• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1162-1173
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• 2016

In this paper, we describe a physicomathematical model of the processes that occur in a sodium circuit with a variable flow cross-section in the case of a water leak into sodium. The application area for this technique includes the possibility of analyzing consequences of this leak as applied to sodium-water steam generators in fast neutron reactors. Hydrodynamic processes that occur in sodium circuits in the event of a water leak are described within the framework of a one-dimensional thermally nonequilibrium three-component gas-liquid flow model (sodium-hydrogen-sodium hydroxide). Consideration is given to the results of a mathematical modeling of experiments involving steam injection into the sodium loop of a circulation test facility. That was done by means of the computer code in which the proposed model had been implemented.

• Korean Security Journal
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• no.34
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• pp.313-336
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• 2013

The purpose of this study is to derive an optimal regression model for occurrences of major crimes on a security company's stock price through identifying precedence of the occurrences of major crimes on the security company's stock price, relationship between the occurrences of major crimes and the security company's stock price. Followings are the results of this study. First, the occurrences of murder crime, robbery crime, rape crime, theft crime move along the security company's monthly stock price simultaneously, and the occurrence of violence crime precedes 6 months to the security company's monthly stock price depending on the results of cross-correlation analysis of precedence of occurrences of major crimes, such as murder crime, robbery crime, rape crime, theft crime, violence crime on the security company's monthly stock price. Second, the explanation of the occurrences of robbery crime, rape crime, theft crime on the security company's monthly stock price is 61.7%($R^2$ = .617) excluding murder crime, violence crime depending on the results of multiple regression analysis(stepwise method) by putting the occurrences of major crimes, such as murder crime, robbery crime, rape crime, theft crime, violence crime into the security company's monthly stock price.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.99-110
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• 2021

This study aims to examine empirically the industry and economic fundamental factors that affect the stock prices of the leading palm oil company in Indonesia. The dynamics of stock price are analyzed using the autoregressive distribution lag (ARDL) model both for symmetric and asymmetric effects. The data used in this study are monthly data for the period from 2008:01 to 2020:03. In the long run, the company stock price moves in line with the competitor company stock price at the current time. The palm oil price has a positive effect on the stock price. Meanwhile, inflation negatively affects the stock price in the short run. The estimated equilibrium correction coefficient indicates a reasonably quick correction of the distortion of the stock price equilibrium in monthly dynamics. However, fundamental factors have asymmetric effects, especially the response of stock price when these factors decrease rather than increase in the short run. Stock prices that are responsive to declines in fundamental performance should be of particular concern to both investors and management in their strategic decision making. The results of this study will contribute to the enrichment of literature related to stock prices from the viewpoint of economic analysis on firm-level data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.154-161
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• 2018

This study conducted to predict the stock market prices based on the assumption that internet news articles might have an impact and effect on the rise and fall of stock market prices. The internet news articles were tested to evaluate the accuracy by comparing predicted values of the actual stock index and the forecasting models of the companies. This paper collected stock news from the internet, and analyzed and identified the relationship with the stock price index. Since the internet news contents consist mainly of unstructured texts, this study used text mining technique and multiple regression analysis technique to analyze news articles. A company H as a representative automobile manufacturing company was selected, and prediction models for the stock price index of company H was presented. Thus two prediction models for forecasting the upturn and decline of H stock index is derived and presented. Among the two prediction models, the error value of the prediction model (1) is low, and so the prediction performance of the model (1) is relatively better than that of the prediction model (2). As the further research, if the contents of this study are supplemented by real artificial intelligent investment decision system and applied to real investment, more practical research results will be able to be developed.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.1005-1015
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• 2020

This paper aims to propose a Comprehensive Decision Support Model to evaluate retail companies' financial performance traded on the Vietnam Stock Exchange Market. The financial performance has been examined in terms of the valuations ratios, profitability ratios, growth rates, liquidity ratios, efficiency ratios, and leverage ratios. The data of twelve companies from the first quarter to the fourth quarter of 2019 and the first quarter of 2020 were employed. The weights of 18 chosen financial ratios are calculated by using the Standard Deviation method (SD). Grey Relational Analysis technique was applied to obtain the final ranking of each company in each quarter. The results showed that leverage ratios have the most significant impact on the retail companies' financial performance and gives some long-term investment recommendations for stakeholders and indicated that the Taseco Air Services Joint Stock Company (AST), Mobile World Investment Corporation (MWG), and Cam Ranh International Airport Services Joint Stock Company (CIA) are three of the top efficient companies. The three of the worst companies are Viglacera Corporation (VGC), Saigon General Service Corporation (SVC), and HocMon Trade Joint Stock Company (HTC). Furthermore, this study suggests that the GRA model could be implemented effectively to ranking companies of other industries in the future research.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.4
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• pp.73-89
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• 2009

Circular shareholdings among three companies are formed when company A owns stock in company B, company B owns stock in company C, and company C owns stock in company A. Since circular shareholdings among large family-controlled firms are used to give the controlling shareholder greater control or more opportunities to expropriate minority investors, the government has encouraged large business groups to gradually remove their circular shareholdings. In this paper, we propose a combinatorial optimization model that can answer the question, which equity investments among complicated investment relationships of one large business group should be removed to resolve its circular shareholdings. To the best knowledge of the authors, our research is the first one that has approached the circular shareholding problem in respect of management science. The proposed combinatorial optimization model are formulated into integer programming problem and applied to some Korean major business groups.

• Convergence Security Journal
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• v.15 no.3_2
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• pp.83-93
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• 2015

In this research, we used KOSPI, KOSDAQ and a stock price of Information Security related Company - S1, Ahnlab, Suprema, Raonscure and Igloosecurity. From August 2010 to July 2014, that is during 208 weeks(4 years), we had grasped index and stock price trend. Also we had attempted various Empirical analysis - Basic statistics of Security related Stock, Analysis of variance, Correlation analysis and Weekly Rate of Rise trends. The first purpose of this research is to see correlation between Security related Company and KOSPI, KOSDAQ. The second purpose of this research is to analyze whether stock items have investment value or not while watching features of flow of stock price per item. We expect possibility and merit of investment when we suppose Security industry's high potential to grow. It seems that Security related Company deserves to be invested. We expect investment for Security related Company that has high possibility of growing will create high yields compared to Market yields.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.885-894
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• 2021

This study aims to analyze the effect of the ratio of profitability and solvability (leverage) on the variable stock price, which is mediated (intervening) by the variable dividend policy. Using the financial reports of manufacturing companies in the consumer goods sector, we take profitability data (ROA, ROE, GPM, and NPM), solvability data (DAR, LTDER, and DER), dividend policy (DPR), and stock price (closing price) from 24 companies, which were selected as samples, from 2011 to 2018. Data was analyzed using the Structural Equation Modeling (SEM) method. The results show that profitability, solvability, and dividend policy affect changes in stock prices, respectively. On the other hand, profitability and solvability do not affect dividend policy. The indirect relationship (intervening) is assessed using a single test, resulting in a dividend policy that can intervene in the relationship between profitability and stock prices but cannot mediate the relationship between solvability and stock prices. The implication of this research is to provide knowledge to investors about the importance of knowing the company's financial performance. Companies with good financial performance will easily develop because there are sufficient funds for company operations. By analyzing financial ratios, investors can get signals to decide whether to invest in the company they want.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.99-108
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• 2023

This study's goal is to investigate the effects of board size, the number of annual board meetings, the profitability of the company, and the audit Committee on the disclosure of climate change in Saudi companies listed on the stock exchange. It was conducted to evaluate affecting some factors on carbon emissions by the regression model. The study uses the content analysis method. Data was collected from the annual and sustainability reports, and the platform database Refinitiv, an LSEG (London Stock Exchange Group Company) for the period 2018 to 2021. The study sample is 51 companies. The study findings showed Saudi Arabia saw its first significant overall drop in CO2 emissions with a 22.61 MtCO2 decline (3.93%) in 2018. The study revealed a positive connection between the size of the director's board, and the disclosure of carbon emissions in Saudi firms listed on the stock market. While other factors are not related to the number of director's board meetings, the audit committee, and the profitability of the company on the disclosure of carbon emissions in the Saudi companies listed on the stock exchange.

• Korean Management Science Review
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• v.28 no.1
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• pp.53-60
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• 2011

Time series analysis methods have been traditionally used in stock price prediction. However, most of the existing methods represent some methodological limitations in reflecting influence from external factors that affect the fluctuation of stock prices, such as oil prices, exchange rates, money interest rates, and the stock price indexes of other countries. To overcome the limitations, we propose a network based method incorporating the relations between the individual company stock prices and the external factors by using a graph-based semi-supervised learning algorithm. For verifying the significance of the proposed method, it was applied to the prediction problems of company stock prices listed in the KOSPI from January 2007 to August 2008.