Capital Markets Review Vol. 32, No. 1 pp. 1-114 (2024)
Capital Markets Review Vol. 32, No. 1, pp. 1-27 (2024)
Assessing the Carbon Footprints of Income Growth, Green Finance, Institutional Quality and Renewable Energy Consumption in Emerging Asian Economies
Tze-Haw Chan1*, Abdul Saqib1 & Agustin Isnaini Nuzula1
1Graduate School of Business, Universiti Sains Malaysia, Malaysia.
Abstract: Research Question: What is the applicability of the Environmental Kuznets Curve (EKC) hypothesis in emerging East and South Asian countries? Do institutional quality, trade openness, renewable energy consumption, green finance, financial development, and their interaction influence carbon emissions? Motivation: A new assessment of green finance, institutional quality, financial development, and other relevant variables in shaping the EKC hypothesis is required. Idea: In the context of emerging Asian countries, it requires consideration of cross-sectional dependence (CSD) due to the high economic integration among East and South Asian countries. They shared residual interdependency and cross-sectional exposure to common shocks, such as oil shocks, global financial shocks, and supply chain disruptions; hence, a more nuanced and multidisciplinary approach is needed. Data: A panel dataset that ranges from 2000 to 2019 is employed for ten developing East and South Asian economies, including China, India, Pakistan, Bangladesh, Sri Lanka, Indonesia, Malaysia, Thailand, Vietnam, and the Philippines. Method/Tools: A series of panel analyses, including the CSD test, slope heterogeneity test, the 2nd generation panel unit root and cointegration tests, and CS-ARDL modelling, have been employed to address heterogeneity and cross-sectional dependence issues. Robustness tests using the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimators corroborate the findings, reinforcing the study’s credibility and policy implications. Findings: Both the short- and long-run results consistently confirm the income-environmental degradation link, but the U-type EKC effect is absent. While green finance, trade openness, and financial development have insignificant impacts on carbon emissions, institutional quality and renewable energy consumption exhibit negative effects, highlighting their importance in curbing environmental degradation. More policy efforts are needed to promote investment in environmental financing, upgrade clean production technology, and enhance the decarbonization process. This study also identifies heterogeneity and cross-sectional dependence on environmental policies among these nations. Contributions: Green finance and R&D investments in green technologies are inadequate. Efforts to promote carbon neutrality by redirecting financing towards the sustainable and renewable energy sectors are needed. These findings underscore the need for greater collaborative efforts among emerging Asian nations, particularly China, to safeguard the environment and achieve sustainable development.
Capital Markets Review Vol. 32, No. 1, pp. 29-58 (2024)
Are Malaysian IPO Investors Influenced by Sentiment Factors or Fundamental Factors?
Evelyn Yee-Foon Kong1* & Kin-Boon Tang 1
1 Nottingham University Business School Malaysia, University of Nottingham Malaysia, Malaysia.
Abstract: Research Question: This study constructs and employs a composite market sentiment index, and a full range of issue, firm, and market characteristics variables to study Initial Public Offering (IPO) markets in Malaysia. Motivation: Radical changes in the Malaysian financial environment, particularly changes in Malaysia’s capital market structure in the past few decades, may have increased heterogeneity in the composition of participants and impacted investors’ risk-taking behavior. This study provides a more comprehensive understanding of the dynamics that shape IPO behavior in Malaysia. Idea: The main objective of this study is to study market sentiment and Malaysian IPOs. To determine whether Malaysian IPOs underpriced, and to identify their key determinants from behavioral and fundamental perspectives. Data: This study investigates 571 IPOs firms listed on Bursa Malaysia from January 2000 to December 2020. Method/Tools: Multiple and binary regression models are employed to examine the determinants of IPO underpricing. Additionally, interaction analysis and marginal probability analysis are used to explain the short-run IPO share performance. Three different methods are used to construct the Malaysian IPO Market Sentiment Index: (1) Baker and Wurgler’s (2007) Principal Component Analysis method; (2) Jiang et al.’s (2022) Scaled Principal Component Analysis method; and (3) Huang et al.’s (2015) Partial Least Squares method. Findings: This study found that overall the Malaysian IPOs underpriced by 28.48% based on the market-adjusted initial return. The findings evidence that sentiment factor plays a significant role in the short-run IPO share performance. The results of this study is consistent with the study by Leite (2005) shown that the presence of sentiment investors in IPOs reduces the winner’s curse problem (Rock’s hypothesis) in the issue by increasing the relative probability for the least-informed (rational) investor to be allocated underpriced shares. Contributions: This study acknowledges the limitations of neoclassical finance theories in explaining the behavior of investors in Malaysian IPO markets. By incorporating behavioral finance theories, this study recognises that fundamental factors might not be the sole driver of investor decisions. This shift in focus toward market sentiment and psychology adds a fresh perspective to understanding IPO underpricing.
Capital Markets Review Vol. 32, No. 1, pp. 59-73 (2024)
Stock Market Reactions to COVID-19 Announcement: Developed Versus Emerging Markets and Large Versus Small Firms
Siew Peng Lee1* & Mansor Isa 2
1Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman, Malaysia.
2 Faculty of Business and Economics, Universiti Malaya, Malaysia.
Abstract: Research Question: How do stock markets around the world react to the World Health Organization (WHO)’s announcement on 11 March 2020 declaring COVID-19 as a global pandemic? Are there any differences in the reaction between developed and emerging markets? Are there any differences in the reaction between large and small firms? Motivation: There is a need to have a better understanding on whether different markets react differently to COVID-19 announcement. It is also important to know what factors make some markets more resilient than others. Idea: We envisage that developed markets, large firms, large stock markets, and markets with international exposure would demonstrate greater degree of resiliency than their respective counterparts. The results of this study would have profound implications on the ability of markets to withstand against global pandemic such as the COVID-19. Data: The sample consists of 30 world’s largest stock markets based on their market capitalization on 31 December 2019, consisting of 18 developed markets and 12 emerging markets. For each market, we collect two indices: the main index representing large firms and the small-firm index representing small firms. Method/Tools: This is an event study using the market model and market-adjusted model to estimate abnormal returns. We then use the OLS and feasible GLS for cross-sectional regression analysis of the CARs. Findings: This study finds that the WHO’s pandemic announcement negatively impacts stock market returns around the world in the short-term, while in the intermediate-term the markets recover some of the losses. Developed markets are less affected than emerging markets and large firms are better able to withstand the pandemic impact. The multiple regression results show that stock market size is positively related to CARs, and a country’s international exposure is negatively associated with short-run CARs but is positively associated with intermediate-term CARs. Contributions: This study documents evidence of stock market reactions around the world to the announcement of the COVID-19 pandemic by the WHO. The study focuses on the difference in the reaction by developed versus emerging markets and by large versus small firms. Further, this study provides several institutional factors that influence the extent of the impact of the COVID-19 pandemic on share prices. Knowing these factors would be useful to governments, policymakers and companies to design strategies to help markets becoming more resilient to systemic risks such as the COVID-19 pandemic.
Capital Markets Review Vol. 32, No. 1, pp. 75-99 (2024)
The Role of Institutional Investors in The Indian Stock Markets During the Pandemic
Nikunj Patel1, Aakruti Patel 1 & Bhavesh Patel1*
1 Institute of Management, Nirma University, India.
Abstract: Research Question: The study evaluates the behaviour of the FIIs and DIIs on the returns and volatility of the four major Indian stock indices namely, Nifty 50, Nifty Next 50, BSE Sensex, and BSE 100 before and during the pandemic of COVID-19. To capture the volatility, exogenous variable, India VIX has been used. Motivation: Due to the stringent measures taken by several countries in response to the COVID-19 pandemic, there was an initial downturn in the global economic prospects and a meltdown in the financial markets. Idea: It made the individual investors curious about the behaviour of institutional investors to take a position amidst the highly uncertain environment. Data: The daily data of buying and selling of FIIs and the DIIs and the four indices have been obtained from the period January 1, 2011, to April 3, 2020. Further, the study is divided into three sub-periods that is full, before COVID and during COVID. Method/Tools: Various analysis were performed using correlation, rolling correlation, Granger causality, GARCH, GJR-GARCH and EGARCH to gauge the relationship between activities of FIIs and DIIs and the market returns. Findings: The outcome of the analysis reveals that both the FIIs and DIIs play significant role in generating the returns and volatility in the Indian stock market. However, during the pandemic of COVID-19, the FIIs led the market returns and DIIs led the volatility. This is due to the fact that the DIIs were the net buyers during this period and the distribution of their net position was positively skewed. The leverage effect is also observed. The persistence of the volatility is highest during COVID-19. Contributions: The study is one of a kind adding to the existing body of knowledge related to the behaviour of FIIs and DIIs during the global epidemic. It is the most recent and closely related to the literature on capturing FII and DII investment patterns during a global pandemic.
Capital Markets Review Vol. 32, No. 1, pp. 101-114 (2024)
Does Uncertainty Indices Impact the Cryptocurrency Market?
Li Yi Thong1, Ricky Chee Jiun Chia1 & Mohd Fahmi Ghazali2*
1Labuan Faculty of International Finance, Universiti Malaysia Sabah, Malaysia.
2Faculty of Economics and Management, Universiti Kebangsaan Malaysia, Malaysia.
Abstract: Research Question: Does uncertainty indices have impact on cryptocurrency? Motivation: Most of the previous study investigate the impact of geopolitical risk and economic policy uncertainty on Bitcoin only and less research investigate the long run and short run relationship between the uncertainty indices and cryptocurrency. Hence, this study investigates whether the economic policy uncertainty, geopolitical risk and US equity market uncertainty have an impact on Bitcoin, Ethereum and Binance Coin by the multivariate VAR Granger non-causality. Idea: This study applied three different uncertainty indices (geopolitical risk, economic policy uncertainty and US equity market uncertainty) and top three ranking cryptocurrency (Bitcoin, Ethereum and Binance Coin) to investigate and compare the impact of uncertainty indices on cryptocurrency with different uncertainty conditions and applied top three ranking cryptocurrency in cryptocurrency market to reinforce the result. Data: This study applied monthly data with 42 observations which cover the period of December 2017 until May 2021 and data for cryptocurrency extracted from investing.com, while the uncertainty indices from policyuncertainty.com. Method/Tools: This study utilize multivariate VAR Granger non-causality to examine the cointegration relationship between the cryptocurrency and uncertainty indices. Findings: The results show that the economic policy uncertainty, geopolitical risk and US equity market uncertainty cointegrated with Bitcoin, while Binance Coin cointegrated with geopolitical risk only. Hence, the economic policy uncertainty, geopolitical risk and US equity market uncertainty plays a vital role in the Bitcoin prediction and geopolitical risk plays an important role to forecast the Binance Coin. Contributions: The Bitcoin investors may focus on the changes in economic policy uncertainty, geopolitical risk and US equity market uncertainty to predict the Bitcoin return, and Binance Coin investors focus on the geopolitical risk.
Updated on 30 March 2024 by Editorial Assistant