• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.725-735
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• 2021

This study investigates whether the Islamic Exchange-Traded Funds (ETFs) provide significant benefit to investors relative to conventional ETFs. Six pairs of Islamic and conventional ETFs with 10-year daily price data from 2010 to 2019 have been selected from major market indices like MSCI World Index, MSCI Emerging Markets, MyETF Dow Jones Islamic Market Malaysia, MSCI South East Asia and Wahed FTSE Shariah USA Index for this study. For ETFs that are launched after 2010, the price data from launch date to 2019 are used. Our results show: First, Islamic ETFs are more likely to trade at a premium rather than at a discount, implying the investors are willing to pay a premium. Second, it is also found that Islamic ETFs have a relatively shorter period of price deviation from the benchmark, implying more price stability. Third, conventional ETFs have higher return and lower tracking errors relative to Islamic ETFs. These new findings add to the stylized facts of Islamic ETFs in the extant literature for investors, plan sponsors and regulators as to the differences between the ETFs. As policy suggestion, asset management companies can design new investment products to bridge the gap between conventional and Islamic finance.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.563-570
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• 2021

This study aims at exploring the corporate social responsibility (CSR) practices in the listed companies of Bangladesh. One hundred eighty-two different companies from fifteen different sectors have been selected as a sample. A weighted disclosure index having fifty-two items has been applied to ensure the degree of CSR practices of the sample companies. Each of the content has been assigned a three-scale value starting from zero to two. After that, eight dimensions of CSR are identified from CSR literature and have been evaluated by the predetermined disclosure index. Finally, a composite CSR disclosure (CSRD) score has been computed to measure the extent of CSR practices of the sample companies. The findings of the study reveal a poor CSRD score by the sample companies. Besides, it has been found that the listed companies provide more CSR activities on employee-related issues and community service-related issues while the listed companies provide less information on energy-related CSRD and customer-related CSRD in the context of Bangladesh. The findings of the study imply that the government and the regulatory authority should give more attention to develop a harmonized standards or policies to measure the degree of CSR practices for comparative purposes.

• East Asian Journal of Business Economics (EAJBE)
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• v.9 no.1
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• pp.41-51
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• 2021

Purpose - The purpose of this study is to propose strategies of improving efficiency of 20 listed port companies in China based on analysis of their input-output indexes from 2014 to 2018. Research design, data, and methodology - In this paper, the relevant input-output indicators of 20 listed port companies in China from 2014 to 2018 were adopted. Data derived from the company annual reports announced by Shanghai stock exchange and Shenzhen stock exchange. Comprehensive efficiency and pure technical efficiency were measured from output perspective by DEA and Malmquist index, and efficiency changes and regional efficiency were analyzed. Result - The results showed that the efficiency value of 20 listed port companies in China fluctuated and increased during 2014-2018, regional efficiency was unbalanced, and change of MPI was influenced by internal factors and external factors. Listed port companies affected by internal and external factors needed to make appropriate response to internal and external factors. Conclusion - The research conclusion can provide important reference information about management and planning for port companies in China and related areas. However, this paper is limited to the availability of data. So the improvement scheme for listed companies in inefficient regional ports needs further study, such as using AHP method.

• The Journal of Industrial Distribution & Business
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• v.13 no.10
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• pp.1-8
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• 2022

Purpose: Support vector machines (SVMs) ensemble has been proposed to improve classification performance of Credit risk recently. However, currently used fusion strategies do not evaluate the importance degree of the output of individual component SVM classifier when combining the component predictions to the final decision. To deal with this problem, this paper designs a support vector machines (SVMs) ensemble method based on fuzzy integral, which aggregates the outputs of separate component SVMs with importance of each component SVM. Research design, data, and methodology: This paper designs a personal credit risk evaluation index system including 16 indicators and discusses a support vector machines (SVMs) ensemble method based on fuzzy integral for designing a credit risk assessment system to discriminate good creditors from bad ones. This paper randomly selects 1500 sample data of personal loan customers of a commercial bank in China 2015-2020 for simulation experiments. Results: By comparing the experimental result SVMs ensemble with the single SVM, the neural network ensemble, the proposed method outperforms the single SVM, and neural network ensemble in terms of classification accuracy. Conclusions: The results show that the method proposed in this paper has higher classification accuracy than other classification methods, which confirms the feasibility and effectiveness of this method.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.143-152
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• 2022

This paper examines the relationship between investor sentiment and the risk of a stock price crash at the firm level. Our dataset includes 131 firms listed on the Saudi stock exchange (Tadawul) from 2011 to 2019, as well as 953 firm-year observations. To evaluate crash risk, we employ two distinct proxies and propose an index for measuring firm-level sentiment which we use for the first time in our study. The average turnover rate, price-earnings ratio, and overnight return are the three sentiment proxies we utilize in our index. Our findings show that high levels of investor emotion increase managers' proclivity to withhold unfavorable news from investors, which aggravates the risk of a stock price crash. We undertake cross-sectional regressions by sector to ensure the robustness of our findings, and our findings are confirmed. After accounting for any endogeneity issues with the GMM technique, the results remain the same. Furthermore, we analyze the liquidity effect by dividing our sample into subsamples with better and worse liquidity and find that firms with worse liquidity have a considerably greater positive impact of investor mood. Overall, our findings help investors and regulators recognize the significance of this downside risk and how to manage it in the stock market.

• Korea Trade Review
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• v.45 no.4
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• pp.25-43
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• 2020

This study mainly measures the level of trade facilitation in member countries along the "the Belt and Road" and discusses the impact of trade facilitation on bilateral trade. Based on the research results of domestic and foreign scholars, this study made a new systematic measuring system which covering 4 indicators and 15 subordinate indicators, to obtain the trade facilitation index. Based on the extended gravity model, this paper conducts a panel data, for more than 50 major trading members along the "the Belt and Road" during 2010~2017 as an example to empirically study the relationship between the trade facilitation level of major trading members and the volume of China's import and export trade. The results show that the level of trade facilitation among member countries is not high and the trade facilitation variable has positive value, indicating that the trade facilitation variable has positive effect on increasing bilateral trade. If the trade facilitation increases by 1% respectively, the bilateral trade level will increase by 0.98% separately. Finally, according to the regression results of four aspects of the trade facilitation index system, e-business development plays the most significant role in promoting trade facilitation.

• Korean Management Science Review
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• v.32 no.4
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• pp.57-67
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• 2015

It is a familiar Wall Street adage that "It takes volume to make prices move." Numerous researches have found the positive correlation between trading volume and price changes. Recent studies have documented that informed traders have strong influences on stock market prices through their trading with distinctive information power. Ever since 1992 capital market liberalization in Korea, it is said that foreign investors make consistent profits with their superior information and analytical skills. This study aims at whether we can make a profitable trading strategy by using the foreign investors' trading information. We analyse the relation between the KOSPI index returns and the foreign investors trading volume using GARCH models and VAR models. This study suggests the profitable trading strategies based on the documented relation between the foreign investors' trading volume and KOSPI index returns. We simulate the trading system with the real stock market data. The data include the daily KOSPI index returns and foreign investors' trading volume for 2001~2013. We estimate the GARCH and VAR models using 2001~2011 data and simulate the suggested trading system with the remaining out-of-sample data. Empirical results are as follows. First, we found the significant positive relation between the KOSPI index returns and contemporaneous foreign investors' trading volume. Second, we also found the positive relation between the KOSPI index returns and lagged foreign investors' trading volume. But the relation showed no statistical significance. Third, our suggested trading system showed better trading performance than B&H strategy, especially trading system 2. Our results provide good information for uninformed traders in the Korean stock market.

• The Journal of Bigdata
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• v.4 no.2
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• pp.115-126
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• 2019

There have been many discussions on export indices in trade exports, but there is no definite trade export index which can be explained by objective indicators. Korea International Trade Association (KITA), Korea Trade-Investment Promotion Agency (KOTRA), etc., but we are currently in the process of thinking about ways to express the capabilities of exporting companies. In this study, we constructed the AI data sets by setting the activity indicators such as the size of the company and the credit score, the number of transaction customers, the number of transactions, the number of items, the transaction volume, and the transaction period as features, Lightgbm. Using the Graph Neural Network as an industrial cluster classification model, the export live index which expresses the exportable capacity among companies, items, and business groups was calculated. This includes the past activity of the company from the current calculating index Objectivity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5671-5676
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• 2011

Volatility Index is the index that represents future volatility of underlying asset implied in option price and expected value of market that measures the possibility of stock price's change expected by investors. The Korea Exchange announces a volatility Index, VKOSPI, since April, 13, 2009. This paper used daily data from January, 2002 through December, 2008 and tested power of Volatility index for future returns of portfolios sorted by size, book-to-market equity and beta. As a result, VKOSPI has the predictive power to future returns and then VKOSPI may be determinants of returns. Also if beta is included when sorting portfolio, the predictive power of VKOSPI is stronger for future portfolio returns.

• Asia-Pacific Journal of Business
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• v.14 no.2
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• pp.51-61
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• 2023

Purpose - Since COVID-19, the government's expansion of liquidity to stimulate the economy has resulted in an increase in private debt and an increase in asset prices of such as real estate and stocks. The recent sharp rise of the US Federal fund rate and tapering by the Fed have led to a fast rise in domestic interest rates, putting a heavy burden on the Korean economy, where the level of household debt is very high. Excessive household debt might have negative effects on the economy, such as shrinking consumption, economic recession, and deepening economic inequality. Therefore, now more than ever, it is necessary to identify the causes of the increase in household debt. Design/methodology/approach - Main methodology is regression analysis. Dependent variable is household loans from depository institutions. Independent variables are consumer price index, unemployment rate, household loan interest rate, housing sales price index, and composite stock price index. The sample periods are from 2017 to May 2022, comprising 72 months of data. The comparative analysis period before and after COVID-19 is from January 2017 to December 2019 for the pre-COVID-19 period, and from Jan 2020 to December 2022 for the post-COVID-19 period. Findings - Looking at the results of the regression analysis for the entire period, it was found that increases in the consumer price index, unemployment rate, and household loan interest rates decrease household loans, while increases in the housing sales price index increase household loans. Research implications or Originality - Household loans of depository institutions are mainly made up of high-credit and high-income borrowers with good repayment ability, so the risk of the financial system is low. As household loans are closely linked to the real estate market, the risk of household loan defaults may increase if real estate prices fall sharply.