• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.103-114
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• 2011

Current series for testing stock market cointegrations tend to be restricted to analyzing the relations between stock market prices and may not be able to understand the whole picture of the variations in the stock market system. The nature of the variations in the stock prices, between the countries that experienced economic crisis and those did not, are different for a certain period of time, and accordingly excluding the potentially important variables in the stock market system causes statistical bias. This study considers domestic foreign exchange markets and financial markets in testing for the cointegrating relations of the stock prices in Korea and major investing countries. The results demonstrate the possibility of specification errors unless those markets are included in the statistical modeling process.

• The Journal of Information Systems
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• v.29 no.3
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• pp.119-144
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• 2020

Purpose Real estate usually takes charge of the highest proportion of physical properties which individual, organizations, and government hold and instability of real estate market affects the economic condition seriously for each economic subject. Consequently, practices for predicting the real estate market have attention for various reasons, such as financial investment, administrative convenience, and wealth management. Additionally, development of machine learning algorithms and computing hardware enhances the expectation for more precise and useful prediction models in real estate market. Design/methodology/approach In response to the demand, this paper aims to provide a framework for forecasting the real estate market with machine learning algorithms. The framework consists of demonstrating the prediction efficiency of each machine learning algorithm, interpreting the interior feature effects of prediction model with a state-of-art algorithm, LIME(Local Interpretable Model-agnostic Explanation), and comparing the results in different cities. Findings This research could not only enhance the academic base for information system and real estate fields, but also resolve information asymmetry on real estate market among economic subjects. This research revealed that macroeconomic indicators, real estate-related indicators, and Google Trends search indexes can predict real-estate prices quite well.

• Current Industrial and Technological Trends in Aerospace
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• v.8 no.1
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• pp.12-22
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• 2010

The great recession which caused by financial crisis made steep rise of oil price and the serious problems of the aircraft industry. High oil price increases operating cost and the recession decreases air traffic. After a period of high book order and delivery from global economic recovery, the aircraft order fell down suddenly. Also the Aircraft price and lease rate deceased and the MRO market is reduced, too. But, the air cargo and passenger increase again since late of 2009. So, it is difficult to predict the market movement, most of the forecasters agreed that the air traffic and aircraft demand will grow gradually in long term with the growth of emerging markets like China, India and Africa. And more efficient, safe and clean aircraft is needed and will need in the market.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.4
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• pp.422-427
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• 2003

The purpose of this study analyzes the effects of M＆A between conglomerate and non-conglomerate corporational with 57 samples of firms during the period from 1990 to 1997 right before IMF. financial crisis. These models employed to measure effects of M＆A in this paper are both market model and market adjusted return model using test of t-statistics. Results of this article show that negative excess returns are observed for non-conglomerate mergers and positive excess gains are exhibited for conglomerate mergers. This implies that conglomerate mergers are more effective than firm specialization in terms of merger effects.

• East Asian Journal of Business Economics (EAJBE)
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• v.8 no.1
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• pp.57-69
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• 2020

Purpose - This study examines what are the asset market fluctuations in Europe and how each economic variable affects major variables, and explore the dynamics of housing and stock market through Greece. The variables under consideration are balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), M3, real rate of interest (IR_REAL) and household credits (LOAN). We investigate the functional and causal relationships between housing and stock market. Research design, data, and methodology - Vector error correction model (VECM) is used to figure out the dynamic relationships among variables. This study also contains the augmented Dickey-Fuller unit root, cointegration, Granger causality test, and impulse response function and variance decomposition analysis by EViews 11.0. Results - The statistical tests show that all variables under consideration have one unit root and there is a longterm equilibrium relationship among variables for Greece. GDP, IR_REAL, M3, STOCK and LOAN can be considered as causal factors to affect real estate market, while GDP, LOAN, M3, BCA and HOUSING can bring direct effects to stock market in Greece. Conclusions - It can be judged that the policy that affects the lending policy of financial institutions may be more effective than the indirect variable such as monetary interest rate.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.39-47
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• 2021

This research aims to confirm if the COVID-19 pandemic has had an impact on existing sectors, and how that affects the Indonesian Stock Exchange (IDX) market returns. The research method used is an event study employing market models in nine sectors of the Exchange with purposive sampling technique, and supported by Ordinary Least Square (OLS) regression. Based on the calculation of abnormal returns in the period of 30 days before up to 30 days after, the financial property, real estate, and construction sector results show a decreased abnormal return value. The infrastructure, utilities, and transportation sectors also show an abnormal return value that tends to be constant, while the abnormal return value increases in other sectors. Judging from the cumulative value of abnormal returns, the most affected sector is financials, followed by the trade, service, and investment sectors. The consumer goods and mining industry sectors are still optimistic, while other sectors show temporary negative sentiment. Overall, the stocks on the Indonesia Stock Exchange (IDX) were affected by the COVID-19 pandemic with a cumulative negative value of the average abnormal return sample. The results using OLS regression also strengthen the relationships between the COVID-19 pandemic, and negative and significant market returns.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.311-324
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• 2021

Investors have increasingly become interested in macroeconomic antecedents in order to better understand the investment environment and estimate the scope of profitable investment in equity markets. This study endeavors to examine the interdependency between the macroeconomic antecedents (international oil price (COP), Domestic gold price (GP), Rupee-dollar exchange rates (ER), Real interest rates (RIR), consumer price indices (CPI)), and the BSE Sensex and Nifty 50 index return. The data is converted into a natural logarithm for keeping it normal as well as for reducing the problem of heteroscedasticity. Monthly time series data from January 1992 to July 2019 is extracted from the Reserve Bank of India database with the application of financial Econometrics. Breusch-Godfrey serial correlation LM test for removal of autocorrelation, Breusch-Pagan-Godfrey test for removal of heteroscedasticity, Cointegration test and VECM test for testing cointegration between macroeconomic factors and market returns,] are employed to fit regression model. The Indian market returns are stable and positive but show intense volatility. When the series is stationary after the first difference, heteroskedasticity and serial correlation are not present. Different forecast accuracy measures point out macroeconomics can forecast future market returns of the Indian stock market. The step-by-step econometric tests show the long-run affiliation among macroeconomic antecedents.

• Journal of Distribution Science
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• v.20 no.9
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• pp.83-95
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• 2022

Purpose: This study aims to explore an ability to time market-wide investor sentiment of mutual fund managers in an emerging market. Research design, data, and methodology: Based on data of Thai mutual fund market over the period of 2000-2019, our sample includes 283 equity funds, consisting of 204 bank-related funds and 79 nonbank-related funds. We perform our regression analyses at the aggregate and portfolio levels. Results: Under the non-normal distribution of return, we find different behaviors between the best- and worst-performing funds in an ability to time market-wide investor sentiment in Thailand, which is dissimilar to the findings in the U.S. Bottom fund managers act as sentiment hedgers, who decrease (increase) an exposure of investment portfolios when the investor sentiment is high (low). Oppositely, top fund managers are likely to chase investor sentiment. Conclusion: We find that only the worst-performing fund managers, especially for bank-related funds are able to time the market-wide investor sentiment. An advantage of gaining information from their bank's clients is a key success. A competition in the mutual fund industry, an ability to predict fundamentals, and financial literacy are possible reasons to explain the main findings found in this study.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.40-40
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• 2009

Construction firms have long sought success in the global construction market through diversifying revenue sources and project portfolios. The volume of international contracts has contributed to firms' sustained growth by mitigating the impact of the domestic market's cyclical nature. In spite of the importance of international construction, the uncertainty and dynamic changes surrounding global construction pose serious threats to global contactors. Over the last decade, the international construction industry has changed drastically in many ways, particularly including financial resource diversity, competition rules for the selection of contractors, and the terms of delivery systems requiring more competent total service providers. This paper investigates the important changes for global contractors through various documentation analysis as well as in-depth interviews with industry experts. This paper then analyzes the common strategies and lessons obtained from the cases of leading global contractors that have sustained their growth in the competitive global construction during the last decade. In addition, the authors further analyzed the comparisons between those firms and Korean contractors to discern any difference in sustaining their growth in the competitive market. It was found that those leading firms were quite proactive and responsive to changing markets by diversifying their market revenues to stabilize their revenue structure and enhancing their competency through a wide range of 'business convergence'. In addition, they significantly increased their upstream/downstream functional capabilities; hence becoming more competent service providers, able to grow in these rapidly changing market conditions. Finally, this paper benchmarks the critical strategies that support growth, which in turn can provide a strategic guideline for expansion into the global construction market.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.187-198
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• 1998

마케팅의 Fundamental\ulcorner 마케팅 : 제품구매와 관련된 소비자의 행위를 연구 마케팅의 역사 : Mass marketing $\longrightarrow$ Market segmentation $\longrightarrow$ Database marketing 소비자 이해와 관리를 위한 다양한 정보와 지식을 제공한다. DBM, Relationship marketing, Frequency marketing, Loyalty marketing, Program customer management, Direct marketing(중략)