Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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Item Government intervention and stock price returns during covid-19 pandemic: evidence from an emerging market(Taylor and Francis Group, 2024-07-10) Le TDQ; Nguyen DT; Ho TH; Ngo TAs the impact of the COVID-19 pandemic on the stock market returns has received much attention from researchers and practitioners, the evidence on the government invention on stock market returns in frontier markets in the Asia-Pacific is very scanty. This study first revisits the relationship between COVID-19 and stock market returns using large data from 23/01/2020 to 28/05/2021. Second, this study examines how the Vietnamese stock market reacts to government actions during the COVID-19 outbreaks. Using the fixed effects model, the findings show stock market returns are negatively affected by the COVID-19 pandemic. Although most sectors face a sharp decline in returns, positive returns are found in some sectors such as Energy, Healthcare, and Utilities, which is the opportunities for investors amid the pandemic. When observing the effect of government intervention, the stock market reacts to it negatively. The same is true for the announcements of social distancing and economic support measures. However, the stock market responds to containment and health measures with positive returns. More importantly, social distancing policy measures further enlarge the negative impact of COVID-19 on stock market returns–thus the government should take these measures with caution. The results also emphasize that economic support policy measures benefit indirectly via the channel of decreasing new infections. As a whole, the study offers some suggestions for the best and most proactive policy actions that governments, market participants, and investors in other emerging markets with similar financial institutions to Vietnam’s should use in the event of exogenous shocks like the COVID-19.Item Fintech Credit and Bank Efficiency: International Evidence(MDPI (Basel, Switzerland), 2021-08-17) Le TDQ; Ho TH; Nguyen DT; Ngo T; Boubaker SThe expansion of fintech credit around the world is challenging the global banking system. This study investigates the interrelationships between the development of fintech credit and the efficiency of banking systems in 80 countries from 2013 to 2017. The findings indicate a two-way relationship between them. More specifically, a negative relationship between bank efficiency and fintech credit implies that fintech credit is more developed in countries with less efficient banking systems. Meanwhile, a positive impact of fintech credit on the efficiency of banking systems suggests that fintech credit may serve as a wake-up call to the banking system. Therefore, fintech credit should be encouraged by the authorities around the world.Item Digital Credit and Its Determinants: A Global Perspective(MDPI (Basel, Switzerland), 2023-12) Le TDQ; Ngo T; Nguyen DT; Ftiti ZDigital credit has gained much attention from academic researchers, practitioners, and policymakers worldwide. This study empirically evaluates the determinants of digital credit using cross-country data from 2013 to 2019. The conventional ordinary least square regression with fixed effects estimator is used to investigate the factors affecting the growth of digital credit. Our study highlights that the regulatory frameworks of anti-money laundering and terrorist financing, the economy’s innovative capacity, and financial development are significant factors affecting the development of digital credit, especially fintech credit. However, the findings indicate that only the innovation capacity is more critical to the expansion of bigtech credit. Nonetheless, our results provide some important implications for market participants and the authorities in promoting digital credit. Accordingly, this study contributes to the literature on the growth of digital credit when considering the critical roles of money laundering and terrorist financing frameworks and innovation capacity.Item Bank performance during the COVID-19 pandemic: does income diversification help?(Taylor and Francis Group, 2023-06-11) Ho TH; Nguyen DT; Luu TB; Le TDQ; Ngo TDThe Covid-19 pandemic’s economic effect led to tighter credit standards and a decline in the market for many types of loans. With a rich database of 1,231 banks in 90 countries from 2018Q1 to 2021Q4, we conducted a timely, broad-based international study to investigate whether non-interest activities, serving as a shock absorber, can promote bank performance before and during the Covid−19 pandemic. When using a dynamic panel data model with a system GMM estimator, our findings indicate that banks should be encouraged to diversify their income sources to reduce the adverse effects of the shock. With comparative analysis, we also found heterogeneous effects of income diversification on bank performance by its components, in pre-Covid−19 and during-Covid−19 periods, in both developed and developing countries. This study implies that bank managers should diversify income sources, especially fee-based services, trading activities, and foreign currency, to foster financial performance and stability during exogenous shocks.Item Efficiency of the Islamic Banking Sector: Evidence from Two-Stage DEA Double Frontiers Analysis(MDPI (Basel, Switzerland), 2023-03) Mai XTT; Nguyen HTN; Ngo T; Le TDQ; Nguyen LP; Ftiti ZThis paper examines the multi-dimensional efficiency of the Islamic banking sector and its determinants, including the impacts of the COVID-19 pandemic. To do that, we use a novel approach of two-stage data envelopment analysis (DEA) double frontiers to evaluate the overall efficiency of 79 Islamic banks across 16 countries (2005–2020). In the first-stage analysis, we found that the Islamic banking sector experienced an increasing trend in its efficiency and performance, even during the recent pandemic, although it varied across banks and countries. Our empirical results of the second-stage analysis further showed that economic development can help countries both withstand the recent pandemic and improve the efficiency and performance of their (Islamic) banking system. This, in turn, could help speed up the recovery process of the global economy. Since there is evidence that the Islamic banking sector is resilient to the COVID-19 pandemic, it is expected that this sector will be a driving force of such recovery.Item The trade-off frontier for ESG and Sharpe ratio: a bootstrapped double-frontier data envelopment analysis(Springer Science+Business Media, LLC, 2023-07-24) Boubaker S; Le TDQ; Manita R; Ngo TThe trade-off between the returns and the risks associated with the stocks (i.e., the Sharpe ratio, SR) is an important measure of portfolio optimization. In recent years, the environmental, social, and governance (ESG) has increasingly proven its influence on stocks’ returns, resulting in the evolvement from a two-dimensional (i.e., risks versus returns) into a multi-dimensional setting (e.g., risks versus returns versus ESG). This study is the first to examine this setting in the global energy sector using a (slacks-based measures, SBM) ESG-SR double-frontier double-bootstrap (ESG-SR DFDB) by studying the determinants of the overall ESG-SR efficiency for 334 energy firms from 45 countries in 2019. We show that only around 11% of our sampled firms perform well in the multi-dimensional ESG-SR efficient frontier. The 2019 average (in)efficiency of the global energy sector was 2.273, given an efficient level of 1.000. Besides the differences in the firm’s input/output utilization (regarding their E, S, G, and SR values), we found that the firm- (e.g., market capitalization and board characteristics) and country-level characteristics (e.g., the rule of law) have positive impacts on their ESG-SR performance. Such findings, therefore, are essential not only to the (responsible) investors but also to managers and policymakers in those firms/countries.Item Recognizing CEOs and Chairmen’s personality and bank performance: new insights from signature analysis(Taylor and Francis Group on behalf of the Chinese Economic Association – UK, 2024-03-30) Le TDQ; Ho TH; Ngo T; Luu TBThis study first uses graphology to examine the signatures of the CEOs and Chairmen of 26 commercial banks in Vietnam (2007-2020) to predict their personalities following the Big Five Personality model. Such personalities are used as a key explanatory variable to explain bank performance. Our findings extend the entrenchment theory that bank profitability is positively affected by the same personality traits of separate CEOs and Chairmen. More specifically, the findings indicate a positive relationship between bank profitability and conscientious and extraverted CEOs and Chairmen. When observing bank ownership, these two categories of personality traits are more critical to listed banks. As the first attempt to investigate whether separate CEO and chairman with the same characteristics may affect bank performance, our study will add more evidence to the existing literature about the relationship between corporate governance and bank profitability.Item Revisiting the Quiet-Life Hypothesis in the Banking Sector: Do CEOs’ Personalities Matter?(MDPI (Basel, Switzerland), 2024-03-20) Le TDQ; Nguyen DT; Ngo T; Bolton BThis study investigates the relationship between market power and bank profitability, and the impacts of CEOs’ personality traits, in Vietnam from 2007 to 2020. The analysis of CEOs’ signatures is used to determine their characteristics. The findings support the quiet-life hypothesis, which suggests that the negative relationship between market power and bank profitability may depend on CEOs’ characteristics. More specifically, the results show that conscientious CEOs with market power tend to reduce bank profitability, and this effect is more pronounced for foreign-owned banks. Therefore, our findings have critical implications for bank management.Item Predicting the performance of MSMEs: a hybrid DEA-machine learning approach(Springer Science+Business Media, LLC, 2023-02-14) Boubaker S; Le TDQ; Ngo T; Manita RMicro, small and medium enterprises (MSMEs) dominate the business landscape and create more than half of employment worldwide. How we can apply big data analytical tools such as machine learning to examine the performance of MSMEs has become an important question to provide quicker results and recommend better and more reliable solutions that improve performance. This paper proposes a novel method for estimating a common set of weights (CSW) based on regression analysis for data envelopment analysis (DEA) as an important analytical and operational research technique, which (i) allows for measurement evaluations and ranking comparisons of the MSMEs, and (ii) helps overcome the time-consuming non-convexity issues of other CSW DEA methodologies. Our hybrid approach used several econometric and machine learning techniques (such as Tobit, least absolute shrinkage and selection operator, and Random Forest regression) to empirically explain and predict the performance of more than 5400 Vietnamese MSMEs (2010‒2016), and showed that the machine learning techniques are more efficient and accurate than the econometric ones. Our study, therefore, sheds new light on the two-stage DEA literature, especially in terms of predicting performance in the era of big data to strengthen the role of analytics in business and management.Item A Dataset for the Vietnamese Banking System (2002–2021)(MDPI (Basel, Switzerland), 2022-09) Le TDQ; Ho TH; Ngo T; Nguyen DT; Tran SH; Guijarro FThis data article describes a dataset that consists of key statistics on the activities of 45 Vietnamese banks (e.g., deposits, loans, assets, and labor productivity), operated during the 2002–2021 period, yielding a total of 644 bank-year observations. This is the first systematic compilation of data on the splits of state vs. private ownership, foreign vs. domestic banks, commercial vs. policy banks, and listed vs. nonlisted banks. Consequently, this arrives at a unique set of variables and indicators that allow us to capture the development and performance of the Vietnamese banking sector over time along many different dimensions. This can play an important role for financial analysts, researchers, and educators in banking efficiency and performance, risk and profit/revenue management, machine learning, and other fields. Dataset: https://doi.org/10.7910/DVN/RIWA3B Dataset License: CC0
