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.