Asia-Pacific Financial Markets最新文献

This paper investigates the time-varying connectedness between oil prices and the stock prices in African markets. We employ a wavelet-based dynamic conditional correlation framework, which allows us to look into the time-varying correlation between oil and African stock markets in time and frequency domains. Empirical results show the interdependence between oil prices and African stock market prices are time-varying and spread across various wavelet scales. More importantly, the dynamic relationship between oil prices and stock returns in these countries varies more frequently and at a lower level in the short run. However, we find the long and medium-range co-movements between them except during the Covid-19 period when short-term integration increased considerably, which might help portfolio managers and investors mitigate risk. We identify the hedge ratios and optimal portfolio weights for practical implications based on the said assets' dynamic conditional correlation.

The study examines the differences in financial debt choices of SME and Non-SME firms in India. Being SMEs, firms enjoy special grants and packages that non-SMEs firms do not, and very often, the SMEs do not want to let go of the SME status. This brings in the information asymmetry and agency problem among the market participants and this may result in differences in the debt choices of the firms. We found that the existing SMEs use more unsecured debt, the newly added SMEs use more long-term debt and secured debt reflecting firm-specific growth opportunities. This shows the difference in capital structure decisions of SMEs operated under different policy environments sourced because of the conflict of interests among the participants.

Can the investments in securities devoid of futures be effectively hedged? If so, what is the best cross-hedging instrument? The study evaluates the efficacy of the cross-hedging strategy for small and medium investors interested in banking sector stocks devoid of futures using the market index, sectoral index and stock futures from the same sector. The risk mitigation ability of each portfolio is estimated for different trade horizons using near-month futures and spot prices. The optimal futures contract size for minimising risk exposure is calculated using the Diagonal BEKK GARCH model with a minimum-variance approach. The cross-hedging portfolio with BANK NIFTY futures performs consistently well in a longer trading horizon with higher hedging costs. A cross-hedging portfolio with single stock futures also shows an excellent risk reduction potential but is less expensive than other alternatives. Fundamental investors achieve risk reduction up to 53.74 per cent cross-hedging using BANK NIFTY futures. Investors can construct cross-hedging portfolios with a closely matching return profile and hold these positions for a longer trade horizon to achieve higher risk reduction.

This study aims to predict GCC financial stress on oil market, and GCC Stock and bond markets while considering the effect of the 2008 financial crisis, 2014 oil drop price and the 2019 novel COVID-19 outbreak. For this purpose, we use a new approach for predicting the financial stress, based on the One-Dimensional Convolutional Neural Network (1D-CNN). This article introduces a parameters optimization method, which provides the best parameters for 1D-CNN to improve the prediction performance of the financial stress indices. The results suggest that indexes of financial stress help to improve forecasting performance. It implies that the 1D-CNN model shows a better predictive performance in the out-of-sample findings.Regarding the influence of financial stress on hedging between Brent, and financial markets, the outcomes emphasize the role of oil in hedging stock market risks in positive market stress case. Another interesting result is that the out-of-sample estimates for stock–bond markets, hedging with oil have higher variability for negative (positive) financial stress. The findings highlight the predictive information captured by financial stress in accurately forecasting oil market volatility and financial markets, offering a valuable opening for investors to monitor oil market volatility using information on traded assets.

The present research is carried out to make a comparative investigation of the impact of board variables on organizational performance before and after the enactment of the Companies Act, 2013, in the Indian corporate sector. Data of 66 Indian companies listed on the BSE Dollex are analysed in two time periods before (2009–2013) and after (2014–2018) the enactment of the Companies Act, 2013. Regression analysis is used to check the effect of independent directors, female directors, CEO duality and board meetings on company performance, as indicated by ROA, ROE and Tobin’s Q. The findings reveal that independent directors and CEO duality have a considerable negative effect on corporate performance as measured by accounting based performance measures, in the post–enactment period of the Companies Act which was insignificant before the enactment of this Act. The effect of women’s representation and board meetings on organizational performance remains insignificant in both periods of the study. The study suggests that organizations should be attentive towards the board practices adopted by them, in order to present a positive and effective image to stakeholders which results in increasing revenues. Furthermore, policymakers should rethink the corporate board regulations as these variable reforms do not have a substantial effect on corporate performance.

This study examines the presence of the “month of the year effect” in the six emerging Asian stock markets (India, Indonesia, Japan, Malaysia, Philippines, and South Korea) for the period January, 1991 to November, 2020 using GARCH (1, 1), EGARCH (1, 1) and TGARCH (1, 1) models. The empirical results indicate the existence of “month of the year effects” on stock returns and volatility of all the emerging Asian stock markets except Japan. The study reveals a positive and significant January effect for each country except Japan. February, April and July effects are positive and significant only in the case of Indonesia, South Korea and Malaysia respectively. The findings confirm the persistence of ARCH and GARCH effects in the monthly return series. Moreover, the asymmetric GARCH models show that the emerging Asian stock market returns exhibit asymmetric (leverage) effect. The seasonal or monthly effect in stock markets in Emerging Asian countries poses an important research question as Emerging Asia’s economic footprint has been growing significantly. The findings of the study have important implications for active and profitable trading strategies.

This article examines the relationships between remittance and financial development (financial institutions and markets) in India and China on the availability of annual data from 1984 to 2018. Human capital formation is considered as a channel of remittances in financial development functions. Institutional quality, Economic globalization, foreign direct investment, economic growth, and government investment are included as a set of control variables in the financial development function. The results of the ARDL bounds test model indicate that remittance can positively impact financial development dynamics in both countries. While considering the human capital formation, higher levels of skilled human capital (secondary and tertiary enrolments) enhance financial development, but low-level human capital (primary enrolments) fails to do so. One contradiction found from the result is that remittance is negatively but significantly affecting financial institutions in India, and also detrimental to China's financial market. Oppositely, remittance positively impacts India’s financial market and China’s financial institutions. We find the varying impacts of control variables on financial development. The outcome of this paper stresses the necessity of a higher level of skilled human capital and improved institutional quality in both countries, which provides better utilization of remittances and other foreign and domestic financial flows.

Exchange Traded Funds (ETF’s) are one of the beloved passively managed funds that offer both retail and institutional investors an access to highly profitable and wide- range of diversifiable financial assets. The study aims to assess the ability of Indian equity ETF’s in replicating the performance of their benchmark indices using a sample of 27 equity ETF’s traded on the National Stock Exchange of India during the pre-pandemic period from 01/01/2015 to 31/12/2019. Evaluation of the performance of sample ETF’s through risk-return analysis, risk-adjusted performance measures, tracking error analysis and multi-factor regression have revealed that the majority of the sample ETF’s outperformed their tracking indices but with notable tracking errors during the study period. Further, the study also indicates that the returns of the sample ETF’s have a significant and positive relationship with the returns of the index but are inversely related to risk and management fees. The results of this study will have major implications for investors in evaluating the performance of ETF’s and fund managers as well in taking suitable measures to reduce tracking errors that will help in successful replication of the benchmark along with undertaking initiatives that will enable the ETF’s to become price efficient.

This study aims to investigate the causal linkage between foreign direct investment (FDI) inflows and economic globalization (considering de facto and de jure indexes) for 7 Association of Southeast Asian Nations (ASEAN) countries for 1985–2018. Our sample consists of Indonesia, Laos, Malaysia, the Philippines, Singapore, Thailand, and Vietnam. Empirically, we propose the panel bootstrap causality test based on wavelet decomposition to find a causal link between the series in different time scales. The main advantages of the methodology can be listed as follows; (a) testing the unit root behavior of the series, or existence of a cointegration relationship between the series are not pre-requisites, (b) one can test the causal relationship between the series in different time scales. Also, we employ the panel bootstrap causality test of Kónya (Econ Modell 23:978–992, 2006) to compare our results with the panel bootstrap causality test based on wavelet decomposition. In addition to the causality analyses, this study utilizes the panel bootstrap cointegration test of Westerlund-Edgerton (2007) to find long-run relationship between variables. The proposed method’s results exhibit that ASEAN countries’ FDI inflows and types of economic globalization levels have mutually affected each other, especially in the long-run. The empirical findings offer some significant implications for policymakers.

An index measuring the degree of dependence in a set of asset returns is defined as the ratio of an equivalent number of independent assets to the number of assets. The equivalence is based on either attaining the same optimized value enhancement or spread reduction. The value enhancement is the difference in value of a value maximizing portfolio and the maximum value delivered by the components. The spread reduction is the percentage reduction attained by a spread minimizing portfolio relative to the smallest spread for the components. Asset values or bid and ask prices of portfolios, are modeled by conservative valuation operators from the theory of two price economies. The dependence indices fall with the number of assets in the portfolio and they are explained by a measure of concentration applied to normalized eigenvalues of the correlation matrix along with the average level of correlation, the level of the (Rudin and Morgan, 2006) portfolio diversification index and the number of assets in the portfolio. A time series of the indices constructed on the basis of the ( S & P) 500 index and the nine sector ETF’s reveals a collapse during the financial crisis with no recovery until 2016, with a peak in February 2020 and a COVID crash in March of 2020. Furthermore, factor dependence benefits are richer than those found in equity indices. Dependence benefits across global indices are not as strong as dependence benefits across an equal number of domestic assets, but they rise substantially for longer horizons of up to three years.