• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.113-121
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• 2020

Multi-criteria stock selection is a critical issue for effective investment since the improper stock investment might cause many problems affecting investors negatively. Investors need a range of financial indicators while they are choosing the optimal set of stocks to invest. This study aims to rank the stock of agriculture companies indexed on the Vietnam Stock Exchange Market. The data of 13 agriculture companies during the 2016-2019 periods was analyzed by analytical hierarchy process (AHP) integrated with grey relational analysis (GRA), multi-objective optimization ratio analysis (MOORA), and technique for order performance by similarity to ideal solution (TOPSIS). The AHP method is employed to determine the weights of the proposed financial ratios, and GRA, TOPSIS, and MOORA approaches are used to obtain final ranking. The results indicated that HSL is the top stock with the highest rank and GRA, MOORA, and TOPSIS rankings have strong correlation values between 0.78-1. The findings suggest that the integrated model could be implemented effectively to specific analysis of industries such as oil and gas, textiles, food, and electronics in future research. Further, other techniques like COPRAS, KEMIRA, and EDAS could be employed to evaluate the financial performance of other companies to solve investment problems.

• Journal of the Korea Safety Management & Science
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• v.6 no.2
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• pp.211-229
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• 2004

The basis of cyber trading has been sufficiently developed with innovative advancement of Internet Technology and the tendency of stock market investment has changed from long-term investment, which estimates the value of enterprises, to short-term investment, which focuses on getting short-term stock trading margin. Hence, this research shows a Short-term Stock Price Forecasting System on Learning Agent System using DTA(Decision Tree Algorithm) ; it collects real-time information of interest and favorite issues using Agent Technology through the Internet, and forms a decision tree, and creates a Rule-Base Database. Through this procedure the Short-term Stock Price Forecasting System provides customers with the prediction of the fluctuation of stock prices for each issue in near future and a point of sales and purchases. A Human being has the limitation of analytic ability and so through taking a look into and analyzing the fluctuation of stock prices, the Agent enables man to trace out the external factors of fluctuation of stock market on real-time. Therefore, we can check out the ups and downs of several issues at the same time and figure out the relationship and interrelation among many issues using the Agent. The SPFA (Stock Price Forecasting System) has such basic four phases as Data Collection, Data Processing, Learning, and Forecasting and Feedback.

• Culinary science and hospitality research
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• v.14 no.2
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• pp.115-127
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• 2008

The purpose of this study is to validate the evaluation of stock, which has relation with self-esteem and career for the development of commercial stock. This study conducted a survey of purchasing attitudes & receptiveness in order to hold an accurate course for developing stock. According to the analysis, the results are as follows. It examined the cuisiniers of deluxe hotels who mainly use stock of Seoul and the capital region. A total of 350 samples were distributed and 289 samples were selected for the research. Statistical analysis of collected data executed frequency, percentage, average, reliability analysis, factor analysis using SPSSWIN 12.0 PC package programs. Making stock, cooking skills, cooking methods, quality of food ingredients and cooking recipes are important. Also, sensory characteristics such as color, odor, and taste should be considered. Career and self-esteem act on the purchase accommodation attitude of commercial stock. Commercial stock products more than 1,000 mL or 2,000 mL of liquid styles need packing of vacuum pack(vinyl). Based on the result of this study, we will make efficient use of research data for the development of commercial stock products and we will be able to improve conservation of taste with good quality by making by hand through standardization and mass production of traditional culinary skills.

• Journal of Industrial Technology
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• v.20 no.A
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• pp.219-228
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• 2000

The determination of lot sizes in prevailing inventory problems has been made with constant safety stock over the planning horizon. But, it is more profitable to accommodate the safety stock to dynamically fluctuating demands. The objective of this paper is to study the method to determine the dynamic safety stock and lot sizing rules depending on the actual customer demands. The last period or highly fluctuating period during the consumption of a lot is the most critical one to stock-out. It means that such periods must be given more attentions. Some dynamic methods to control safety stock are proposed with viewpoints of the time, quantity, and time-quantity. Simulation results show that lot sizing methods with dynamic safety stock reduce about 10% of average total cost compared to those with constant safety stock.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.191-203
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• 2012

In the stock market, the investors rely on stock information to trade. Good information may stimulate buying, raising the stock prices and the bad information may result in selling, decreasing the stock prices. In terms of the relationship between information and stock prices, stock prices can be viewed as reaction of investors to all the information flowing into the market. The significant increase of web stock news volume is often associated with the significant changes of stock prices. When the web stock news volume for a firm increases significantly, the stock price movement is often oscillatory. This paper attempts to investigate the relationship between volumes of information from Korean web IT and stock prices in Korean stock market. This research shows that when the web stock news volume increases significantly, volatility, trading volumes and rate of returns are increase too. The results of the study provide us with the new clues to the microstructure of the stock market from the perspective of the web news.

• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.113-118
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• 2019

This study analyzed how interdependence between China, Hong Kong, Taiwan and Singapore stock markets changed after the implementation of Shanghai-Hong Kong Stock Connect system using the EGARCH-GED model that allow simultaneous analysis of return and variability. Since the implementation of this system, the interdependence of Taiwan stock market with the Greater China stock markets has been weakened, and the interdependence of Singapore's stock market with the Greater China stock markets has not been exist. On the other hand, he interdependence between China and Hong Kong stock markets has been shown to be significantly enhanced since the implementation of this system. This is appears to be the result of improved conditions for Chinese and Hong Kong investors to invest in the two stock markets following the implementation of this system. Thus, considering the portfolio investment in the Greater China stock markets, the investors will need to develop their investment strategies in light of these facts that the weakening interdependence of the Taiwan and Singapore securities markets and the strengthening interdependence of the Chinese and Hong Kong securities markets.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.399-407
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• 2021

Stock movement is difficult to predict because it has dynamic characteristics and is influenced by many factors. Even so, there are some approaches to predict stock price movements, namely technical analysis, fundamental analysis, and sentiment analysis. Many researches have tried to predict stock price movement by utilizing these analysis techniques. However, the results obtained are varied and inconsistent depending on the variables and object used. This is because stock price movement is influenced by a variety of factors, and it is likely that those studies did not cover all of them. One of which is that no research considers the use of fundamental analysis in terms of currency exchange rates and the use of foreign stock price index movement related to the technical analysis. This research aims to predict stock price movements in Indonesia based on sentiment analysis, technical analysis, and fundamental analysis using Support Vector Machine. The result obtained has a prediction accuracy rate of 65,33% on an average. The inclusion of currency exchange rate and foreign stock price index movement as a predictor in this research which can increase average prediction accuracy rate by 11.78% compared to the prediction without using these two variables which only results in average prediction accuracy rate of 53.55%.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.173-183
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• 2022

The objective of this research is to examine the influence of the COVID-19 pandemic on stock markets in a few developing and developed countries. This study uses daily data from January 2020 to May 2021 and obtained from World Health Organization and Thomson Reuters. The secondary data was evaluated through panel econometric methodology that includes different unit root tests, and to analyze the long-run relationship between variables, panel cointegration techniques were applied. The long-run causality among variables was examined through Panel Vector Error Correction Model. The overall findings of this study suggest a long-run association exists between several cases and death with the stock returns of the GCC and other stock markets. Furthermore, the VECM model also identified a long-run causality running from COVID cases and death towards the stock rerun of both sets of stock markets. However, a subsequent Wald test yielded mixed results, indicating no short-run causality between cases and deaths and stock returns in both groups; however, in the case of GCC, several COVID-19 cases are having a causal impact on stock markets, which is notable in light of the fact that the death rate in GCC is significantly lower than in many developed and developing countries.

• Journal of Information Technology Applications and Management
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• v.9 no.4
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• pp.65-78
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• 2002

We propose a new application method of the datamining technique that might help building an efficient trade strategy in the stock market, where the analysis of the huge database is essential. The proposed method utilizes the association rules among the price changes of individual stock from the market basket analysis (a datamining technique typically used in the Marketing field) in building the strategy We also apply the proposed method to the daily stock prices in Korean stock market, from Jan. 2000 to Dec. 2001. The application results show that the proposed method gives an significantly higher yield rate than the actual stock chage rate.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.807-814
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• 2021

As economic activities decrease, and the stock market decline due to COVID-19, many people are jumping into stock investment as an alternative source of income. As people's interest increases, many stock price analysis studies are underway to earn more profits. Due to the variance observed in the stock markets, it is necessary to analyze each stock independently and consistently. To solve this problem, we designed and implemented models and services that analyze stock prices using a reinforcement learning technique called Asynchronous Advantage Actor-Critic(A3C). Stock market data reflected external factors such as government bonds and KOSPI (Korea Composite Stock Price Index) as well as stock prices. Our proposed work provides a web service with a visual representation of predictions of stocks and stock information through which directions are given to investors to make safe investments without analyzing domestic and foreign stock market trends.