despite extensive literature on MLM schemes and pyramid schemes, there remains a significant research gap regarding the psychological mechanisms and cognitive biases that drive investor participation behavior. This study investigates factors influencing Vietnamese female investors’ intention to participate in fintech MLM schemes, using Pi Network as a case study. Grounded in behavioral finance theories (Prospect Theory and Social Comparison Theory), the model empirically examines the impacts of herding bias and overconfidence bias, explaining participation intention through the mediating effect of the fear of missing out (FOMO) and perceived risk. A quantitative approach was employed using PLS-SEM analysis, with data collected from 264 female investors in Ho Chi Minh City. The results reveal that herding behavior and overconfidence significantly shape investors’ FOMO and perceived risk, with these biases significantly increasing FOMO and decreasing perceived risk. More importantly, these biases, mediated by FOMO and perceived risk, significantly shape participation intention in fintech MLM schemes. This study contributes empirical evidence showing the interaction between high social connectivity and cognitive-bias-driven vulnerabilities in a rapidly expanding and unregulated digital market such as Vietnam. This study has practical implications for policymakers and financial educators in protecting investors from financial schemes by monitoring social media to debunk “safety in numbers” narratives and prioritize the awareness of biases in financial education to mitigate impulse investments. Full article

Financial reporting integrity (FRI) plays a critical role in capital market efficiency, yet its determinants remain difficult to model due to nonlinear relationships, heterogeneous firm characteristics, and institutional differences across emerging markets. Prior research largely relies on linear econometric approaches, which may overlook threshold effects and complex governance dynamics. This study develops an explainable Optuna-optimized Extremely randomized trees (ET) ensemble framework to examine the association between controlling shareholders and FRI in Egypt and Saudi Arabia. Using a panel dataset of 1746 firm-year observations over the period 2014–2022, the model incorporates advanced preprocessing and mutual information-based feature selection to enhance predictive accuracy and robustness. The proposed model significantly outperforms regularized linear models, standalone machine learning models, and alternative ensemble techniques, achieving R² values of 0.7935 in Egypt and 0.9231 in Saudi Arabia, alongside substantial reductions in RMSE and MAE. Diebold–Mariano tests confirm that these performance gains are statistically significant (p < 0.01). Explainability analysis using SHAP reveals that firm size and market share are the dominant drivers of FRI, while blockholder ownership exhibits a nonlinear and context-dependent association. Partial dependence results show a complex, non-monotonic relationship in Egypt—consistent with a monitoring–entrenchment trade-off—contrasted with a predominantly positive and monotonic association in Saudi Arabia. Importantly, these nonlinear patterns are not detected in conventional panel fixed effects models, highlighting the limitations of standard econometric specifications in capturing complex ownership dynamics. The findings highlight the importance of institutional context in shaping governance outcomes and demonstrate how explainable ensemble learning can uncover hidden nonlinearities in financial reporting behavior. This study contributes by identifying nonlinear thresholds and cross-country variation in ownership effects while integrating predictive performance with interpretability, offering a robust framework for analyzing corporate governance mechanisms in emerging markets and supporting more informed decision-making by investors, regulators, and policymakers. Full article