Issue #3 (Volume 22 2025)

Free Trade Agreements (FTAs) are widely recognized as instruments for enhancing economic integration and attracting Foreign Direct Investment (FDI). This study examines the impact of FTAs, particularly next-generation agreements such as the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) and the European Union-Vietnam Free Trade Agreement (EVFTA), on FDI inflows to Vietnam. Using a Gravity Model and a panel dataset of 48 trading partners covering the period 2007–2023, this study quantifies the extent to which FTAs influence FDI attraction. The empirical results reveal that FTAs significantly contribute to increased FDI inflows. The overall effect of FTA participation is estimated at 5.64% (coefficient = 0.0549, p < 0.05), reinforcing the positive relationship between trade liberalization and investment attraction. However, the impact varies across agreements. The CPTPP has a stronger effect, increasing FDI inflows by approximately 9.47% (coefficient = 0.0905, p < 0.05), while the EVFTA does not exhibit a statistically significant impact. These findings highlight the effectiveness of next-generation FTAs in attracting investment, particularly when agreements include deeper commitments beyond tariff reductions. For Vietnam and other emerging economies, maximizing the benefits of FTAs requires complementary structural reforms, including institutional improvements, regulatory enhancements, and investment-friendly policies to sustain FDI inflows and strengthen global economic integration.

Acknowledgment
The authors gratefully acknowledge the financial support from the Banking Academy of Vietnam.

This study investigates the relationship between Environmental, Social, and Governance (ESG) performance and financial outcomes, as measured by Return on Assets (RoA), among publicly SRI-KEHATI listed firms in Indonesia. Utilizing panel data from 90 firm-year observations over six years, the analysis employs a Random Effects Model (REM) across three progressively expanded specifications. ESG performance is proxied by the Sustainalytics ESG Risk Score, with higher values indicating poorer ESG standing. The estimation reveals a consistently positive and statistically significant relationship between ESG risk and financial performance. In the baseline model, the coefficient for ESG is 0.598 with a p-value of 0.052. This effect strengthens in the second model (coefficient = 0.768, p-value = 0.010) and remains significant in the fully controlled model (coefficient = 0.724, p-value = 0.017). These results imply that firms with weaker ESG profiles may achieve higher profitability, particularly in emerging markets with lenient ESG enforcement. Sustainable Growth Rate (SGR) also strongly and positively influences RoA (coefficient = 0.740, p-value = 0.002), underscoring the role of sectoral reinvestment capacity. The findings raise critical questions regarding the alignment between ESG efforts and financial incentives in transition economies. Policymakers are urged to consider stronger regulatory frameworks to realign ESG compliance with firm-level profitability. This study contributes to the literature by providing context-specific insights into the paradox of ESG and financial success in under-regulated markets.

The foreign exchange market, characterized by high volatility and economic significance, requires accurate predictive models. This study investigates the application of the Temporal Fusion Transformer (TFT), enhanced with Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), for forecasting major foreign exchange (forex) currency pairs: USD/EUR, USD/JPY, USD/CNY, USD/AUD, and USD/INR. The proposed framework integrates a wide range of economic indicators, which include interest rate differentials, GDP growth, and trade balances, alongside investor sentiment derived from Twitter and ESG-related news sentiment. By addressing the non-linear, multiscale nature of forex time series, the CEEMDAN-TFT model facilitates improved signal decomposition and interpretability. Empirical results indicate that the model demonstrates competitive performance across all five currency pairs, with the USD/EUR pair exhibiting the highest predictive accuracy. Other pairs, exhibiting good predictive accuracy, include USD/JPY and USD/CNY, underscoring the model’s adaptability to varying economic contexts. Performance is assessed using multiple error metrics, and the model is benchmarked against standard neural network approaches (MLP, RNN, LSTM, CNN). Variable importance analysis highlights the dynamic influence of interest rates, investor sentiment, and ESG factors across different market regimes. This study provides empirical evidence that including ESG and investor sentiment can improve the accuracy of currency forecasting models. This study provides guidance and a framework for informed decision-making for traders, analysts, and policymakers.

The efficient market hypothesis is struggling to explain market behavior during rare, high-impact events. In such uncertain times, familiarity guides the decisions, allowing the brain to rely on subconscious processing for optimal outcomes. Therefore, this research aimed to examine the relationship between elevated familiarity bias and abnormal returns during rare events. Data were collected from all companies listed and active on the Indonesia Stock Exchange from 1997 to 2020. A systematic sampling method was used to establish the sample criteria, which led to a total of 5,615 observations derived from the number of trading days over 23 years across nine industries on the Indonesian Stock Exchange. The data collected were analyzed using the traditional Capital Asset Pricing Model, prospect theory and extending the Fama and French three-factor model with the addition of a psychological factor. The results show that familiarity bias behavior does not uniformly occur across all industries in Indonesia during rare events. The industries negatively impacted by these events include agriculture, consumer goods, trade services and investment, finance, basic industry, chemicals, mining, miscellaneous industries, property, real estate and building construction at values of –0.0847, –0.0946, –0.0721, -0.0405, –0.0717, –0.1258, –0.024, and –0.0805, respectively. A positive impact was only found in the infrastructure, utilities, and transportation industry at 0.0028. In conclusion, stock market behavior also affects the economy from a behavioral finance perspective.

Type of the article: Research Article

Abstract
This study examines the impact of crude oil price shocks on stock market efficiency and volatility spillovers across BRICS countries (Brazil, Russia, India, China, and South Africa) using 6,275 daily observations from April 1999 to March 2024. The results from unit root and Lo-Mackinlay variance ratio tests show that only Russia and India exhibit weak-form efficiency, while Brazil, China, and South Africa display inefficiencies, indicating scope for abnormal returns. Granger causality analysis confirms strong short-term interlinkages, with Brazil emerging as a leading market for Russia, India, and South Africa. Johansen’s cointegration test reveals long-term relationships among BRICS markets and with crude oil prices, suggesting limited diversification opportunities. ARCH-GARCH models and impulse response functions show significant volatility spillovers triggered by oil price shocks, lasting 2-6 trading days. Crude oil volatility affects all markets except South Africa, reflecting varying energy dependencies. These findings underscore the interconnectedness and systemic risk exposure of BRICS financial systems, with critical implications for international investors and policymakers in managing portfolio strategies and stabilizing markets.

Type of the article: Research Article

Abstract
Mega project, defined as infrastructure investments exceeding USD one billion, play a central role in national development but often face significant financial risks. This study explores the dynamic relationship between macroeconomic risk factors and return on investment (ROI) in mega projects using a panel data econometric approach. A balanced dataset from 2000 to 2024 was constructed, covering five economies with significant mega infrastructure investment: Turkey, China, the United States, India, and Germany. The analysis incorporates both internal project risks (cost overruns, completion delays) and external macroeconomic shocks (exchange rate volatility, inflation, interest rates). Representative infrastructure projects in transport, energy, and urban sectors were selected based on official national data and international financial databases. Pedroni cointegration tests confirmed the existence of long-term equilibrium relationships, justifying the application of a panel Generalized Method of Moments (GMM) model to address endogeneity, heterogeneity, and dynamic effects. The results indicate that a 1% increase in budget allocation leads to a 0.21% rise in ROI (p < 0.001), while cost overruns are associated with a 0.84% ROI increase per 1% overspend (p = 0.003), suggesting potential value in strategic overspending. In contrast, a 1% increase in exchange rate volatility reduces ROI by 0.69% (p < 0.001). No significant effects were found for inflation or completion delays. These findings reflect aggregated financial behavior rather than individual project cases, offering generalizable insights into mega project finance. The study contributes to the literature by constructing a risk-adjusted, multi-country econometric model and offers policy guidance for enhancing financial resilience in large-scale infrastructure investments.

Type of the article: Research Article

Abstract
This study examines the relationship between Environmental, Social, and Governance (ESG) performance and equity financing among non-financial firms listed on the Johannesburg Stock Exchange (JSE) in South Africa. Using the data from Refinitiv Eikon, Bloomberg, and company sustainability reports, the research analyzes ESG and financial performance across multiple sectors, including manufacturing, retail, and mining, with a sample of 420 firm-year observations covering 60 firms over the period from 2015 to 2023. The results from System Generalized Method of Moments (GMM) model reveal that the Debt-to-Equity Ratio has a significant positive relationship with equity financing, highlighting the persistence of capital structure in financing decisions. Environmental Score demonstrates a significant positive effect on equity financing, indicating that better environmental performance attracts more investment, though this result was not significant in the Fixed Effects Model. Social Score consistently shows a positive impact across both models, reinforcing the importance of social performance in attracting equity capital. Governance practices also exhibit a significant influence on equity financing, emphasizing the role of effective governance in improving access to equity financing when considering dynamic factors. These findings suggest that ESG performance is a critical factor in equity financing decisions, and underscore the need for financial regulators, investment institutions, and industry bodies to raise awareness about the importance of ESG considerations. The study contributes to the growing literature on sustainable finance, illustrating the strategic importance of ESG factors in shaping investor preferences and enhancing market stability.

Type of the article: Book Review

Abstract
Book “Antitrading” by Oleksii Plastun is a bold, lively, well-illustrated but still critical and science-based examination of the trading industry and financial market, challenging widespread myths about making “easy money”, technical analysis almighty, and the promises of financial heaven given by trading “gurus”. Mixing personal trading experience and academic background, Plastun describes cognitive biases, psychological traps, and misleading narratives that lead traders to financial losses in the face of severe laws of market power, probability, and financial market theories, concepts, and hypotheses.

Type of the article: Research Article

Abstract
In emerging markets such as Vietnam, where firms face rapid growth and rising operational complexity, understanding how inventory efficiency interacts with business dynamics is vital. This study aims to examine the relationship between inventory management and firm performance, with a specific focus on how this relationship is moderated by business growth and management costs. Using a balanced panel dataset of 364 manufacturing firms listed on Vietnam’s stock exchanges from 2012 to 2023, this study employs panel data regression methods, including Fixed Effects Model, Random Effects Model, Feasible Generalized Least Squares, and, notably, the System Generalized Method of Moments to address issues of endogeneity and unobserved firm-level heterogeneity. Firm performance is measured by return on assets, and inventory management is proxied by average inventory days. The results show that average inventory days are negatively associated with firm performance, indicating that longer inventory cycles reduce profitability. The interaction term between inventory days and business growth is also negative, suggesting that growth exacerbates the adverse effects of inefficient inventory practices. In contrast, the interaction between inventory days and management costs is positive, implying that effective cost control can mitigate inventory inefficiency. These findings highlight the need for Vietnamese manufacturing firms to align inventory practices with growth strategies and cost management to sustain profitability in dynamic markets.

Acknowledgment
This research was conducted as part of the doctoral dissertation project under Decision No. 5379/QĐ-ĐHDT dated December 31, 2022, issued by Duy Tan University.

Type of the article: Research Article

Abstract
To defend its stewardship role to business owners, management often employs audit firm industry specialists to validate the reporting system’s authenticity. While auditing, these specialist auditors may expend additional effort to achieve audit quality. However, the direction of the association between audit firm industry specialization, audit effort, and audit quality is unknown. Therefore, this research analyzes the nexus between audit industry specialization, audit effort, and audit quality in Nigerian banks between 2011 and 2023. Audit firm industry specialization is proxied using a binary variable, where 1 represents an audit firm with a market share above 30 percent and 0 otherwise. Audit effort is proxied by audit report lag, defined as the cumulative number of days from the fiscal year-end to the day the auditor signs off the financial statements. Finally, audit quality is proxied by using a discretionary accrual model. The study utilized the panel vector autoregression model to examine the annual data of 11 banks. The findings in the three models indicate that in the first model, prior audit effort influences the current audit effort (coef = 0.226, p <0.05), while in the second model, both previous experience of specialization (coef = 0.872, p < 0.05) and audit effort (coef = 0.362, p < 0.05) influence the current audit firm industry specialization. Finally, in the third model, audit firm industry specialization drives high audit quality (coef = 0.069, p <0.05). The study concludes that corporate management appointment of specialist audit firms can result in extended audit report lag but with a positive effect on audit quality.

Type of the article: Research Article

Abstract
Investors are very interested in companies that have high profits and stable dividend payments. Increasing investment and company profitability increase firm value. This study aims to examine the relationship between liquidity, company size, and earnings quality with firm value and dividend policy as moderators in this relationship. The secondary data used come from the 45 most liquid shares (LQ45) on the Indonesia Stock Exchange and have observations for 10 years from 2014 to 2023. The sample used is 450 data points and is tested using moderated regression analysis. The findings show that earnings quality and liquidity have significant effects on firm value. Conversely, there is no notable effect of firm size on firm value; large assets do not necessarily mean greater firm value if the assets are inefficient. Interactive effect analysis reveals that dividend policy moderates the association between liquidity and firm value, affirming its crucial role in facilitating firm valuation. Also, dividend policy affects the influence of earnings quality on firm value. However, dividend policy does not moderate the relationship between firm size and firm value. Such findings are especially valuable for investors as they indicate that liquid stocks tend to maintain stable dividend payouts, further affirming their value. Moreover, the study suggests that large assets necessarily lead to a greater valuation of a company unless paired with effective management strategies in a volatile business environment.

Type of the article: Research Article

Abstract
The service industry sector is crucial to Thailand’s employment and economic development. The firm value and sustainable growth of firms in this industry inevitably have a beneficial impact on the country. This study investigates the impact of capital structure and financial distress on sustainable growth and firm value among listed companies in Thailand’s service sector. Using unbalanced panel data from 133 firms listed on the Stock Exchange of Thailand, the analysis encompasses 1,117 firm-year observations spanning the period from 2014 to 2023. Data were sourced from the SETSMART database of the Stock Exchange of Thailand. The empirical findings indicate that capital structure, measured by debt to equity ratio, demonstrates a significant negative influence on both sustainable growth (β = –1.8600, p < 0.05) and firm value (β = –1.7600, p < 0.05), suggesting that excessive leverage undermines long-term performance, while financial distress, as captured by the Z-score, shows positive impact on both sustainable growth (β = 1.1253, p < 0.01) and firm value (β = 0.1578, p < 0.01), indicating that reduced financial distress enhances corporate outcomes. These findings underscore important managerial implications. Service firms should optimize capital structure through balanced debt-equity ratios. Proactive financial distress management is crucial for sustaining growth. This study contributes to the corporate finance literature in emerging markets by empirically validating capital structure theories in Thailand’s unique service sector context while providing practical guidance for financial decision-making.

Type of the article: Research Article

Abstract
This study investigates the effects of capital structure, corporate governance, and intangible assets on financial performance and firm value in Indonesia’s chemical industry, while examining the moderating role of firm size. Focusing on the context of an emerging economy, the research explores how internal corporate factors influence firm outcomes. The study uses a quantitative approach based on secondary data collected from the financial statements of nine chemical companies listed on the Indonesia Stock Exchange, covering 108 firm-year observations from 2012 to 2023. Capital structure, corporate governance, intangible assets, and firm size are treated as independent variables, with financial performance and firm value as dependent variables. The relationships between variables are examined using Structural Equation Modeling to capture both direct and moderating effects. The findings show that capital structure and corporate governance significantly and positively influence both financial performance and firm value, aligning with trade-off and agency theories. Intangible assets significantly affect financial performance but do not directly impact firm value. Firm size has a positive effect on financial performance and moderates the relationships between intangible assets and firm value, as well as between financial performance and firm value. However, firm size does not significantly moderate the effects of capital structure or corporate governance on firm value. These results highlight the importance of internal financial strategies and governance practices in enhancing corporate outcomes in Indonesia. The study provides practical implications for managers and policymakers to strengthen firm value through effective resource allocation, governance, and strategic planning.

Type of the article: Research Article

Abstract
Foreign institutional investors (FIIs) have traditionally dominated the Indian equity markets. However, since 2020, the landscape has significantly transformed as the registered investor base at the National Stock Exchange, India, has tripled. This phenomenon is driven by the COVID-19 pandemic and the rise of ‘influencers’ or easy access to financial knowledge. This study investigates the long-term and causative relationship between the Nifty 50 index and the net flows of domestic institutional investors (DIIs) in the Indian stock market, using daily data from April 2017 to March 2022. Employing the Augmented Dickey-Fuller (ADF) test, Johansen cointegration tests, and Granger causality analysis, the findings reveal a long-term cointegrated relationship between the Nifty 50 and DIIs’ daily flow, both before and after COVID-19. The results reveal a bidirectional Granger causality between the Nifty 50 and DIIs (p-value < 0.02) and NIFTY 50 and FIIs (p-value < 0.00) in the post-COVID era, a shift from the unidirectional pattern observed pre-COVID between NIFTY 50 and DIIs. This indicates that traders and analysts may use DII flows as a leading indicator for NIFTY 50 movements. Studying DII’s interaction with the Nifty 50 index helps assess whether their investment patterns drive market movements or are reactive to them and highlights the resilience of Indian markets to external shocks.

Type of the article: Research Article

Abstract
The growing emphasis on sustainability and continuous innovation has changed the way firms approach value creation and performance. As firms increasingly adopt ESG initiatives and invest in technological innovation, understanding how these strategies jointly affect financial outcomes across different industry contexts becomes essential. The purpose of this study is to explore the valuation implications of the interplay between ESG initiatives and technological innovation, specifically in terms of accounting, valuation, and growth metrics of corporate operations, with a focus on comparing high-technology and low-technology industries. Utilizing random effects generalized least squares (GLS) regression, this paper examines 4,000 high-technology and 4,739 low-technology firm-year observations from KOSPI and KOSDAQ listed firms in Korea from 2012 to 2022. The results show that while the influence of environmental, social, and governance factors on corporate performance, firm value, and growth show specific implications across the two industries, both ESG adoption (ROA: –0.0025; p < 0.01; TQ: –0.0298; p < 0.05; SGR: –0.0052; p < 0.05) and research and development investments (ROA: –0.0928; p < 0.01; SGR: –0.1192; p < 0.01) tend to manifest a costly impact on corporate operations. Nevertheless, when these two elements are pursued together, the negative impacts are mitigated, ultimately leading to improvements in corporate performance (ROA: 0.0453; p < 0.01; TQ: 0.8902; p < 0.01 for high-tech industries; SGR: 0.0920; p < 0.10 for low-tech industries). This study provides a comparative analysis of the impact of ESG and innovation on corporate metrics across high- and low-technology industries. The findings show that integrating ESG with technological innovation can promote sustainable corporate operations across varying levels of technological intensity.

Acknowledgment
The authors would like to express their sincere appreciation to the Korea Institute of Corporate Governance and Sustainability (KCGS) for generously providing ESG ratings data for listed firms in South Korea. Their valuable support made these analyses possible.

Type of the article: Research Article

Abstract
Sentiment analysis of financial text data plays a crucial role in investment decision-making, yet existing approaches often rely on single-model sentiment scores that may suffer from biases or hallucinations. This study aims to enhance portfolio optimization by integrating sentiment signals from multiple Large Language Models (LLMs) into the Black-Litterman framework. The proposed method aggregates sentiment scores from three finance-domain fine-tuned LLMs using a Long Short-Term Memory network, which captures non-linear relationships and temporal dependencies to produce a robust Meta-LLM sentiment score. This score is then incorporated into the Black-Litterman model as investor views to derive optimal portfolio weights. The methodology is tested on a portfolio of S&P 500 stocks. The results show that the proposed approach significantly improves portfolio performance, achieving an annualized return of 31.22%, compared to 24.57% for the market capital-weighted portfolio. Additionally, the model attains a Sharpe Ratio of 3.02, an Omega Ratio of 2.48, and a Jensen’s Alpha of 1.95%, outperforming both the benchmark portfolios and portfolios based on single-LLM sentiment. The findings demonstrate that aggregating sentiment from multiple LLMs enhances risk-adjusted returns while mitigating model-specific limitations. Future research could explore the integration of LLMs with different architectures to further refine sentiment-aware portfolio strategies.

Type of the article: Research paper

Abstract
This study aims to examine the underlying reasons why manufacturing firms in Indonesia utilize both short-term and long-term debt. Specifically, it investigates the roles of profitability, firm size, investment, asset tangibility, non-debt tax shields, and monitoring mechanisms in influencing corporate decisions regarding the use of short-term and long-term debt within their capital structure. The paper seeks to identify the most significant determinants of capital structure among Indonesian manufacturing firms. The study employs a sample of 58 manufacturing companies listed on the Indonesia Stock Exchange (IDX), covering a total of 580 firm-year observations over the period from 2011 to 2023. Structural equation modeling (SEM) using LISREL is applied as the primary analytical tool. The findings reveal that manufacturing firms investing in real sectors through fixed assets tend to rely on long-term debt financing. In contrast, those allocating capital to intangible or non-fixed assets prefer short-term debt instruments. Moreover, the study uncovers that the capital structure of Indonesian manufacturing firms is more heavily influenced by short-term debt, particularly in response to short-term working capital needs and market demand fluctuations. The study further suggests the necessity of exploring unrelated diversification as a potential indicator of managerial opportunism in the context of both short-term and long-term debt financing decisions.

Type of the article: Research Article

Abstract
The emergence of Islamic finance has positioned Sukuk as a moral substitute for traditional bonds. However, misalignment with International Financial Reporting Standard 9, especially in Jordan, erodes investor confidence and reduces integration into world markets. This paper attempts to quantitatively evaluate how classification difficulties under International Financial Reporting Standard 9 affect investment strategies, decision-making, and market attractiveness of Sukuk within Jordan’s financial system.
Data were collected from a stratified sample of 346 finance professionals from banks, investment businesses, insurance companies, and regulatory authorities. Each participant had at least three years of work experience and suitable academic credentials. Utilizing partial least squares structural equation modeling, the survey was carried out between September 2024 and January 2025. The results indicate that classification issues have a significant adverse effect, reducing investment strategy efficacy by 46% (β = –0.46, p < 0.01), decision-making clarity by 37% (β = –0.37, p < 0.05), and Sukuk attractiveness by 52% (β = –0.52, p < 0.001). These significant effects are reinforced by vigorous diagnostics of the model, with variance inflation factor measures between 1.15 and 1.23, and by superb fit indices of the model, such as a standardized root mean square residual of 0.06 and a comparative fit index of 0.95.
The results underline the need for a coordinated international classification system and the structural influence of regulatory inconsistencies on Sukuk viability. Promoting openness, restoring investor confidence, and enabling wider acceptance in foreign markets all depend on aligning Islamic financial instruments with global reporting standards.

Type of the article: Research Article

Abstract
Investor sentiment plays a crucial role in shaping firm valuation dynamics within emerging markets, where its bidirectional relationship with Tobin’s Q remains a largely uncharted territory. This is especially relevant in contexts like Vietnam, where the dominance of retail investors and the prevalence of herd behavior significantly heighten market volatility, creating unique challenges for understanding market mechanisms. This study delves into the mutual interplay between investor sentiment and Tobin’s Q among companies listed on the Vietnamese stock market, aiming to uncover the intricate connections that influence valuation processes. The study employs the Autoregressive Distributed Lag (ARDL) model, a robust econometric approach, to analyze an extensive dataset comprising 410 firms from the Ho Chi Minh City Stock Exchange (HOSE) and Hanoi Stock Exchange (HNX) over the period spanning 2015 to 2023. The findings unveil a multifaceted dynamic: in the short term, investor sentiment negatively affects Tobin’s Q, suggesting that excessive market optimism often leads to overvaluation, followed by necessary corrections. In contrast, over the long term, sentiment positively affects Tobin’s Q, indicating that sustained positive perceptions can substantially enhance firm valuation. Furthermore, Tobin’s Q demonstrates a positive short-term influence on sentiment, reflecting how improved valuations bolster investor confidence, although this influence fades in the long run. Granger causality tests reinforce the presence of a reciprocal short-term relationship between these variables. These insights underscore the critical influence of sentiment on firm valuation within Vietnam’s emerging market, providing valuable guidance for investors and policymakers to better manage and mitigate the risks associated with sentiment-driven market fluctuations.

Acknowledgments
We, Trang Tran Thi Thu, Huyen Le Thanh, and Dien Do Thi, would like to extend our deepest gratitude to our families for their unwavering support and encouragement throughout this research. Their patience and understanding have been a constant source of strength for us.
We are also immensely grateful to our colleagues for their invaluable assistance and collaboration.
Without the support of our families and colleagues, this research would not have been possible. Thank you all for your belief in us and your continuous encouragement.

Type of the article: Research Article

Abstract
The purpose of this study is to investigate how corporate specification, ownership, and macro-risk affect earnings information, with firm size functioning as a moderator in one of the world’s most dynamic economies. According to the research criteria, quantitative research is employed using secondary data with a supportive sample. The population of this study comprises the firms listed as members of the Kompas-100 index during the 2013–2023 period at IDX. This study employs panel data analysis to examine causal relationships and conduct in-depth hypothesis testing, thereby enhancing scientific credibility. The findings of this study indicate that the relationship between leverage and profitability yields two results: DAR and DER have positive and negative effects, respectively, at the 1% significance level. This finding is noteworthy because it reveals a difference in the impact of the two types of leverage. Other corporate specifications that significantly influence earnings information are the market ratio, firm size, and business prospects at the 10% level. However, tangibility and ownership do not affect substantially earnings information, which is primarily influenced by macroeconomic risk and the interaction with firm size. Further analysis reveals that, although certain corporate specifications have a short-term effect, the interaction of firm size as a moderating role confirms the impact of corporate specifications on earnings information, suggesting managerial opportunism in long-term decisions. Generally, this study demonstrates that the quality of corporate specification plays a critical role in discouraging ownership and macro-risk-manipulated management behavior on earnings information for the market.

Acknowledgment
Thanks to all the colleagues and reviewers who provided valuable input, criticism, and feedback on this article.

Type of the article: Research Article

Abstract
Investor sentiment influences financial markets beyond fundamental factors. Understanding the extent of this influence on market returns is crucial for stakeholders to make informed decisions. The study analyzed the impact of investor sentiment on the National Stock Exchange (NSE). The investor sentiment index, constructed by extracting sentiments from Times of India business news articles, is used to create the first index, the Financial Index (FinDex), using FinBERT (Financial Bidirectional Encoder Representations from Transformers). The Composite Investor Sentiment Index (CISI), which consists of FinDex and selected sentiment proxy variables, is finally constructed using Principal Component Analysis. This study has analyzed the impact of CISI on selected market indices. Results indicated that stock market returns significantly influence investor sentiment. The broad market index explains 39.12% of the variations in CISI. In the sectoral indices, the percentage of variations explained by the sectoral market index is more than 40% for auto, realty, and pharma. Investor sentiment also influences stock market returns, but comparatively, the influence is minimal. Thus, sentiment lags behind stock returns rather than driving them. Bidirectional causal relation exists in the case of the auto, public sector bank, and realty sectors (p-value < 0.10). CISI can be used by investors to refine their asset allocation strategies, ensuring better market timing and reducing exposure to irrational market swings. It can also be used as an early warning system for systematic risk in financial markets.

Type of the article: Research Article

Abstract
This study examines whether the relationship between working capital management and profitability in Vietnam’s listed transportation is nonlinear and influenced by a cash-holding threshold. Using panel data from 88 transportation firms listed on HSX, HNX, and UPCOM during the period 2014–2023, and Hansen’s (1999) threshold regression, the study identifies the threshold point and estimates the model parameters. The empirical results reveal that before reaching the identification threshold, DSO, DPO, and DSI have a noticeably negative impact on ROA (coefficients being –0.004, –0.006, and –0.017, p < 0.01), indicating that lengthening collection, payment, or inventory periods harms profitability under lower liquidity conditions. However, once the identified threshold is exceeded, the effects of DSO, DPO, CCC, and OCC are reversed, suggesting that with sufficient liquidity, more lenient working capital policies can actually support profitability. Meanwhile, control variables such as LEV and CASH demonstrate a substantially positive influence on ROA (LEV: 0.016–0.022; CASH: 0.0904–0.1512, p < 0.01), affirming that prudent debt use and ample liquidity buffers enhance performance, whereas SZ negatively affects ROA (–0.0176 to –0.0219, p < 0.01). The study proposes some practical recommendations for working capital management to enhance the profitability of transportation firms.

Type of the article: Research Article

Abstract
This study examines the effect of contractual, asset pricing, and opportunistic motivations on choosing a fair value or cost model for investment properties, as well as how institutional ownership moderates the influence of these three motivations. This study was conducted on 100 companies with investment property accounts in ten sectors listed on the Indonesia Stock Exchange from 2018 to 2022, including 500 firm-year data observations. The study used logistic regression and moderated regression analysis to test the hypotheses. The results indicate that the three motivations explain the choice between fair value and cost models. However, institutional ownership plays an important moderating role. Contractual motivation and firm size as a proxy are positively related to fair value choice, contradicting political costs, as fair value can enhance asset value, potentially increasing opportunities for third-party financing. Asset pricing incentives and the ratio of market to book value as proxies for information asymmetries do not affect the choice because Indonesia is a developing country where investors tend to exhibit herding bias, meaning their information sources rely on issues rather than financial reports. As for opportunistic motivation, the gain arising from changes in the fair value of investment property for the bonus plan proxy is positively related to the fair value choice. In addition, institutional ownership can strengthen the influence of contractual and opportunistic motivations and weaken the influence of asset pricing motivation on selecting a fair value model.

Type of the article: Research Article

Abstract
Amid China’s accelerating financial development and heightened concerns over corporate debt, default risk has emerged as a central challenge for financial stability. This study investigates whether the educational attainment of board directors significantly reduces corporate default risk in the context of China’s listed firms. Using a panel dataset of 4,751 firms spanning 2003–2023, default risk is measured through Merton Distance to Default and the Z-Score, a widely used metric of financial distress constructed as a weighted linear combination of five financial ratios. Fixed-effects regression results show that higher educational attainment among board members significantly lowers default risk. A one-standard-deviation increase in board education leads to a 0.344-point increase in Z-Score, approximately 7% of its standard deviation. Notably, the mitigating effect of board education is more evident in non-state-owned enterprises, where weaker governmental support makes governance quality especially vital. The effect is also stronger in small firms, where limited internal controls heighten reliance on board oversight. Furthermore, in firms with weak institutional monitoring, better-educated boards appear more capable of navigating market pressures and reducing financial vulnerability. To address potential endogeneity, lagged variable analyses are conducted, which suggest that earlier levels of board education predict lower future default risk. Two-stage least squares regressions, using the industry-median board education as an instrument, further support the causal interpretation of the relationship. These findings underscore the strategic importance of board education in mitigating financial distress, strengthening risk management, and fostering sustainable corporate development in China’s evolving market environment.

Acknowledgment
This research was funded by the Wenzhou Association for Science and Technology—Service and Technology Innovation Program [jczc0254], the General Program of the Zhejiang Provincial Department of Education [Y202353438], the Wenzhou-Kean University International Collaborative Research Program [ICRP2023002], and the Wenzhou-Kean University Student Partnering with Faculty Research Program [WKUSPF202411].

Type of the article: Research paper

Abstract
The Public Investment Fund (PIF), Saudi Arabia, founded in 1971, at the forefront of reshaping Saudi Arabia’s economic flow through its Vision 2030, diversification from crude oil revenues and towards more sustainable growth. The study attempts to quantify the impact of PIF on the financial performance of the country, looking into key economic indicators such as GDP growth, foreign direct investment (FDI), and stock market stability. The study adopts a mixed-methods approach and uses data from 2018 to 2023. The dataset comprises annual economic reports from the Saudi Central Bank, General Authority for Statistics, investment data from the Public Investment Fund’s, and financial market data from Tadawul Stock Exchange. Analysis reveals a statistically significant positive correlation (R = 0.46, p < 0.05) between increases in PIF’s Assets under Management (AUM) and national GDP growth, suggesting that strategic public investments strongly contribute to macroeconomic expansion. Strategic PIF investments resulted in a notable 45% rise in FDI specifically into the non-oil sector, alongside a 30% increase in domestic job creation between 2018 and 2023. Additionally, stock market stability significantly improved during the study period, as evidenced by reduced volatility and a sustained upward trend in the Tadawul All Share Index (TASI), reflecting strengthened investor confidence driven by PIF initiatives. These findings underscore the strategic role of PIF in catalyzing Saudi Arabia’s transition toward a diversified and sustainable economy, supporting green energy initiatives, population-driven economic growth, and substantial progress in national mega-projects.

Type of the article: Research Article

Abstract
In emerging markets, understanding the dynamics of share price volatility is essential for corporate financial management and investor decision-making. The industrial sector often experiences price movements that may be influenced by companies’ financial policies. This research investigates the impact of dividend policy on share price volatility, with a focus on the moderating role of the debt ratio. The research draws on a balanced panel dataset of 64 Jordanian industrial firms listed on the Amman Stock Exchange during the period 2015–2023.
Using panel regression models, the findings reveal a statistically significant negative association between both dividend yield and payout ratio with share price volatility. Specifically, a 1% increase in dividend yield is associated with a 0.42% reduction in volatility (p < 0.01), while a 1-point increase in the payout ratio reduces volatility by approximately 0.31% (p < 0.05). In addition, the debt ratio significantly moderates these relationships, which reduces the stabilizing impact of dividends in highly leveraged firms. The high interaction term between dividend yield and debt ratio was confirmed by the positive interaction term between dividend yield and debt ratio. These findings highlight the importance of balanced dividend and leverage strategies in reducing stock market risk, which may improve market stability.

Acknowledgment(s)
This research was funded through the annual funding track by the Deanship of Scientific Research, from the vice presidency for graduate studies and scientific research, King Faisal University, Saudi Arabia [Grant No. KFU253003].

Type of the article: Research Article

Abstract
This study examines whether the value relevance of accounting information has changed in the post-pandemic “New Normal” era, in light of evolving business models and greater reliance on intangible assets. The study analyzes firms listed on the Korean Stock Exchange from 2013 to 2023, defining the period from 2020 to 2023 as the New Normal period. A total of 5,007 firm-year observations from the post-2020 period are used to assess whether traditional financial metrics remain effective in capturing firm value under the new economic conditions. Following Ohlson (1995), a firm’s value is estimated using a linear combination of book value (BPS) and earnings (EPS). Additionally, 1,688 firm-year observations from the information technology (IT) sector are separately examined, given the sector’s strong adaptability and emphasis on digital innovation. The empirical analysis reveals that the explanatory power of the Ohlson model declined from 0.501 to 0.382 in the post-COVID period. Furthermore, the coefficients of both EPS and BPS decreased significantly after the pandemic (coef = –3.574, t-value= –11.29; coef = –0.244, t-value= –9.84). This trend is particularly pronounced in the IT sector (coef = –4.654, t-value= –4.54; coef = –1.103, t-value= –8.45). This indicates that the value relevance of earnings and book value decreased during the New Normal era. These findings highlight the limitations of traditional reporting frameworks and the growing importance of incorporating nonfinancial information into corporate disclosures.

Type of the article: Research Article

Abstract
This study investigates the asymmetric short- and long-run effects of gold prices, crude oil prices, and the USD/INR exchange rate on India’s Nifty 50 index. Drawing on daily data from 2022 through 2024, it employs the Nonlinear Autoregressive Distributed Lag (NARDL) model to uncover both long-term equilibrium relationships and short-term nonlinear dynamics among these key economic variables. Unit root tests reveal mixed orders of integration, reinforcing the suitability of the NARDL framework for this analysis. The long-run estimates indicate that only negative gold price shocks exert a statistically significant effect on the Nifty 50, while positive shocks appear inert. In contrast, the short-run results highlight that both USD/INR appreciations and depreciations adversely affect the index, underlining the stock market’s heightened sensitivity to exchange rate volatility. Intriguingly, short-term declines in gold prices are associated with positive responses in equity markets, potentially reflecting hedging behavior or shifts in investor sentiment. Meanwhile, crude oil price fluctuations exert no statistically meaningful impact in either the short or long term. Diagnostic checks confirm a stable long-run cointegrating relationship among the studied variables. These findings offer robust, empirically grounded insights for investors and policymakers, particularly in crafting risk mitigation strategies and informed decision-making during periods of geopolitical turbulence and economic uncertainty.

Type of the article: Research Article

Abstract
The inability of monetary policy to maintain price stability under the flexible exchange rate system, with the high volatility of the Naira/Dollar exchange rate in Nigeria, motivates this study. This study, therefore, investigates monetary policy effectiveness on price stability when an external shock threatens the system. With the standard deviation of the Naira/Dollar exchange rate as a proxy for external shock, results from the nonlinear autoregressive distributed lag (NARDL) using quarterly data from 1980Q1 to 2024Q1 reveal that monetary policy effectiveness is weakened by external shock. Specifically, monetary expansion is less inflationary in the short run than in the long run, whereas its contraction dampens productivity with no significant impact on inflation in a closed economy with no shocks. However, in the presence of external shocks, monetary contraction and expansion produced an overly ambiguous and inconsistent impact on inflation in both periods. This implies that besides the structural imperfections from external shocks, it weakens the policy response of monetary policy on price stability. With inflation persistence at 77.7%, while the adjustment speed to steady state equilibrium stood at 7.7% per quarter, it implies that the system will be divergently unstable in the long run. The study concludes that monetary policy effectiveness is weakened by external shocks; therefore, fiscal-monetary policies on price stability, a managed-float exchange rate system, and inflation targeting were recommended.

Type of the article: Research Article

Abstract
A high-frequency enough dataset may be able to identify very short-term opportunities that can potentially generate significant profits. The present study aims to test the performance of momentum and contrarian trading strategies in a high-frequency setting. To this end, tick-by-tick data from Refinitiv (TRTH) are employed, and 288 strategies are tested across a sample of 28 highly liquid U.S. blue chip stocks during the period 2020–2021, a timeframe marked by significant market volatility, notably the COVID-19-induced crash of February–March 2020 and the subsequent recovery phase from April 2020 to December 2021. The analysis reveals that, although certain strategies exhibit superior performance relative to the benchmark strategy both prior to and following adjustments for risk, data snooping, and luck, none outperform the benchmark strategy once reasonable transaction costs are accounted for. These findings suggest that sophisticated retail traders may be unable to exploit underreaction or overreaction in stock prices at high frequency. The main contribution of this study lies in the application of stringent robustness checks, including a robustness check based on luck within the context of intraday trading strategies.

Type of the article: Research Article

Abstract
In today’s dynamic financial environment, understanding the psychological and cognitive factors that shape saving behavior is important for strengthening financial stability and well-being. This study examines the influence of financial knowledge and financial attitude on the saving behavior of working women in Haryana (India). Furthermore, the study also examines the mediating role of the internal locus of control in these relationships. A primary survey is conducted between December 2023 and April 2025, using a self-administered questionnaire. Data are collected from 225 working women through a non-probability sampling method and analyzed using Smart PLS version 4.0. The findings indicate that financial knowledge and financial attitude significantly and positively affect internal locus of control and saving behavior, respectively. Working women with a positive financial mindset and greater financial understanding believe in their ability to manage financial outcomes and engage in consistent saving practices. Internal locus of control also positively influences saving behavior and serves as a significant mediator in the relationships between financial knowledge and saving behavior, and between financial attitude and saving behavior. Notably, the mediation of the internal locus of control between financial attitude and saving behavior shows a stronger influence than its mediation between financial knowledge and saving behavior.

Type of the article: Research Article

Abstract
Financial technology has become a top priority and a vital avenue for banking institutions seeking financial development and enhanced services. Financial technology is using a new digital transformation in the financial services industry. The study aims to investigate the dynamic effect of financial technology tools on financial development, examining both the long-run and short-run perspectives. The study used an ex-post facto research design because the data already existed and were retrieved from the Central Bank of Nigeria’s statistical bulletin. The Autoregressive Distributed Lag (ARDL) model was employed to examine the impact of financial technology policy tools and financial development from the first quarter to the fourth quarter of 2013–2023. The long-run results revealed that financial technology positively impacted financial development, where a 1% increase in financial technology led to a 20.33% (p-value = 0.4123) increase in financial development, though statistically insignificant. In the short run, financial technology positively impacted financial development, where a 1% increase in financial technology led to a 6.57% (p-value = 0.0053) increase in financial development. The results showed a statistically significant relationship between biometric authentication devices, point of sale, web-based transactions, and mobile banking on money supply to gross domestic product in the short run, suggesting that financial technology drives financial development, enhancing access to financial services, and improving efficiency. Banks should continuously strengthen the adoption of financial technology tools that would promote banks’ efficiency.

Type of the article: Research Article

Abstract
This paper examines the potential impact of financial technology (Fintech)on the financial inclusion of women working in the informal sector in Morocco, a population largely excluded from formal financial systems despite the rapid expansion of digital financial services.
The study aims to identify the key factors that influence the adoption of Fintech solutions among these women, using the Technology Acceptance Model (TAM) as the theoretical framework. Specific variables analyzed include perceived usefulness, ease of use, cost reduction, transaction security, and language accessibility.
The study is based on primary data collected through a structured survey conducted between March and May 2024. The sample consists of 315 Moroccan women engaged in informal sectors, including local trade, handicrafts, and agriculture. The women come from both rural and urban areas. An ordered Probit model is employed to test eight hypotheses concerning the adoption of Fintech.
Results show that simple user interfaces, lower costs, and perceived security significantly increase the likelihood of Fintech adoption. Conversely, variables such as greater access to financial services or awareness-raising initiatives have a limited impact. Control variables such as level of education and social influence also reveal significant effects, while access to digital infrastructure shows a more moderate influence. The results underline that Fintech can contribute to the financial inclusion of women in the informal sector, provided that solutions are simple, affordable, and culturally appropriate. The study recommends the development of Fintech tools adapted to the sociocultural and technological contexts of this vulnerable group.

Type of the article: Research Article

Abstract
In developing economies, financial institutions are positioned as a catalyst for economic innovation, yet there is little empirical research linking digital transformation to an enhanced management control function within these institutions. This paper investigates the relationship between digital transformation and the management control function in financial institutions, based on a study conducted in Moroccan financial institutions.
A quantitative survey, conducted in 2025, focused on 149 controllers from about 90 Moroccan financial institutions. Clearly, the sample size was limited, and the representation was justified. Five hypotheses were tested in a regression analysis. The findings confirmed a positive relationship between the management controller effectiveness and the use of digital levers. Evidence indicated that automation had the most influence, followed by the implementation of Business Intelligence and Big Data, followed by Cyber Security, followed by Cloud-enabled mobile. Data visualization also had a weaker but significant impact. These findings were consistent with previous literature regarding the Moroccan context. It was encouraging finding that the use of digital levers in management control provided operational efficiencies, as well as assisting controllers in the strategic advisory aspects. However, we caution against overgeneralizing based on the limited sample size. It is recommended that further research be conducted in more diverse types of institutions and that this validation work be expanded by using future digital integrations such as artificial intelligence and predictive analytics.

Type of the article: Research Article

Abstract
In an attempt to examine the relevance of behavioral finance in the capital market of Bangladesh, this study intends to investigate which cognitive biases and behavioral errors lead to the psychological biases ultimately affecting the rationality of individual investors’ choice of investment pattern on the Dhaka Stock Exchange. A structured survey questionnaire is used, identifying 32 factors grouped into seven separate quantitative variables – accounting, technical, diversification, herding, heuristics, market, and personality – to evaluate against one dependent variable: the demand for common stock. The database has been developed for a one-year tenure from January 2024 to January 2025. The paper applies multiple Regression Analysis and Chi-Square tests on 424 active investor responses after confirming the reliability and validity of the variables. The findings reveal that, except for diversification, five independent variables – market, accounting, technical, herding, and heuristics – appear significant at the 1% significance level, while personality significantly affects the rationality of investment behavior at the 5% significance level. This confirms the existence of psychological and cognitive biases that disrupt the individual investment patterns of investors at the Dhaka Stock Exchange. Consequently, this study recommends that more awareness and financial literacy should be introduced by formal training and counselling sessions in exchange for the better restoration of confidence and literacy of investors in their respective belongingness to the financial market.