• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.37-46
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• 2020

The paper examines the dynamic relationship of domestic credit and stock market liquidity on the economic growth of the Philippines from 1995 to 2018 applying the autoregressive distributed lag (ARDL) bounds testing approach to cointegration, together with Granger causality test based on vector error correction model (VECM). The ARDL model indicated a long-run relationship of domestic credit and stock market liquidity on GDP growth. When the GDP per capita is the dependent variable there is weak cointegration. Also, the Johansen cointegration test confirmed the existence of long-run relationship of domestic credit and stock market liquidity both on GDP growth and GDP per capita. The VECM concludes a long-run causality running from domestic credit and stock market liquidity to GDP growth. At levels, domestic credit has significant short-run causal relationship with GDP growth. As for stock market liquidity at first lag, has significant short-run causal relationship with GDP growth. With regards to VECM for GDP per capita, domestic credit and stock market liquidity indicates no significant dynamic adjustment to a new equilibrium if a disturbance occurs in the whole system. At levels, the results indicated the presence of short-run causality from stock market liquidity and GDP per capita. The CUSUMSQ plot complements the findings of the CUSUM plot that the estimated models for GDP growth and GDP per capita were stable.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.1
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• pp.11-23
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• 2003

This study Investigates the short and long-run dynamic relationships between the domestic and U.S. stock markets for the period of declining stock prices. It Is well known that the domestic stock market variations are largely caused by the U.S. stock market movements. Multivariate causal tty test Is utilized to examine the lead-lag relationships among four stock prices of KOSPI and KOSDAQ In the domestic part and DOWJONES and NASDAQ In the U.S. part. When the stock prices tend to decrease In the long run, It Is found that both KOSPI and KOSDAQ have closer relations with NASDAQ than DOWJONES. When both of domestic stock markets are severely fluctuate, bidirectional causal relationships appear to exist between NASDAQ and each of KOSPI and KOSDAQ. On the other hand. when the domestic stock markets are relatively stable, unidirectional causality Is found to exist between NASDAQ and each of KOSPI and KOSDAQ. which is explicitly validated by the analysis of variance decomposition.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.543-549
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• 2021

The stock market plays a crucial role in the growth of industry and trade, which eventually affects the economy. This paper studies the determinants of stock market development in Jordan using yearly time-series data (1978-2019). The autoregressive distributed lag approach is applied to examine co-integration, while the vector error correction model is employed to estimate (long-run and short-run) causal relationships. The results show that macroeconomic determinants such as gross domestic product, gross domestic savings, investment rate, credit to the private sector, broadest money supply, stock market liquidity, and inflation rate are important determinants of stock market development. These findings provide vital implications for policymakers in developed and emerging stock markets. First, economic development plays an imperative role in stock market development. Second, developing the banking sector is mandatory because it can significantly promote stock market development. Third, domestic investment is a significant determinant of stock market development, especially in emerging countries. However, it is vital to launch policies that lead to encourage investment and promote stock market development, and this could be done through (1) encouraging competition, (2) improving the institutional framework, and (3) removing trade blocks by establishing a mutual connection between foreign private investment entities and government authorities.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.9-24
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• 2022

With a view to attracting foreign investment and growing the economy, the Vietnamese government has hastened financial reforms, including the lifting of limitations on foreign investment, which has resulted in rapidly rising foreign ownership in recent years. To study the relationship between transactions of foreign investors and transactions of domestic investors on two stock exchanges in Vietnam Ho Chi Minh City Stock Exchange (HSX) and Hanoi Stock Exchange (HNX). This study applies a secondary dataset comprising daily market trading information of 912 stocks from 18 industries listed on 2 Vietnam stock exchanges, including HSX and HNX, which includes executed price, executed volume, daily Buy Orders, and Sell Orders categorized into domestic investors' orders and foreign investors orders from 01.04.2010 to 10.04.2018. The regression results show a significantly positive relationship between foreign investors' trading and domestic investors' transaction in all trading activities in both up and down markets. Therefore, these results indicate that domestic investors in Vietnam are concerned with foreign investors' trading as an important sign, and domestic investors tend to follow their counterparties without appropriate fundamental information. From there, there are signs of herding behavior of domestic investors following foreign investors in transactions on the stock market in Vietnam.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.135-140
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• 2022

In the domestic stock market, the capital market opened in January 1992, and the proportion of foreign capital has steadily increased, accounting for 30% of the domestic market in Overall stock market trend infers that the domestic stock market is more influenced by foreign issues than domestic issues. The trading trend of foreign capital displays a similar flow to exchange rate fluctuations,; thus, preparing an investment strategy by using the Pearson analyzing method the effect of exchange rates of foreign capital trading, fluctuations in exchange rates, and predicting one of the macroeconomic indicators will yield high returns in the stock market. Therefore, this research was conducted to help investment by predicting foreign variables comparing and analyzing exchange rates and foreign capital trading patterns, and predicting appropriate time for buying and selling.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.1-9
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• 2021

This paper investigates the impact of the domestic and global outbreak of the coronavirus (COVID-19) pandemic on the trading size of the Malaysian stock (MS) market. The theoretical model posits that stock markets are affected by their response to disasters and events that arise in the international or local environments, as well as to several financial factors such as stock volatility and spread bid-ask prices. Using daily time-series data from 27 January to 12 May 2020, this paper utilizes the traditional Augmented Dickey and Fuller (ADF) technique and Zivot and Andrews with structural break' procedures for a stationarity test analysis, while the autoregressive distributed lag (ARDL) method is applied according to the trading size of the MS market model. The analysis considered almost all 789 listed companies investing in the main stock market of Malaysia. The results confirmed our hypotheses that both the daily growth in the active domestic and global cases of coronavirus (COVID-19) has significant negative effects on the daily trading size of the stock market in Malaysia. Although the COVID-19 has a negative effect on the Malaysian stock market, the findings of this study suggest that the COVID-19 pandemic may have an asymmetric effect on the market.

• Korean Management Science Review
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• v.32 no.3
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• pp.91-103
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• 2015

This study recognizes that there is a correlation between the movement of the financial market and the sentimental changes of the public participating directly or indirectly in the market, and applies the relationship to investment strategies for stock market. The concerns that market participants have about the economy can be transformed to the search terms that internet users query on search engines, and search volume of a specific term over time can be understood as the economic trend of big data. Under the hypothesis that the time when the economic concerns start increasing precedes the decline in the stock market price and vice versa, this study proposes three investment strategies using casuality between price of domestic stock market and search volume from Naver trends, and verifies the hypothesis. The computational results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior in domestic stock market.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.153-160
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• 2015

The domestic stock market has been subjected to a major change since the September 1997 financial crisis. Foreign capital came repeat themselves in the stock market and bond market, foreign exchange market opening up domestic financial markets after the financial crisis. The domestic stock market has been most affected by domestic capital before the financial crisis. But it has been receiving an absolute influenced by foreign capital after the financial crisis. The purpose of this study is to analyze the trends in the two sections that look at any changes in the volatility of the KOSPI appears after the crisis. To this, obtained a daily weekly monthly normal distribution and kurtosis, skewness degree it should be analyze the tilt phenomenon and variability of the two intervals. This study also predict the future movement of the domestic stock market Based on this, look at the difference between the two sections. Analysis result, after the financial crisis change width has a reduction but direction of the KOSPI has appeared relatively distinct in the medium to long term. Based on this future market seems desirable the mid- to long-term investment looking for direction.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.4
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• pp.113-125
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• 2008

This paper investigates the spillover effects(co-movements) between korean and U.S stock market by KOSPI and DJIA Index. Especially it compare to the pre- and post period of U.S. financial crisis resulted from sub-prime mortgage loan. The main results are as follows. First, the spillover effects of DJIA(U.S. market) to KOSPI(Korean market) are strong. This result accord with the former researches on this subject. Second, spillover effects are more strong after U.S. financial crisis. A possible reason for this phenomenon is a trend which the major investors such as foreign and institutional investors in domestic stock market have more attention to U.S. stock market. Third, the spillover effects appear in the opposite direction, that is KOSPI(Korean Stock Market) to DJIA(U.S. Stock Market). It seems to be the results of asian stock market's growing infIuences to European and U.S Markets.

• The Journal of Information Systems
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• v.30 no.3
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• pp.21-45
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• 2021

Purpose This paper analyzed the impacts of domestic stock market by a global pandemic such as COVID-19. We investigated how the overall pattern of the stock market changed due to the impact of the COVID-19 pandemic. In particular, we analyzed in depth the pattern of stock price, as well, tried to find what factors affect on stock market index(KOSPI) in the healthcare industry due to the COVID-19 pandemic. Design/methodology/approach We built a data warehouse from the databases in various industrial and economic fields to analyze the changes in the KOSPI due to COVID-19, particularly, the changes in the healthcare industry centered on bio-medicine. We collected daily stock price data of the KOSPI centered on the KOSPI-200 about two years before and one year after the outbreak of COVID-19. In addition, we also collected various news related to COVID-19 from the stock market by applying text mining techniques. We designed four experimental data sets to develop decision tree-based prediction models. Findings All prediction models from the four data sets showed the significant predictive power with explainable decision tree models. In addition, we derived significant 10 to 14 decision rules for each prediction model. The experimental results showed that the decision rules were enough to explain the domestic healthcare stock market patterns for before and after COVID-19.