• The Korean Journal of Financial Management
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• v.23 no.2
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• pp.27-56
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• 2006

This paper analyzes whether corporations which have done capital reduction fulfill the objectives of their capital reduction as planned and also asks how did the capital reduced corporations fare in terms of stock returns, by investigating the capital reduced corporations on the Exchange and the Kosdaq between 2000 and 2004. Most capital reduced companies aim to improve their capital structure. Debt to Equity ratio among financial ratios has improved significantly after capital reduction, yet the profitability of corporations wasn't up to expectations. The analysis of cumulative abnormal returns (CARs) indicates that the CARs were below '0' during whole investigation period. Besides, the CARs of companies listed on the Kosdaq have plummeted to -53.5%. Half of the companies on the Kosdaq in this sample which have reduced their capital to avoid delisting have been eventually delisted after capital reduction. This Study concludes that simple capital reduction without having value-added projects is not beneficial to shareholders.

• Korean Business Review
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• v.17
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• pp.27-52
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• 2004

The miraculous growth of Korean economy and its business corporations during 1960' s and 1970's are mainly due to the government leadership and its market intervention. We can find the reasons why the government initiated economic growth plan was so successful in Korea in its efficient bureaucratic government system and fair discipline to the corporations based on its contribution to the economy. During 1960's, the primary factors for the growth of business entities and the formation of business groups were the financial special favor, the preferential treatment in the new industry entrance and the merge & acquisition, lavish export incentives from the government, and the export explosion to Vietnam. During 1970's, the substantial deduction of corporations' private debt, enormous support in heavy industry investment, special benefits to general trading companies by the government, and the construction export to the Middle-East were the main causes of the business growth and the business groups formation. Also, the economic rent for the big companies had still been effective since 1960's. However, the preferential benefit to the big companies made them to diversify into the unrelated business ares and to be in very vulnerable financial position. The governmental support brought about the monopoly as well.

• The Korean Journal of Financial Management
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• v.27 no.1
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• pp.121-156
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• 2010

Back-door-listing can be viewed both as M&A and an alternative to IPO. If IPO is an access to the capital market through regulations, back-door-listing would be the way of entering the market through trading. Back-door-listing can be a better choice considering the common wisdom that regulations hinder the functioning of free market system. One would, however, prefer IPO, for the informational asymmetry isless severe in case of IPO. This paper examines if IPO is superior to back-door-listing as to the informational efficiency. The excess buy-and-hold returns of the Kosdaq back-door-listing firms are estimated over the three-year-period since the event. They are compared against the excess buy-and-hold returns of the Kosdaq IPO firms over the same period of time. The results confirm this paper's prediction that IPO should be more information-efficient. Both IPO and back-door-listing firms start with high short-term excess returns and end up with long-term under-performance. However, back-door-listing firms show more significantly damaging long-term results. Furthermore, back-door-listing firms record poorer accounting results over the research period. These results imply that there exists fad at the time of both events and, in case of back-door-listing, this fad is reinforced by the possibility of window dressing.

• Korean Journal of Construction Engineering and Management
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• v.19 no.1
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• pp.90-102
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• 2018

In preparation of the increase in the domestic debts and the rise in the US interest rate, the Korean government has started to strengthen the regulation on the property market since 2017. So, it is likely that the sales in the domestic construction market would be decreased. Even in the overseas plant projects market, as there has been the continuous increase in the cost and the resulting increase in the losses, it looks hard for the large construction companies to keep their credit ratings as they are now. This study is designed to check Korean government's property policy and any possible problems caused by the overseas and domestic economic environment, which include the property market policy, interest rate, rise in the property price and lackluster sales in housing market. It showed the change in the credit ratings by finding out the sales, work capability, sales in non-governmental projects, operating profits and PF contingency liabilities. For this study, the questionnaires were sent to 30 practical experts to analyze the effect of the risk factor on the outside credit rating of large construction companies.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.163-175
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• 2016

The purpose of this study is to provide an efficient internal control system formation incentives for company and to confirm empirically usefulness of the internal accounting control system for financial institutions by analyzing whether the internal control vulnerabilities of companies related significantly to the classification and assessment of soundness of financial institutions. Empirical analysis covered KOSPI, KOSDAQ listed companies and unlisted companies with more than 100 billion won of assets which have trading performance with "K" financial institution from 2008 until 2013. Whereas non-internal control vulnerability reporting companies by the internal control of financial reporting received average credit rating of BBB on average, reporting companies received CCC rating. And statistically significantly, non-reporting companies are classified as "normal" and reporting companies are classified as "precautionary loan" when it comes to asset quality classification rating. Therefore, reported information of internal control vulnerability reduced the credibility of the financial data, which causes low credit ratings for companies and suggests financial institutions save additional allowance for asset insolvency prevention and require high interest rates. It is a major contribution of this study that vulnerability reporting of internal control in accordance with the internal control of financial reporting can be used as information significant for the evaluation of financial institutions on corporate soundness.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.173-190
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• 2015

The purpose of this study is to improve bankruptcy prediction models by using a novel hybrid under-sampling approach. Most prior studies have tried to enhance the accuracy of bankruptcy prediction models by improving the classification methods involved. In contrast, we focus on appropriate data preprocessing as a means of enhancing accuracy. In particular, we aim to develop an effective sampling approach for bankruptcy prediction, since most prediction models suffer from class imbalance problems. The approach proposed in this study is a hybrid under-sampling method that combines the k-Reverse Nearest Neighbor (k-RNN) and one-class support vector machine (OCSVM) approaches. k-RNN can effectively eliminate outliers, while OCSVM contributes to the selection of informative training samples from majority class data. To validate our proposed approach, we have applied it to data from H Bank's non-external auditing companies in Korea, and compared the performances of the classifiers with the proposed under-sampling and random sampling data. The empirical results show that the proposed under-sampling approach generally improves the accuracy of classifiers, such as logistic regression, discriminant analysis, decision tree, and support vector machines. They also show that the proposed under-sampling approach reduces the risk of false negative errors, which lead to higher misclassification costs.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.3
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• pp.125-140
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• 2018

According to statistics, it is shown that domestic SMEs rely on bank loans for the majority of fund procurement. From financial information shortage (Thin file) that does not provide information necessary for credit evaluation from banks such as financial statements. In order to overcome these problems, recently, in alternative finance such as P2P, using differentiated information such as demographics, trading information and the like utilizing Fintech instead of existing financial information, small funds A new credit evaluation method has been expanding to provide SMEs with small amounts of money. In this paradigm of environmental change, in this research, credit evaluation which can expand fund supply to SMEs by utilizing big data based on trade area information such as sales fluctuation, location conditions etc. In this research, we try to find such a solution. By analyzing empirically the big data generated in the trade area, we verify the effectiveness as a credit evaluation factor and try to derive the main parameters necessary for the business performance evaluation of the founder of SMEs. In this research, for 17,116 material businesses in Seoul City that operate the service industry from 2009 to February 2018, we collect trade area information generated for each business location from Big Data specialized company NICE Zini Data Co., Ltd.. We collected and analyzed the data on the locations and commercial areas of the facilities that were difficult to obtain from SMEs and analyzed the data that affected the Corporate financial Distress. It is possible to refer to the variable of the existing unused big data and to confirm the possibility of utilizing it for efficient financial support for SMEs, This is to ensure that commercial lenders, even in general commercial banks, are made to be more prominent in one sector of the financing of SMEs. In this research, it is not the traditional financial information about raising fund of SMEs who have basically the problem of information asymmetry, but a trade area analysis variable is derived, and this variable is evaluated by credit evaluation There is differentiation of research in that it verified through analysis of big data from Trading-area whether or not there is an effect on.