• Journal of the Korea Society of Computer and Information
• /
• 제28권8호
• /
• pp.67-75
• /
• 2023

Stock price prediction is an important topic extensively discussed in the financial market, but it is considered a challenging subject due to numerous factors that can influence it. In this research, performance was compared and analyzed by applying time series prediction models (LSTM, GRU) and non-time series prediction models (RF, SVR, KNN, LGBM) that do not take into account the temporal dependence of data into stock price prediction. In addition, various data such as stock price data, technical indicators, financial statements indicators, buy sell indicators, short selling, and foreign indicators were combined to find optimal predictors and analyze major factors affecting stock price prediction by industry. Through the hyperparameter optimization process, the process of improving the prediction performance for each algorithm was also conducted to analyze the factors affecting the performance. As a result of feature selection and hyperparameter optimization, it was found that the forecast accuracy of the time series prediction algorithm GRU and LSTM+GRU was the highest.

• Land and Housing Review
• /
• 제14권3호
• /
• pp.1-15
• /
• 2023

Using youth panel data, this study attempted to diagnose the effect of residential characteristics (housing type and housing type) and various household background variables on the implementation of youth NEET (Not in Employment, Education or Training), and to suggest appropriate policy directions. As a result of the analysis, it was found that young individuals residing in unfavorable living conditions such as those who rent on a monthly basis or live in multi-household, villa, or officetel settings, had a higher likelihood of transitioning to NEET. Those who received financial support from their parents were more likely to transition to NEET. Therefore, comprehensive youth NEET support policies such as customized housing and job policies according to the characteristics of NEET should be established. In particular, even though they have reached adulthood, it is shown that the likelihood of becoming NEET is very high for youth who live together with their parents without being economically independent or who receive financial assistance from their parents. In order to mitigate and prevent these young people from NEET transition, transitioning from school to the labor market should be facilitated with policy support.

• Health Policy and Management
• /
• 제33권1호
• /
• pp.55-64
• /
• 2023

Background: Despite the various activities of the regional public hospitals, discussions are being made as to whether or not to continue due to the issue of financial deficit. Therefore, the main factors affecting the fiscal deficit were analyzed with 10-year data. Methods: This study is a panel analysis that analyzed the characteristics of 34 regional public hospitals and influencing factors on medical benefits for 10 years from 2010 to 2019. First, we analyze the determinants of medically vulnerable areas set by the government, analyze the trend of medical profit per 100 beds and medical profit rate from 2010 to 2019, and identify the factors that affect them. Results: Differences in medical profit per 100 beds and medical profit-to-medical profit rate were caused by market share representing regional characteristics, and both indicators improved as the number of outpatients increased. The important influencing variables are the number of doctors and nurses, and both indicators improve when there are specialists, but medical benefits decrease as the number of doctors increases when judged by the number of people per 100 beds. In addition, the number of nurses per 100 beds does not contribute to medical profit and has a negative effect on the medical profit ratio. Conclusion: As only regional characteristics were taken into account for medically vulnerable areas, operational characteristics need to be considered. The greatest impact on the finances of local medical centers is the proper staffing of doctors and nurses, and their efficient arrangement is the most important factor in financial stability.

• Korea Journal of Hospital Management
• /
• 제28권1호
• /
• pp.37-51
• /
• 2023

Purposes: There exist many non-covered services that the National Health Insurance does not cover, and thus, their prices are set by individual health care providers. However, little study has been done to investigate how hospitals set prices for those services. The purpose of this study is to examine the relationship between ownership, profitability, and prices of those services for a sample of general hospitals. Methodology/Approach: Data regarding the prices of major non-covered services (e.g., upper-level hospital room fees, MRI, Da 7inci robot surgery, and LASIK) were obtained from the Health Insurance Review and Assessment Service and the financial information, as well as other characteristics, were derived from the financial reports from the Korea Health Industry Development Institute. Descriptive statistics, t-tests, and multiple linear regression analyses were used to test the relationship between the independent variables and the dependent variables. Findings: Hospitals owned by private universities appeared to have higher prices for non-covered services while regional public hospitals tend to have lower prices. Profitability, measured by operating margin, was not significantly related to the prices. Hospitals that charge higher prices were more likely to be located in the capital area (Seoul, Incheon, and Gyeonggi), and to employ larger number of personnel. Practical Implications: Public hospitals tend to charge lower prices for non-covered services. Relative market power appears to be related to pricing. Further research is needed to investigate whether such a relationship varies over time and its effects on the quality and access.

• Journal of Digital Convergence
• /
• 제20권3호
• /
• pp.131-143
• /
• 2022

Focusing on FinTech keywords, this study is analyzing newspaper articles and Twitter data by using text mining methodology in order to understand trends in the industry of domestic digital financial service. In the growth of FinTech lifecycle, the frequency analysis has been performed by four important points: Mobile Payment Service, Internet Primary Bank, Data 3 Act, MyData Businesses. Utilizing frequency analysis, which combines the keywords 'China', 'USA', and 'Future' with the 'FinTech', has been predicting the FinTech industry regarding of the current and future position. Next, sentiment analysis was conducted on Twitter to quantify consumers' expectations and concerns about FinTech services. Therefore, this study is able to share meaningful perspective in that it presented strategic directions that the government and companies can use to understanding future FinTech market by combining frequency analysis and sentiment analysis.

• Asia-Pacific Journal of Business
• /
• 제14권1호
• /
• pp.149-169
• /
• 2023

Purpose - The main purpose of this study is to develop the stress test model for Korean banks by exploring the optimal Monte Carlo simulation and BIS forecasting model. Design/methodology/approach - This study selects 15 Korean banks as sample financial firms and collects relevant 76 quarterly data for the period between year 2000 and 2018 from KRX(Korea Excange), Bank of Korea, and FnGuide. The Regression analysis, Unit-root test, and Monte Carlo simulation are hired to analyze the data. Findings - First, most of the sample banks failed to keep 8% BIS ratio for the adverse and severely Adverse Scenarios, implying that Korean banks must make every effort to realize better BIS ratios under adverse market conditions. Second, we suggest the better Monte Carlo simulation model for the Korean banks by finding that the more appropriate volatility should be different depending on variables rather than simple two-sigma which has been used in the previous studies. Third, we find that the stepwise regression model is better fitted than simple regression model in forecasting macro-economic variables for the BIS variables. Fourth, we find that, for the more robust and significant statistical results in designing stress tests, Korean banks are required to construct more valid time-series and cross-sectional data-base. Research implications or Originality - The above results all together show that the optimal volatility in designing optimal Monte Carlo simulation varies depending on the country, and many Korean banks fail to pass sress test under the adverse and severely adverse scenarios, implying that Korean banks need to make improvement in the BIS ratio.

• The Korean Journal of Franchise Management
• /
• 제2권1호
• /
• pp.152-172
• /
• 2011

This study aims to analyze the effect of franchisor's pre-open support services on franchisee's relationship quality and performance in foodservice franchise system. The analysis data was collected from 500 franchisees located in Seoul and Gyeonggi-do of Republic of Korea. The finding are as followings: firstly, the factors of information providing, market researching, interior and equipment supporting, education and training supporting, sale and promotion supporting, and legal supporting influence positively franchisee's satisfaction. Second, regarding relationship among relationship quality, satisfaction positively influences trust and commitment, and trust positively influence commitment. Third, relationship quality influences positively both financial and non-financial performance.

• Korea Trade Review
• /
• 제47권5호
• /
• pp.289-304
• /
• 2022

Korea's LNG and crude oil are the most important energy and export raw materials, but 100% import resources by overseas. However, tanker shipping companies, which play the most crucial role in energy cargo security, are very small in number and size, which can be a factor in the supply chain crisis. Therefore, this paper studied the policy of expanding tanker transportation necessary for the transport of crude oil and LNG in Korea. In the existing literature, there was no policy study necessary for tanker ships, but referring only to the importance of overseas energy development and transportation, so we tried to derive various demands necessary for expanding the tanker fleet through expert interviews and AHP which was conducted on 89 related energy institutions to derive policies and their priorities. The results of the study are as follows. As for the policy, the financial support policy was the highest priority, followed by the business and the mutual cooperation policy of related agencies. Tax support (22.6%) and ship financing (19.4%) were the highest priorities, followed by the Energy Intermediate Promotion Act (11.9%), Tanker Guarantee Insurance (10.6%), Energy Budget Independence (9.3%), and Korea Trader Development (8.2%). Energy governance (6.3%), information center establishment (6.2%), and energy procurement committee (5.5%) ranked seventh, eighth, and ninth. The research results show that it is necessary to supply sufficient ships to the market through the expansion of ship finance for tankers and to follow business support policies such as guarantee insurance. In addition, it was also possible to derive that the financial resources need to be determined by law and independent budgets for consistency and continuity.

• Asia-Pacific Journal of Business
• /
• 제15권1호
• /
• pp.209-223
• /
• 2024

Purpose - This article analyzes the impact of macroeconomic variables of the United States, China, and Korea on KOSPI and VKOSPI, in that United States and China have a great influence on Korea, having an export-driven economy. Design/methodology/approach - The influence of US, China, and Korea interest rates, industrial production index, consumer price index, US employment index, Chinese real estate index, and Korea's foreign exchange reserves on KOSPI and VKOSPI is analyzed on monthly basis from Jan 2012 to Aug 2023, using multifactor model. Findings - The KOSPI showed a positive relationship with the U.S. industrial production index and Korea's foreign exchange reserves, and a negative relationship with the U.S. employment index and Chinese real estate index. The VKOSPI showed a positive relationship with the Chinese consumer price index, and a negative relationship with the U.S. interest rates, and Korean foreign exchange reserves. Next, dividing the analysis into two periods with the Covid crisis and the analysis by country, the impact of US macroeconomic variables on KOSPI was greater than Chinese ones and the impact of Chinese macroeconomic variables on VKOSPI was greater than US ones. The result of the forward predictive failure test confirmed that it was appropriate to divide the period into two periods with economic event, the Covid Crisis. After the Covid crisis, the impact of macroeconomic variables on KOSPI and VKOSPI increased. This reflects the financial market co-movements due to governments' policy coordination and central bank liquidity supply to overcome the crisis in the pandemic situation. Research implications or Originality - This study is meaningful in that it analyzed the effects of macroeconomic variables on KOSPI and VKOSPI simultaneously. In addition, the leverage effect can also be confirmed through the relationship between macroeconomic variables and KOSPI and VKOSPI. This article examined the fundamental changes in the Korean and global financial markets following the shock of Corona by applying this research model before and after Covid crisis.

• Journal of the Korea Society of Computer and Information
• /
• 제29권5호
• /
• pp.11-20
• /
• 2024

This study presents TabNet, a novel deep learning method, to enhance corporate credit rating accuracy amidst growing financial market uncertainties due to technological advancements. By analyzing data from major Korean stock markets, the research constructs a credit rating prediction model using TabNet. Comparing it with traditional machine learning, TabNet proves superior, achieving a Precision of 0.884 and an F1 score of 0.895. It notably reduces misclassification of high-risk companies as low-risk, emphasizing its potential as a vital tool for financial institutions in credit risk management and decision-making.