• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1099-1106
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• 2006

This study is an analysis of the stock trading value in terms of investor types in the Korean stock market for recent 12 years. We examined the characteristics in stock trading value variation according to each investor type and the interactive relationship in the trading value between types of investors. The results show that the trading value scale of every investor type increases overall while the proportion of the trading value by each investor type in the market exhibits variation. In addition, a statistically significant interactive relationship in the trading value between types of investors exists: the correlations are formed differently before and after events which largely influence the stock market.

• East Asian Economic Review
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• v.21 no.2
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• pp.147-165
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• 2017

This study quantifies the dynamic interrelationship between the KOSPI index return and search query data derived from the Naver DataLab. The empirical estimation using a bivariate GARCH model reveals that negative contemporaneous correlations between the stock return and the search frequency prevail during the sample period. Meanwhile, the search frequency has a negative association with the one-week- ahead stock return but not vice versa. In addition to identifying dynamic correlations, the paper also aims to serve as a test bed in which the existence of profitable trading strategies based on big data is explored. Specifically, the strategy interpreting the heightened investor attention as a negative signal for future returns appears to have been superior to the benchmark strategy in terms of the expected utility over wealth. This paper also demonstrates that the big data-based option trading strategy might be able to beat the market under certain conditions. These results highlight the possibility of big data as a potential source-which has been left largely untapped-for establishing profitable trading strategies as well as developing insights on stock market dynamics.

• IE interfaces
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• v.15 no.4
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• pp.409-425
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• 2002

This case study provides a market analysis methodology for overseas markets by applying statistical tools and the Six Sigma approach. The study suggests a procedure with seven steps to improve brands position in the market. These steps consist of interviewing consumers and floor salesmen of stores, surveying, analysis of correlation between brand position and customers satisfaction, analysis of relationship with companies and customer satisfaction factors, analysis of the customer satisfaction gap between companies, evaluating the importance of customer satisfaction factors, and suggestion for enhancement of brand position. The Six Sigma approach such as "Define", "Measure" and "Analyze" is used in this procedure, which is part of Six Sigma procedure, D-M-A-I-C (Define, Measure, Analyze, Improve, Control). Minitab and SAS are used for the statistical analysis.

• Communications for Statistical Applications and Methods
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• v.21 no.5
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• pp.445-459
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• 2014

This paper investigates the dependence structure of Korean financial markets (stock, foreign exchange (FX) rates and bond) using copula-GARCH and dynamic conditional correlation (DCC) models. We examine GJR-GARCH with skewed elliptical distributions and four copulas (Gaussian, Student's t, Clayton and Gumbel) to model dependence among returns, and then employ DCC model to describe system-wide correlation dynamics. We analyze the daily returns of KOSPI, FX (WON/USD) and KRX bond index (Gross Price Index) from $2^{nd}$ May 2006 to $30^{th}$ June 2014 with 2,063 observations. Empirical result shows that there is significant asymmetry and fat-tail of individual return, and strong tail-dependence among returns, especially between KOSPI and FX returns, during the 2008 Global Financial Crisis period. Focused only on recent 30 months, we find that the correlation between stock and bond markets shows dramatic increase, and system-wide correlation wanders around zero, which possibly indicates market tranquility from a systemic perspective.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.535-545
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• 2019

If the real estate auction market indicators are relevant and meaningful, they can be meaningful information to the real estate market in connection with general real estate. The purpose of this study is to examine whether time-supply logic is applied in auction market by identifying time series correlations for the number of auctions, the auction rate, and the auction price rate, which are major indicators of real estate auction market. The real estate types were classified into three categories: residential real estate, land, and commercial real estate. The monthly time series of auctions in the metropolitan real estate were compiled for 96 months. Based on this data, the auction market model for each type was established and the mutual influences between the indicators were analyzed. As a result, the supply and demand indicators, the number of auctions and the auction rate, showed the nature of supply and demand according to the supply and demand logic of the market. However, the correlation was high for residential real estate and relatively low for commercial real estate. the auction rate has a long-term impact on price indicators, especially residential real estate, which is quantitatively explanatory and significant. The three auction-related indicators differ in degree, but there is a correlation, especially for residential real estate, which can be useful information for policy making.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.27-34
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• 2014

In this paper, we investigate the statistical correlation of the time series for temperature measured at the heat box in the automobile drying process. We show, in terms of the sample variance, that a significant non-linear correlation exists in the time series that consist of absolute temperature changes. To investigate further the non-linear correlation, we utilize the volatility, an important concept in the financial market, and induce volatility time series from absolute temperature changes. We analyze the time series of volatilities in terms of the de-trended fluctuation analysis (DFA), a method especially suitable for testing the long-range correlation of non-stationary data, from the correlation perspective. We uncover that the volatility exhibits a long-range correlation regardless of the window size. We also analyze the cross correlation between two (inlet and outlet) volatility time series to characterize any correlation between the two, and disclose the dependence of the correlation strength on the time lag. These results can contribute as important factors to the modeling of forecasting and management of the heat box's temperature.

• Convergence Security Journal
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• v.19 no.4
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• pp.165-171
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• 2019

The domestic information security market is booming, For the development of the information security industry. I wanted to suggest a strategy for finding and developing a good business model. So the main products were classified by similar industries. And The sector was selected as the dependent variable. Expert interviews were conducted and classified according to technical maturity. Independent variables were sales, number of employees, and performance. Average analysis result, sales amounted to 8.798 billion won, 13.51 years in industry, and 64.3 employees. As a result of SPSS statistical analysis, the correlation between industry type and sales according to technical maturity (r = -.729) was within 5% of significance level. The regression results were significant. (p= .047<0.05) Therefore, industry classification and sales are related to technological maturity.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.817-825
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• 2020

Over the last few decades, corporate frauds have highlighted the significance of corporate governance in deriving firm performance. By using different sample data, extensive research has examined how corporate governance structure influences firm's profitability, but limited research was undertaken on the banking sector of Pakistan. This research adds to the literature by testing how board structure derives bank's performance by using sample data of 19 banks for the period from 2010 to 2017. In addition, the study analyzes the controlling part of size on the link between board governance and bank performance. Findings reveal that banks having small board size, fewer non-executive directors and minimum activity level perform better. Analysis related to bank size illustrates that board size has value in increasing benefits in large size banks in contrast to small size one, while higher participation by board members enhances performance of small size banks more. The correlation results and findings showed that there existed no multicollinearity issue between independent variables. Board size showed positive correlation with the market variable, while board activity tended to correlated negatively with the market performance. Inverse correlation between board size and independent directors indicated that Pakistani banks with greater board size had fewer independent directors.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.465-471
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• 2021

The study investigates the dynamic correlation of cryptocurrencies and equity in Vietnam and tests the safe-haven property of them from the perspective of the stock market in Vietnam during the pandemic crisis by applying the dynamic conditional correlation (DCC) GARCH model and regression with a dummy variable, respectively. This study employs time series data on the daily dataset from September 2014 to September 2021 with the focus on the two most popular cryptocurrencies - Bitcoin and Litecoin. The results show that the dynamic conditional correlations between cryptocurrencies and equity in Vietnam increased during the pandemic, however, in most periods, positive dynamic correlations often dominate. Besides, the regression results also indicate that Bitcoin and Litecoin act as weak safe-haven investments for stocks in Vietnam during the COVID-19 turmoil. They are more suitable for diversification purposes although the dynamic correlations between them and the stock index in Vietnam vary stronger during the pandemic crisis than before. The findings of this study suggest that in the period of pandemic crisis, cryptocurrencies are not concerned as effective safe-haven assets for stock in Vietnam. Instead, cryptocurrencies are only playing a potential role in diversification benefit in this economy.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.1
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• pp.47-56
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• 2019

As the zero interest rate era was over with the end of quantitative easing, the economy of several global markets observed the fluctuations of the base interest rate. Interest rate, which is the change of money value with respect to time, is negatively correlated with construction investment. Considering the characteristics of interest rates and construction investment as economic variables, the necessity of cross-border analysis between base interest rate and construction investment was suggested in this paper. Cross-correlation analysis between base interest rates and construction investment crossing the border was performed. The effective correlations were confirmed with values varying by countries. Similar characteristics were also observed among countries with similar economy, which were then divided into three groups. Additionally, identifying the base interest rate that affects the construction investment of a particular country was made possible by reflecting a self-cycle of base interest rates. Lastly, from the result of examining the influence of each rise and fall of the interest rate, it was verified that the difference was more than twice as large in some countries. These results are expected to contribute to construction-related policy makers or investors to make decisions in response to the economic status of the construction market.