• Journal of Digital Convergence
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• v.19 no.6
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• pp.133-141
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• 2021

Governments of each country are actively implementing fiscal expansion policies to recover the real economy after Corona 19. In Korea, the stock market and housing market are greatly affected as liquidity in the market increases due to the implementation of disaster subsidies and welfare policies. The purpose of this study is to analyze the relationship between stock market and housing market trends and liquidity. Data were collected by the Bank of Korea and Kookmin Bank. The analysis period is from January 2000 to December 2020, and monthly data are used. For empirical analysis, the rate of change from the same month of the previous year was calculated for each variable, and numerical analysis, index analysis, and model analysis were performed. As a result of the analysis, it was found that the stock index showed a positive(+) relationship with the house price, while a negative(-) relationship with M2. Previous studies have suggested that, in general, an increase in liquidity affects the stock market and the housing market, and inflation also rises. In this study, it was found that the stock market and the housing market had an effect on each other. However, it was investigated that liquidity showed an inverse relationship with the stock market and had no relationship with the housing market. Through this, this study estimated that there is a time difference in the relationship between liquidity and the stock market & housing market.

• The Journal of Information Systems
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• v.30 no.3
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• pp.21-45
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• 2021

Purpose This paper analyzed the impacts of domestic stock market by a global pandemic such as COVID-19. We investigated how the overall pattern of the stock market changed due to the impact of the COVID-19 pandemic. In particular, we analyzed in depth the pattern of stock price, as well, tried to find what factors affect on stock market index(KOSPI) in the healthcare industry due to the COVID-19 pandemic. Design/methodology/approach We built a data warehouse from the databases in various industrial and economic fields to analyze the changes in the KOSPI due to COVID-19, particularly, the changes in the healthcare industry centered on bio-medicine. We collected daily stock price data of the KOSPI centered on the KOSPI-200 about two years before and one year after the outbreak of COVID-19. In addition, we also collected various news related to COVID-19 from the stock market by applying text mining techniques. We designed four experimental data sets to develop decision tree-based prediction models. Findings All prediction models from the four data sets showed the significant predictive power with explainable decision tree models. In addition, we derived significant 10 to 14 decision rules for each prediction model. The experimental results showed that the decision rules were enough to explain the domestic healthcare stock market patterns for before and after COVID-19.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.431-444
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• 2023

Purpose - This study applies the traditional Structure-Conduct-Performance (SCP) model from industrial organization theory to investigate the relationship between market structure and performance in China's banking industry. Design/methodology/approach - For analysis, financial data from the People's Bank of China's "China Financial Stability Report" and financial reports of 6 state-owned banks and 11 joint-stock banks for the period 2010 to 2021 were collected to create a balanced panel dataset. The study employs panel fixed-effects regression analysis to assess the impact of changes in market structure and ownership structure on performance variables including return on asset, profitability, costs, and non-performing loan ratios. Findings - Empirical findings highlight significant differences in the effects of market structure between state-owned and joint-stock banks. Notably, increased market competition positively correlates with higher profits for state-owned banks and with lower costs for joint-stock banks. Research implications or Originality - State-owned banks demonstrate larger scale and stability, yet they struggle to respond effectively to market shifts. Conversely, joint-stock banks face challenges in raising profitability against competitive pressures. Additionally, the study emphasizes the importance for Chinese banks to strengthen risk management due to the increase of non-performing loans with competition. The results provide insights into reform policies for Chinese banks regarding the involvement of private sector in the context of market liberalization process in China.

• Proceedings of the KAIS Fall Conference
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• 2011.05b
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• pp.792-795
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• 2011

After the year of 2000, compositions of stock holders in domestic firms are rapidly changing. In domestic stock market, the proportion of market value held by foreign investors reaches over 40%. There are several blue chip companies among those where foreign investors hold more than 50% of the stocks. There are still hot debates going on about whether the increase in the number of foreign investors contributes to domestic companies. This research attempted to determine foreign ownership increases enhance firm value empirically. It has been shown that foreign ownership variable has significant positive impact on Tobin's Q of firm value variable. The result suggests that foreign ownership increases in domestic corporations positively contribute to firm value, as they monitor and keep the management transparent as an institutional investor, and they work to soothe agency problems by the managements or the large stock holders.

• Korean Business Review
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• v.16
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• pp.43-60
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• 2003

There are several stylized facts concerning stock return volatility. First, it is persistent, so an increase in current volatility lasts for many periods. Second, stock volatility increases after stock prices fall. Third, stock volatility is related to macroeconomic volatility, recessions, and banking crises. On the other hand, there are many competing parametric models to represent conditional heteroskedasticity of stock returns. For this article, I adopt the strategy followed by French, Schwert, and Stambaugh(1987) and Schwert(l989, 1990). The models in this article provide a more structured analysis of the time-series properties of stock market volatility. Briefly, these models remove autoregressive and seasonal effects from daily returns to estimate unexpected returns. Then the absolute values of the unexpected returns are used in an autoregressive model to predict stock volatility.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.123-129
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• 2013

The aim of this study is to design an intelligent pattern-based real-time trading system (PRTS) using rough set analysis of technical indicators, dynamic time warping (DTW), and genetic algorithm in stock futures market. Rough set is well known as a data-mining tool for extracting trading rules from huge data sets such as real-time data sets, and a technical indicator is used for the construction of the data sets. To measure similarity of patterns, DTW is used over a given period. Through an empirical study, we identify the ideal performances that were profitable in various market conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.7
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• pp.2930-2936
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• 2012

This paper examines the effects of corporate ownership structure variables on stock returns. The dependent variables identified in this paper include the equity ratio of large shareholders, institutional investors and foreign investors, and the control variables are firm size, book-to-market ratio, and earning-to-price ratio and leverage. This paper finds that the results of regressions say that institutional investors and foreign investors, firm size, book-to-market ratio and earning-to-price ratio can explain the differences in stock returns using panel data.

• The Journal of Industrial Distribution & Business
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• v.4 no.2
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• pp.13-19
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• 2013

Purpose - The paper tested the relationship between the stock markets of the Middle East and the USA with the oil price and US dollar index as threshold variables. Research design, data, and methodology - The stock price indices of the USA, the Middle East (Abu Dhabi, Jordan), WTI spot crude oil price, and US dollar index were daily returns in the research period from May 21, 2001 to August 9, 2012. Following Hansen (1999), the panel threshold regression model was used. Results - With the US dollar index as the threshold variable, a negative relationship existed between the stock price indices of Jordan and the USA but no significant result was found between the stock price indices of Abu Dhabi and the USA. Conclusions - The USA is an economic power today:even if it has a closer relationship with the US stock market, the dynamic US economy can learn about subsequent developments and plan in advance. Conversely, if it has an estranged relationship with the US stock market, thinking in a different direction and different investment strategies will achieve good results.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• The Journal of Industrial Distribution & Business
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• v.12 no.3
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• pp.43-49
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• 2021

Purpose: This study attempted to examine the risk of stock price plunge according to the firm's management strategy. Prospector firms value innovation and have high uncertainties due to rapid growth. There is a possibility of lowering the quality of financial reporting in order to meet market expectations while withstanding the uncertainty of the results. In addition, managers of prospector firms enter into compensation contracts based on stock prices, thus creating an incentive to withhold negative information disclosure to the market. Prospector firms' information opacity and delays in disclosure of negative information are likely to cause a sharp decline in share prices in the future. Research design, data and methodology: This study performed logistic analysis of KOSPI listed firms from 2014 to 2017. The independent variable is the strategic index, and is calculated by considering the six characteristics (R&D investment, efficiency, growth potential, marketing, organizational stability, capital intensity) of the firm. The higher the total score, the more it is a firm that takes a prospector strategy, and the lower the total score, the more it is a firm that pursues a defender strategy. In the case of the dependent variable, a value of 1 was assigned when there was a week that experienced a sharp decline in stock prices, and 0 when it was not. Results: It was found that the more firms adopting the prospector strategy, the higher the risk of a sharp decline in the stock price. This is interpreted as the reason that firms pursuing a prospector strategy do not disclose negative information by being conscious of market investors while carrying out venture projects. In other words, compensation contracts based on uncertainty in the outcome of prospector firms and stock prices increase the opacity of information and are likely to cause a sharp decline in share prices. Conclusions: This study's analysis of the impact of management strategy on the stock price plunge suggests that investors need to consider the strategy that firms take in allocating resources. Firms need to be cautious in examining the impact of a particular strategy on the capital markets and implementing that strategy.