• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.483-494
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• 2013

The importance of financial risk management has been highlighted after several recent incidences of global financial crisis. One of the issues in financial risk management is how to measure the risk; currently, the most widely used risk measure is the Value at Risk(VaR). We can consider to estimate VaR using extreme value theory if the financial data have heavy tails as the recent market trend. In this paper, we study estimations of VaR using Peaks over Threshold(POT), which is a common method of modeling fat-tailed data using extreme value theory. To use POT, we first estimate parameters of the Generalized Pareto Distribution(GPD). Here, we compare three different methods of estimating parameters of GPD by comparing the performance of the estimated VaR based on KOSPI 5 minute-data. In addition, we simulate data from normal inverse Gaussian distributions and examine two parameter estimation methods of GPD. We find that the recent methods of parameter estimation of GPD work better than the maximum likelihood estimation when the kurtosis of the return distribution of KOSPI is very high and the simulation experiment shows similar results.

• Korean journal of communication and information
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• v.56
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• pp.48-70
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• 2011

Although many researchers propose that market-driven journalism is incurred by the worsening of financial situation as a result of intensifying competition in mass media industry, few studies investigated this claim with actual news data. This study analyzed the headline news of eight major newspapers and two terrestrial TV companies to find the weakening of 'orientating-journalism' function of Korean news media. The results revealed that the duplication rate of news items among ten news companies were decreasing, and the range of news subjects were broadened into diverse topics during last ten years. Therefore it seemed that the tendency of monopolization of a certain events or issues was weakening in news reporting. The financial situation of news companies is an important factor in explaining the change of news reporting. The companies with more worse financial situation have higher duplication rate of news topics along as the more amount of soft news items, leading to the gradual deterioration of their own voices in reporting. The rate of 'independent issue report' was also less than seven precent, thus their reporting is evaluated as having many limitations. In sum, the major newspapers and network broadcasting companies are still exerting strong influences in agenda-setting, but they(mostly newspapers) are suffering from the financial problems, resulting the deterioration of performing orientation journalism function. This study concluded with remarks about the role of major news media in current changing situation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.614-623
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• 2017

The purpose of this study is to analyze the impact of the financial performance of regional public hospitals on their efficiency. In addition, the analysis of their efficiency using environmental factors, such as the market share, operating mode, and size of the regional public hospitals, as well as the factors influencing their efficiency, are selected by selecting the input and output factors of the hospitals and some differences were found between them. The DEA index and financial performance of the 31 regional public hospitals were calculated for the three years from 2012 to 2014. ANOVA and hierarchical regression analysis were used. As a result, there was a significant difference in their efficiency according to the environmental factors, such as the city scale of the regional public hospital, the number of hospital beds, and their business performance, productivity, and publicness. The medical profit margin (p<0.05), labor cost investment efficiency (p<0.05) and HHI (p<0.05) were found to affect the efficiency. In order to identify the inefficiencies of the regional public hospitals and increase their efficiency, it is necessary to measure the efficiency of the input resources and to reduce their cost. In addition, if the regional public hospitals were to provide specialized services, such as specialized functions of medical care that would give them a competitive advantage over private hospitals, their operational efficiency would be enhanced and they would be able to fulfill their role as public medical institutions.

• Korean Journal of Construction Engineering and Management
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• v.21 no.5
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• pp.64-73
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• 2020

The government announced a plan for fund support to the enterprises with high possibility of recovery and early restructuring for the enterprises with low recovery by objectifying credit assessment system. Such announcement of government could be extended to restructuring risk of middle standing enterprises with low financial soundness by establishing the basis to prepare prompt restructuring by reinforcing the basis for restructuring through capital market. This research analyzed financial soundness based on the financial evaluation of bank by selecting 10 middle standing construction companies which focused on housing business in 2019, based on such analysis result, it was confirmed that there was a high possibility of restructuring risk. This research determined that there would be a decrease in growth rate of construction industry on the whole in 2020 due to fall of economic growth rate and reinforced real estate regulation, accordingly, there's a big possibility for middle standing construction companies with paid-in capital ratio due to its low possibility of maintenance of stable credit rating. This research established KCSI assessment model by utilizing the material of a reliable research institute in order for middle standing construction companies to evade restructuring risk, and indicated risk ratio differentiated per each item through a working-level expert survey. Such research result could suggest credit risk reduction method to middle standing construction company management staffs, and prepare a basis to evade restructuring risk.

• Journal of Convergence for Information Technology
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• v.9 no.11
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• pp.92-102
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• 2019

This study analyzed the effect of technology innovation capacity and social capital on the non-financial performance of SMEs in the metropolitan area. Technology innovation capacity is defined as R & D capacity and technology accumulation capacity, and social capital is defined as interaction, goal sharing, and member trust. The samples were collected through a survey conducted in-person and through telephone calls, e-mail, and fax. The sample data used for analysis was 223 copies. Analysis results showed that R & D capacity and technology accumulation capacity (for technology innovation capacity) and interaction and member trust (for social capital) were variables that significantly affect non-financial performance, but not goal sharing. The findings of this study were as follows. First, despite lacking sufficient technology or capital, SMEs are constantly engaging in innovation to survive in the competitive market environment. Second, the members of SMEs make considerable efforts to achieve performance based on interaction and member trust, however, they hold a negative perception toward sharing the goals pursued by their company.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.379-389
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• 2019

The study empirically investigates financial factors that may influence on corporate R&D intensity during the post-era of the global financial turmoil (from 2010 to 2015) to mitigate possible spillover effect associated with the crisis. Concerning the empirical research settings of the study, chaebol firms listed in the KOSPI stock market are used as sample data with adopting various econometric estimation methods to enhance validity of the results. In the first hypothesis test, it is found that there exist inter-industry financial differences in terms of the ratio of R&D expenditure across all the sample years, but the statistical differences may arise from only a few domestic industries beloning to the high-growth sector. Moreover, it is also interesting to identify that, for the high-tech sector, 3 explanatory variables such as R&D intensity in a prior year, firm size and change in cash holdings are proved to be financial factors to discriminate between chaebol firms and their counterparts of non-chaebol firms, whereas a proportion of tangible assets over total assets as well as the former two variables are shown to be significant factors on the R&D intensity for the low-tech sector.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.73-78
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• 2019

Recently, there is a need to introduce a Korean-style restriction sandbox system that exempts or suspends existing regulations so that new products or services based on new technologies can be commercialized without restrictions. In response, the government reorganized the relevant statutes to promptly check regulations centering on four fields, including industrial convergence, ICT, FinTech, and regional innovation growth, and to allow experimental, proof and market releases by setting certain conditions(zone, period, scale, etc.). However, despite the same regulatory sandbox application, depending on the nature of the field applied, differences in application subject, whether application of regulatory specifics, system of push ahead decision-making and whether support of financial and taxation are shown. This research is intended to present efficient operation measures for successful settling of Korean-style regulation sandboxes by comparing and analyzing, centering on the Industrial Fusion Promotion Act in the Industrial Convergence Field, ICT field's Information and Communication Convergence Act, FinTech field's Financial Innovation Act and Regional Special Zone Act in the Regional Innovation and Growth Sector.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.492-497
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• 2020

Today, banks around the world are making great efforts to adapt to the rapidly changing internal and external environment changes caused by the development of IT technology and to gain a competitive advantage in the market. In particular, in line with the rapid growth of smartphone usage, financial services are also provided in a variety of ways using Fintech, and one of the fastest growing areas is mobile simple payment. Mobile payment service is a financial service that pays the purchase price using a portable mobile device. As fintech, a convergence of financial services and information technology, it is recently used not only in financial services, but also in various industries. It is used in all fields where payment functions such as distribution are available. In the case of mobile cards, it shows that the usage rate of people in their 20s and 30s is increasing very much, so it can be said that the use of mobile payment services will continue to increase in the coming future. We know that simple payments are being used. However, it can be said that the research on the use of mobile payment services by these teenagers is somewhat incomplete. Therefore, this study investigated what factors are important for Korean teenagers to use mobile payment services. As a result, among the five hypotheses presented in this study, all hypotheses were adopted except for , which states that cash usage habits have no effect on innovation.