• The Journal of Asian Finance, Economics and Business
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• 제6권3호
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• pp.131-140
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• 2019

The study aims to examine the impact of productivity in addition to the policy of increasing the foreign investors' ownership rate on the performance of businesses which were listed on Vietnam's stock exchange market from 2010 to 2017. With the database of 3.961 observations, the study employs a statistical method - multiple regression to estimate the relationship between labor productivity, foreign ownership as well as other firm-level characteristics and firm performance. Research findings show that increasing labor productivity and increasing foreign ownership rates help increase firm performance. In addition, except for financial leverage, variables such as liquidity and firm size have positive effects on firm performance measured by Tobin's Q. These findings have theoretical contributions and practical implications for managers, investors and government in Vietnam. Managers should pay attention to improving labor productivity through employing incentive mechanisms, building a good working environment, investing in technology, etc. in order to enhance the firm performance. Investors could utilize the labor productivity and foreign ownership indicators to select stocks of good companies for investment. For Vietnamese government, relaxing the limit of foreign ownership and accelerating the divesting of State capital in State-owned enterprises could help increase the investment scale of foreign investors and resulting in positive effects on the firm performance.

• Journal of the Korea Society of Computer and Information
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• 제4권4호
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• pp.244-250
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• 1999

This study aimed to analyze the effect of the change in CP class of a firm on the abnormal yield of its stock price. As a result, it was found that the change in CP class of a firm had an effect on the abnormal yield. That is. the abnormal yield rose when the class of CP rose while it dropped when the class of CP dropped. And it was analyzed that the class of CP in the firm in which its current net gain was great while it dropped in the firm in which the current net gain was small. And it was found that the CP class of the firm with the high debt to equity ratio rose when the CP class of the firm changed, whereas it rose in the firm with the low debt to equity ratio. But it was found that the size of majority shareholders equity rate in a firm, the size of corporate value of the firm, the size of cash flow of the firm and the size of the burden of financial costs of the firm were not related to the abnormal yield of its stock price. This study has its significance in analyzing the effect of the information on the change in CP class of the firm on the capital market. But it has its limitations in the sample firm and the selection of the point in time of disclosure.

• The KIPS Transactions:PartB
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• 제11B권2호
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• pp.207-212
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• 2004

This paper presents a reinforcement learning framework for stock trading systems. Trading system parameters are optimized by Q-learning algorithm and neural networks are adopted for value approximation. In this framework, cooperative multiple agents are used to efficiently integrate global trend prediction and local trading strategy for obtaining better trading performance. Agents Communicate With Others Sharing training episodes and learned policies, while keeping the overall scheme of conventional Q-learning. Experimental results on KOSPI 200 show that a trading system based on the proposed framework outperforms the market average and makes appreciable profits. Furthermore, in view of risk management, the system is superior to a system trained by supervised learning.

• Journal of Distribution Science
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• 제21권5호
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• pp.11-18
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• 2023

Purpose: The purpose of this article is to determine whether there are differences in the level of return and risk of the conventional and Islamic capital markets. Research design, data and methodology: This study takes data on the Jakarta Islamic Index (JII) and the Liquid-45 (LQ45) stock groups in the 2017 to 2020 period. The research approach used is quantitative research with a type of comparison. The data used secondary data sourced from the closing price of shares on the Indonesia Stock Exchange. The statistical method used to test the hypothesis is a different test or independent sample t-test. Results: There is a significant difference between the rate of return and investment risk in JII and LQ-45. The rate of return and risk of investing in LQ-45 is higher than that of JII. Conclusions: There is a significant difference in the rate of return on investment in Jakarta Islamic Index (JII) and LQ-45, including conventional stock Liquid-45 (LQ-45) is higher than the rate of return on shares of JII shares. There is a significant difference in the level of investment risk in the Jakarta Islamic Index (JII) and the Liquid-45 (LQ-45), where the risk level for the LQ-45 is higher than that of the JII shares.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제5권6호
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• pp.580-587
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• 2004

The purpose of this study is to examine if the trading volume can apply to the short-term forecasting of the futures price change by verificating the casuality between trading volume and futures price in the KOSPI 200 futures market. The outcome of the research is summarized as follows. In the analysis of subordinate periods, based on the yearly time segments, trading volume were found to lead futures price. As for trading volume, it was under comparably greater influence of its self of the past than the return rate of futures. In the analysis of subordinate periods, based on the trend of the futures market, trading volume lead return rate of futures feebly in a bull market. But return rate of futures lead trading volume significantly in a bearish market.

• Environmental and Resource Economics Review
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• 제27권4호
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• pp.667-694
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• 2018

We analyze the learning-by-doing effects of the allowance pricing system on the Korea's emission trading scheme. The price of allowance (Korean Allowance Unit) is influenced differently by internal market factors and economic conditions variables in the first (January 2015 to June 2016 ) and the second commitment year(January 2016 to June 2017). The prices and transaction volumes of complementary credits (KCU and KOC) as well as economic conditions variables (such as call rate, exchange rate, stock price) are statistically significant only for the second commitment year. Thus, the learning-by-doing effect makes the market participation decision on K-ETS market more efficient in the second commitment year, adopting the previous experience and knowledge in the K-ETS market. The factors estimated significantly in both commitment periods include the institutional binary variable for requiring the submission of the emissions verification reports issued both on February and March.

• Journal of Intelligence and Information Systems
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• 제26권3호
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• pp.1-36
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• 2020

This study is to reveal the acceptance factors of the Market Sentiment Index (MSI) created by reflecting the investor sentiment extracted by processing unstructured big data. The research model was established by exploring exogenous variables based on the rational behavior theory and applying the Technology Acceptance Model (TAM). The acceptance of MSI provided to investors in the stock market was found to be influenced by the exogenous variables presented in this study. The results of causal analysis are as follows. First, self-efficacy, investment opportunities, Innovativeness, and perceived cost significantly affect perceived ease of use. Second, Diversity of services and perceived benefits have a statistically significant impact on perceived usefulness. Third, Perceived ease of use and perceived usefulness have a statistically significant effect on attitude to use. Fourth, Attitude to use statistically significantly influences the intention to use, and the investment opportunities as an independent variable affects the intention to use. Fifth, the intention to use statistically significantly affects the final dependent variable, the intention to use continuously. The mediating effect between the independent and dependent variables of the research model is as follows. First, The indirect effect on the causal route from diversity of services to continuous use intention was 0.1491, which was statistically significant at the significance level of 1%. Second, The indirect effect on the causal route from perceived benefit to continuous use intention was 0.1281, which was statistically significant at the significance level of 1%. The results of the multi-group analysis are as follows. First, for groups with and without stock investment experience, multi-group analysis was not possible because the measurement uniformity between the two groups was not secured. Second, the analysis result of the difference in the effect of independent variables of male and female groups on the intention to use continuously, where measurement uniformity was secured between the two groups, In the causal route from usage attitude to usage intention, women are higher than men. And in the causal route from use intention to continuous use intention, males were very high and showed statistically significant difference at significance level 5%.

• Journal of Distribution Science
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• 제17권12호
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• pp.5-12
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• 2019

Purpose - In this paper, we examine the effect of accrual earnings management and real earnings management on the corporate value of retail corporations. Research design, data, and Methodology - The sample cover firms whose settlement is December among retail companies listed on the Korea Stock Exchange's securities market and KOSDAQ market from 2001 to 2016. Of these, the targets were companies with operating profit and equity capital of zero or higher and with sales data. The secondary data was collected through KIS-VALUE data base. The Jones model and the modified Jones model were used for the calculating the accrual-based earnings management and the real earnings management. Result - According to the empirical results, the relationship between accrual earnings management, real earnings management and firm value is positively significant in the retail industry as in manufacturing industry. These results are also significant when controlling the size, profitability, investment, debt ratio, dividend, and growth potential of a company. Conclusions - The characteristics of the distribution business can be identified and the influence of the various kinds of earnings management, which is being researched around the manufacturing industry, can be studied in the distribution industry to give practical implications to investors.

• The Journal of Asian Finance, Economics and Business
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• 제9권3호
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• pp.217-227
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• 2022

Predicting return and volatility in the global Capital Market during a pandemic is challenging, and it is more difficult for a specific sector, particularly if that sector has a positive outlook. The goal of this research is to look at the impact of COVID-19 on the mean and volatility of the Information Technology Indexes of the best nine technology-driven countries based on return performance using an econometric GARCH model that is widely used. The daily returns of information technology indexes are evaluated for the same from November 2018 to February 2021. Data is taken from Yahoo Finance for CAC Tech (France), DAX Tech (Germany), FTSE All Tech (UK), KOPSI 200 IT (Korea), NIFTY IT (India), S&P 500 IT (US), S&P TSX (Canada), SSE_IT (China) and TOPIX17 (Japan). The results show daily positive mean returns for 8 countries' IT Indices and further, an uptrend in mean daily returns is observed in the crisis period for 6 countries' IT Indices. The exogenous variable COVID-19 which was taken as a regressor for the GARCH model was found to be positively significant for IT indices of all the countries. The overall results confirm the presence of the mean-reverting phenomenon for IT indices of all the countries.

• Information Systems Review
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• 제22권4호
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• pp.21-39
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• 2020

Recently, deep learning has shown high performance in various applications such as pattern analysis and image classification. Especially known as a difficult task in the field of machine learning research, stock market forecasting is an area where the effectiveness of deep learning techniques is being verified by many researchers. This study proposed a deep learning Convolutional Neural Network (CNN) model to predict the direction of stock prices. We then used the feature selection method to improve the performance of the model. We compared the performance of machine learning classifiers against CNN. The classifiers used in this study are as follows: Logistic Regression, Decision Tree, Neural Network, Support Vector Machine, Adaboost, Bagging, and Random Forest. The results of this study confirmed that the CNN showed higher performancecompared with other classifiers in the case of feature selection. The results show that the CNN model effectively predicted the stock price direction by analyzing the embedded values of the financial data