• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.107-115
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• 2020

This study is concerned with the relationship between firm's ownership structure and the co-movement of the stock return with the market return. Four different types of firm ownership, including managerial ownership, state ownership, foreign ownership, and concentrated ownership, are among the main features of the company's governance mechanism and have been separately documemented in the previous research to understand their impact on stock price synchronicity. We constructed the regression model, using stock price synchronicity as the dependent variable and the above four components of ownership structure as explanantory variables. The pooled OLS, the fixed effects model, and the random effects are employed to investigate the outcome of the study. Data used in the reserch are of public firms listed on the Ho Chi Minh City Stock Exchange (HOSE) during the five-year period term from 2015 to 2019. The data sample contains 235 companies from 10 industries with 1135 observations. The results revealed by the fixed effects model, the large ownership and the managerial ownership are found to have adverse effect on the stock price synchronicity, whereas the foreign ownership model is revealed to have positive influence on the stock return co-movement. The effect of the state ownership on the stock price synchronicity is not confirmed.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.31-36
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• 2021

As the global economy stagnated due to the Corona 19 virus from Wuhan, China, most countries, including the US Federal Reserve System, introduced policies to boost the economy by increasing the amount of money. Most of the stock investors tend to invest only by listening to the recommendations of famous YouTubers or acquaintances without analyzing the financial statements of the company, so there is a high possibility of the loss of stock investments. Therefore, in this research, I have used artificial intelligence deep learning techniques developed under the existing automatic trading conditions to analyze and predict macro-indicators that affect stock prices, giving weights on individual stock price predictions through correlations that affect stock prices. In addition, since stock prices react sensitively to real-time stock market news, a more accurate stock price prediction is made by reflecting the weight to the stock price predicted by artificial intelligence through stock market news text mining, providing stock investors with the basis for deciding to make a proper stock investment.

• Asia-Pacific Journal of Business
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• v.11 no.2
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• pp.133-143
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• 2020

Purpose - This study seeks to summarize the tax changes in stock trading and analyze K-OTC stock trading data in 2017 and 2018 to infer the effects of the application of capital gains taxes by individual investors. Design/methodology/approach - This study analyzes the case of the expansion of the 2018 capital gains tax exemption in the K-OTC market, which exempts capital gains tax on the proceeds from the sale of individual investors of certain stocks under the temporary special law. Findings - In the K-OTC market, the amount of transactions has expanded since the capital gains tax exemption in 2018, but the volume of transactions and transaction turnover have decreased. In particular, the result of lower transaction turnover after the expansion is contrary to expectations. To control the macroscopic effects of the stock market, further analyses the transactions of capital gains tax-exempt stocks and non-exempt stocks. The turnover rate of exemption stocks is higher than that of the non-exempt stocks. In the case of transaction turnover, the two results are not consistent. However, the latter result is more meaningful because the comparison of exempt and non-exempt reduces distortion by macro effects. Research implications or Originality - To mitigate the impact of capital gains taxes on stock market, government authorities need to consider the gradual expansion of the scope of taxation, the application of separate taxation in the introduction of capital gains, the reduction tax rate on transfer income of listed shares, and the reduction tax rate on long-term holdings.

• Korea Real Estate Review
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• v.28 no.2
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• pp.21-34
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• 2018

The purpose of this study is to investigate the effect of macro-finance variables on the correlation between the housing and stock markets because understanding the nature of time-varying correlations between different assets has important implications on portfolio allocation and risk management. Thus, we adopted the AG-DCC GARCH model to obtain time-varying, conditional correlations. Our sample ranged from January 2004 to November 2017. Our empirical result showed that the coefficients on asymmetric correlation were significantly positive, implying that correlations between the housing and stock markets were significantly higher when changes in the housing price and stock returns were negative. This finding suggested that the housing market has less hedging potential during a stock market downturn, when such a hedging strategy might be necessary. Based on the regression analysis, we found that the term spread had a significantly negative effect on correlations, while the credit spread had a significantly positive effect. This result could be interpreted by the risk premium effect.

• The Journal of the Korea Contents Association
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• v.7 no.5
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• pp.166-173
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• 2007

This study analyzed the valuation of stock market for marketability of mobile contents. We investigated, during the period of 2002 to 2005, the anormal returns of each firms which announced the launching of new mobile contents. As a result, we found statistically significant average abnormal return(AAR) at launching day of new mobile contents. And the meaningful average cumulative abnormal returns(ACAR) are observed during event period. Which means that the launching announcement of new mobile contents leads to statistically significant positive abnormal returns at stock market. Therefore, we concluded that stock market react immediately to new mobile contents, and which valuate only specific value but also implied value of contents.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.36-46
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• 2019

If stock market is efficient, any well-devised trading rule can't consistently outperform the average stock market returns. This study aims to verify whether the strategy based on bid-ask volume information can beat the stock market. I suggested a day trading strategy using order imbalance indicator and empirically analyzed its profitability with the KOSPI 200 index futures data from 2001 to 2018. Entry rules are as follows: If BSI is over 50%, enter buy order, otherwise enter sell order, assuming that stock price rises after BSI is over 50% and stock price falls after BSI is less than 50%. The empirical results showed that the suggested trading strategy generated very high trading profit, that is, its annual return runs to minimum 71% per annum even after the transaction costs. The profit was generated consistently during 18 years. This study also improved the suggested trading strategy applying the genetic algorithm, which may help the market practitioners who trade the KOSPI 200 index futures.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.9-18
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• 2020

The research paper examines the influence of elections on the stock market. The study analyses whether the market reaction would be the same when a party wins and comes to power for the second consecutive time. The study employs Market Model Event study methodology. The sample period taken for the study is 2014 to 2019. A sample of 31 companies listed in Bombay Stock Exchange is selected at random for the purpose of the study. For the elections held in 2014, an event window of 82 days was taken with 39 days prior to the event and 42 days post event. The event (t0) being the declaration of the election results. For the elections held in 2019 an event window of 83 days was taken with 41 days prior to the event and 41 days post event. The results indicate that the market reacts positively with significantly positive Average Abnormal Returns. The findings of the study reveal that the impact on the market is not the same between any two elections even when the same party comes to power for the second time. The semi-strong form of efficient market hypothesis holds true in the context of emerging markets like India.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.845-853
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• 2021

The stock market shows the current health of an economy, and investment performance represents it. This study aims to clarify the relationship between financial behavior and investment decisions as well as its impact on investment results. Determine the influence of behavioral factors on individual investors' investment decisions and investment performance on the Vietnam stock market. The study surveyed 250 investors. The main analytical methods used are Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). Research results show that Heuristic, Prospect, Market, and Herding directly and positively affect investment decision-making. Besides, the above factors have a direct and positive effect on investment performance. In particular, the Prospect factor has the strongest influence on investment decision-making and investment performance. The major findings of this study suggested that the important role of Heuristic, Prospect, Market, and Herding on Investment Decision-making and Investment Performance. Prospect had the strongest impact on Investment decision-making (β = 0.275). Heuristic had the second strongest impact (β = 0.257), then Herding (β = 0.202), and finally Market (β = 0.189) had the weakest effect. Regarding Investment Performance, the Prospect factor has a higher degree of impact than Heuristic Herding and Market.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.199-226
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• 2009

We examine the intertemporal relation between risk and return in the Korean stock market and foreign exchange market based on the two factor ICAPM framework. The standard GARCH model and the GJR(1993) model are employed to estimate conditional variances of the stock returns and foreign exchange rates. The covariance between the rates of stock returns and changes in the exchange rates are estimated by the constant conditional correlation model of Bollerslev(1990) and the dynamic conditional correlation model of Engle(2002). The multivariate GARCH in mean model and quasi-maximum likelihood estimation method, consequently, are applied to investigate riskreturn relation jointly. We find that the estimated coefficient of relative risk aversion is negative and statistically significant in the post-financial crisis sample period in the Korean stock market. We also show that the expected stock returns are negatively related to the dynamic covariance with foreign exchange rates. Both estimated parameters of conditional variance and covariance in the foreign exchange market, however, are not statistically significant. The GJR model is better than the standard GARCH model to estimate the conditional variances. In addition, the dynamic conditional correlation model has higher explanatory power than the constant correlation model. The empirical results of this study suggest following two points to investors and risk managers in hedging and diversifying strategies for their portfolios in the Korean stock market: first, the variability of foreign exchange rates should be considered, and second, time-varying correlation between stock returns and changes in foreign exchange rates supposed to be considered.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.197-203
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• 2022

The agricultural sector has an important contribution to the economic development of Vietnam in particular and other countries in general. The growth of enterprises in the industry is an important bridge in promoting the economic development of the country. Currently, the policies of the Government of Vietnam always create favorable conditions for enterprises to conduct business, especially enterprises in the agricultural sector. The study aims to assess factors influencing the profitability of listed firms in Vietnam's stock market. Using 40 enterprises in the agricultural industry listed on the Ho Chi Minh City Stock Exchange and the Hanoi Stock Exchange and using advanced econometric modeling, dealing with defects in the regression model, the research results show that large-scale firm has higher economic efficiency than small-scale firm. In addition, a firm with higher use of loan capital is associated with a more efficient firm, reflected in the relatively good debt management ability of enterprises in the agricultural sector. Adversely, growth and age do not have any impact on firm performance. Macroeconomic factors do not impact profitability. Finally, the study has some policy implications for developing agricultural businesses in the case of Vietnam.