• Journal of Korea Trade
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• v.26 no.1
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• pp.99-112
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• 2022

Purpose - This paper empirically investigates via a spatial lag model from the perspective of space economy to find the influencing factors of South Korea's OFDI along with 60 countries. Design/methodology - In the study of regional economic phenomena, we must first test the corresponding spatial correlation, and on this basis, complete the construction of the spatial model. For the target research object, after testing the spatial correlation, if there is spatial correlation, a spatial measurement model is needed. This paper uses the global Moran's I index for calculation. Based on the characteristics and research needs of the research object, this paper selects the spatial lag model to verify the existence of the spatial effect and factors affecting OFDI. Findings - Our results show that export scale, infrastructure, technology level, political stability, resource endowment, market size, distance and labor cost have a certain impact on Korea's OFDI, but at present the distance and market size factors are the most important influencing factors for South Korea's OFDI, The technical level and political stability have little effect on South Korea's OFDI, and are not main factors determining South Korea's OFDI. Originality/value - Through spatial measurement verification, it was found that the spatial effect has a significant impact on OFDI, along with more than 60 countries. On this basis, relevant suggestions are put forward, which have strong practical significance for South Korea's OFDI to achieve healthy and sustainable development.

• The Journal of Industrial Distribution & Business
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• v.10 no.4
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• pp.33-41
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• 2019

Purpose - This study investigates the effect of strategic orientation on market performance with emphasis on the mediative role of innovation capability, economic value and relational value in food producer companies. Research design, data, and methodology - In this descriptive study, a population of 244 managers and employees of Food industry companies in Tehran were investigated. The respondents filled a questionnaire on strategic orientation, innovation capability, economic value, relational value and market performance, during January to August 2018. Reliability and validity were evaluated by Cronbach's alpha coefficient and confirmatory factor analysis. To analyze the data, Spearman's correlation coefficient and structural equation modeling were used by SmartPLS software. Results - Effects of competitor's orientation and technology orientation on all three intermediary variables were positive and significant. The effect of customer orientation on innovation and economic value was positive and significant, but the effect of customer orientation on the value of the relationship was insignificant. Furthermore, entrepreneurial orientation has a positive and significant effect on innovation capability. The effects of three mediator variables on market performance are positive and significant. Conclusions - As the relationship between the mediator variables and market performance were positive and significant, companies should have a comprehensive plan of focus on strengthening these variables.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.582-586
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• 2004

The purpose of this study is to examine the lead-lag relationship between volatility and returns in high frequency stock market data to see the validity of two hypotheses that explain volatility asymmetry. Specifically, wavelet analysis is applied to decompose the volatility process into permanent and transitory components and then each component is investigated in conjunction with returns. The results from cross-correlation analysis between volatility and returns support the leverage effect hypothesis rather than the volatility feedback hypothesis in all cases.

• Journal of the Korea Convergence Society
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• v.7 no.4
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• pp.9-17
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• 2016

This study is to analyze korea credit card market and the China credit card market, and predict future economic activity by developing the Algorithm for future economic trend Estimation As a results, there is no significant correlation between personal income growth and the credit card usage amount, and significant correlation between the credit card per capita and the credit card usage amount, in korea. there is significant correlation between personal income growth and the credit card usage amount, and between the credit card per capita and the credit card usage amount in china. it could be predicted that the china credit card market would be increased and the rate of increase would be gradually increased over the next five years, under the condition without constraints in the external environment.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.4
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• pp.35-52
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• 2013

Markowitz's portfolio selection model is used to construct an optimal portfolio which has minimum variance, while satisfying a minimum required expected return. The model uses estimators based on analysis of historical data to estimate the returns, standard deviations, and correlation coefficients of individual stocks being considered for investment. However, due to the inaccuracies involved in estimations, the true optimality of a portfolio constructed using the model is questionable. To investigate the effect of estimation inaccuracy on actual portfolio performance, we study the changes in a portfolio's realized return and standard deviation as the accuracy of the estimations for each stock's return, standard deviation, and correlation coefficient is increased. Furthermore, we empirically analyze the portfolio's performance by comparing it with the performance of active mutual funds that are being traded in the Korean stock market and the KOSPI benchmark index, in terms of portfolio returns, standard deviations of returns, and Sharpe ratios. Our results suggest that, among the three input parameters, the accuracy of the estimated returns of individual stocks has the largest effect on performance, while the accuracy of the estimates of the standard deviation of each stock's returns and the correlation coefficient between different stocks have smaller effects. In addition, it is shown that even a small increase in the accuracy of the estimated return of individual stocks improves the portfolio's performance substantially, suggesting that Markowitz's model can be more effectively applied in real-life investments with just an incremental effort to increase estimation accuracy.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.45-59
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• 2014

Real estate has been the most preferable investment asset since 1980's has begun. Especially the ups and downs of housing price influence significantly on the household and national economy for a digital economy. In this analysis, monthly movement of apartment price of Seoul and its correlation with KOSPI, construction concerned shares, securities concerned shares, interest rate and exchange rate for 320 months(from January, 1987 to August, 2013) are shown. From the analysis, correlation coefficient of the price of apartment in Seoul and KOSPI is 0.8566 which is highly positive while the price of apartment in Seoul and interest rate are shown strong negative correlation which is -0.7846. The rise of stock market does affect the rise of the price of apartments in Seoul, on the contrary, the price goes down when the interest rate goes up.

• Journal of Korea Port Economic Association
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• v.27 no.3
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• pp.41-64
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• 2011

This article investigates the interrelationships in daily returns using fractionally integrated error correction term and volatilities using constant conditional correlation and dynamic conditional correlation GARCH with asymmetries between Capesize and Panamax markets. Our findings are as follows. First, for the fractionally cointegrated error correction model, there is a unidirectional relationship in returns from the Panamax market to the Capesize market, but a bidirectional causal relationship prevails for the traditional error correction models. Second, the coefficients for the error correction term are all statistically significant. Of particular interest are the signs of the estimates for the error correction term, which are all negative for the Capesize return equation and all positive for the Panamax return. Third, there are bidirectional volatility spillovers between both markets and the direction of the information flow seems to be stronger from Panamax to Capesize. Fourth, the coefficients for the asymmetric term are all significantly positive in the Capesize market, but the Panamax market does not have a significant effect. However, the coefficients for the asymmetric term are all significant, implying that the leverage effect does exist in the Capesize and Panamax markets.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.127-150
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• 2003

This study analyzes how capital market comovement can affect investors' decision making. We first analyze time-varying correlation coefficient between stock indices of U.S.A. and Korea. and then, using our empirical results, attempt to draw implications on investors' behavior. We find that the tendency of comovement between Korea and U.S.A. equity returns has considerably increased after the financial crisis of late 1997. Through the analysis of investors' behavior, we find that foreign investors, contrary to ITC's (Investment Trust Company) and individual investors, buy more shares in Korean markets as American stock prices go up. Foreign investors employ dynamic hedging strategy and give more weight on global economic factors than domestic ones. Our empirical results as a whole imply that investment behavior of foreign investors is most closely related to comovement of U.S.A. and Korea capital markets.

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.104-111
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• 2011

In this study, I have tried to analyze an influence of R&D investment on ROV(Real Option Value), corporate value and market value by analyzing R&D investment, ROV, corporate value and market value of machine and material industry in the perspective of ex post. As a result of this study, corporate value, which has been deduced by real option according to R&D investment, reflects market value well and possesses a strong correlation with R&D investment, ROV, corporate value and market value. This implication demonstrates this study result is corresponding with existing theories.