• Journal of the Economic Geographical Society of Korea
• /
• v.20 no.3
• /
• pp.329-352
• /
• 2017

Since the late 2000s Korean foreign direct investors in North Korea and China border regions have gone through the closure of outward processing trade(OPT) networks and changes in their location due to UN security council resolution and Korean independent sanctions against North Korea's nuclear and missile tests. However, the introduction of new Chinese OPT policy has led to the invigoration of domestic market-based OPT networks towards North Korea. The main aim of this paper is to identify the exceptional characteristics of Dandong in Liaoning province, a North Korea and China border region by analyzing OPT networks towards North Korea. Fundamentally the establishment of OPT networks towards North Korea is likely to be based on the utilization of a plenty of low wages in North Korea. The main reasons for this are fallen into two perspectives: geo-economics and geo-politics. The first perspective is geo-economics centering on the consolidation of economic exchange between North Korea and China, and North Korean economic development. For example, the introduction of Chinese OPT in border region has enabled Chinese local firms based on domestic market to access a plenty of low wage in North Korea in formal and institutional contexts. The second is geo-politics for the stability of North Korean regime based on the means of geo-economics. As the invigoration of domestic market-based OPT networks might make North Korea possible promoting foreign money earning, it enable North Korea to be sustainable as a buffering region between capitalist and socialist regime for China. It shows Chinese geo-strategic attempts to deal with the economic and regime stability of North Korean as a buffering state. In other words, OPT networks in North Korea should be concerned with the discourse practice of geo-economics and geo-politics which might lead to various and contingent spatial economies in border region. As a consequence, North Korea and China border regions could defined as a space in which is applicable to exceptional institutions and policies, and an exploitative space in which create surplus and rents by utilizing a plenty of low wages in North Korea through OPT networks.

• Journal of Venture Innovation
• /
• v.2 no.2
• /
• pp.95-115
• /
• 2019

In the context of today's business environment, not only is the nation or company's credit rating considered very important in our recent society, but it is also becoming important in international transactions. Likewise, at this point of time when the importance and reliability of credit evaluation are becoming important at home and abroad, this study analyzes financial ratios related to corporate profitability, safety, activity, financial growth, and profit growth to study the impact of financial indicators on enterprise value and corporate taxes on credit evaluation. To proceed with this, the financial ratio of 465 companies of KOSPI securities listed in 2017 was calculated and the impact of enterprise value and corporate taxes on credit evaluation was analyzed. Especially, this further study tried to derive a reliable and consistent conclusion by analyzing the financial data of KOSPI securities listed companies for eight years from 2011, which is the first year of K-IFRS introduction, to 2018. Research has shown that the significance levels among variables that show the profitability, safety, activity, financial growth, and profit growth of each financial ratio were significant at the 99% level, except for the profit growth. Validation of the research hypothesis found that while the profitability of KOSPI-listed companies significantly affects corporate value and income tax, indicators such as safety ratio and growth ratio do not significantly affect corporate value and income tax. Activity ratio resulted in significant effects on the value of enterprise value but not significant impacts on income taxes. In addition, it was found that the enterprise value has a significant effect on the company's credit and corporate income taxes, and that corporate income taxes also have a significant effect on the corporate credit evaluation, and this also shows that there is a mediating function of corporate tax. And as a result of further study, when looking at the financial ratio for eight years from 2011 to 2018, it was found that two variables, KARA and LTAX, are significant at a 1% significant level to KISC, whereas LEVE variables is not significant to KISC. The limitation of this study is that credit rating score and financial score cannot be said to be reliable indicators that investors in the capital market can normally obtain, compared to ranking criteria for corporate bonds or corporate bills directly related to capital procurement costs of enterprise. Above all, it is necessary to develop credit rating score and financial score reflecting financial indicators such as business cash flow or net assets market value and non-financial indicators such as industry growth potential or production efficiency.

• Journal of Venture Innovation
• /
• v.1 no.1
• /
• pp.83-98
• /
• 2018

This paper makes a theoretical approach to the differences between transaction tax and capital gains tax when the financial instruments are traded and imposed taxes in K-OTC market, a newly emerging off-board market. Since it is difficult to reduce risk to the level which investors would like to pursue - depending on the taxation methods of portfolio-composed financial instruments - when it comes to forming a synthetic bond to hedge risk, this paper also seeks for effective taxation methods to make this applicable. First of all, to thoroughly review the taxation balance of synthetic bonds, this paper analyzed the effects of the transaction tax and capital gains tax imposed upon synthetic bonds according to the changes in final stock price and strike price in K-OTC market, and analyzed after-tax profit differences among them depending on whether income tax deduction took place or not. As a result of the research upon the tax gap in transaction tax and capital gains tax according to the changes of final stock prices, it was shown that imposing transaction tax is more likely to be effective for some level of risk hedging with replicating portfolio considering taxation policies and financial markets, since the effect of the transaction tax has a much lower tax gap than that of capital gains tax. In addition, in relation to whether income tax deduction was permitted or not, it was proved that the effect of the transaction tax and the capital gains tax vary depending on the variation in the strike price. Above all, it was shown that if the strike price is lower than the stock price, the transaction tax will be less affected by the existence of income tax deduction than the capital gains tax, while both will be equally affected by the existence of income tax deduction if the strike price is higher than the stock price. Further study would be to demonstrate the validation of this in the K-OTC market with actual financial instruments and, also, to seek for a more systematic hedging method by using a ratio analysis approach to the calculation of the option transaction tax

• Journal of Venture Innovation
• /
• v.1 no.1
• /
• pp.49-65
• /
• 2018

For a long time the German economy was primarily defined by large corporations and thriving small and medium-sized enterprises. Since about 2005 a second strand has started to emerge and it is one which is becoming increasingly important and is creating jobs - start-ups in the digital sector. This start-up activity is taking an important role in Germany's economic development: Start-up companies spawn innovations and create jobs, thus promoting the concept of competition. In general "start-up" refers to digitally-driven companies that are not more than five years old. Germany's start-up policy consists of three main parts. First of all, Germany has the characteristics of technology-based start-ups. The Hartz reform since 2002 has shown its focus on technology-based start-ups. In particular, it is the most appropriate for a start-up company to take the role of a new technology company to respond to changes in the global industrial structure. Second, it is approaching from a long-term perspective. In this regard, the small business policy, including Germany's new business policy, is seen as a tradition that can be consistent and can make policy decisions based on the basics rather than following the times. Third, the government is implementing policies centered on demand. Germany's start-up policy is summarized as a technology-based policy and new job creation. The policy response is that the government seeks the best combination of policies by adapting them to the times from the broad trend of employment market policies. What is important here is that policies are made based on consumers, not suppliers, in the process of policy making and implementation. With the Digital Agenda 2020 the Federal government has likewise committed itself to preparing the digital economy for international competition and making Germany the "No. 1 digital growth country in Europe". Ever since 1998 the Federal Ministry for Economic Affairs and Energy (BMWi) has awarded the "EXIST" start-up scholarship to students and graduates. The Ministry also invests in the High Tech start-up fund. Together with Kreditanstalt für Wiederaufbau (KfW) and 18 other investors from the world of business the seed investor promotes young technology companies. Germany offers start-ups a good infrastructure and lots of funding opportunities. Berlin is regarded as Europe's start-up capital and also attracts lots of international young entrepreneurs.

• The Korean Journal of Financial Management
• /
• v.23 no.2
• /
• pp.109-141
• /
• 2006

The central factor in the pecking order theory of financial structure is the asymmetric distribution of information between managers and less-informed outside investors. Myers and Majluf (1984) show that this asymmetry leads managers to prefer internal funds to external funds. Funds are raised through equity issues only after the capacity to issue debt has been exhausted. In contrast, according to static tradeoff theory, an optimum financial structure exists by the tradeoff between tax saving by debt and bankruptcy costs. This study examines the recent changes of Korean firms' financial structure and financing behavior and the determinants of financial structure. The sample of firms comes from the period of $1996{\sim}2004$, and the number of firms is 32,003. The major findings are as follows. First, in contrast with previous studies using US firms as sample, Korean firms have been using debt financing as their major financing instrument. Especially, the firms in the fund deficit situation relies much more on $long{\sim}term$ and $short{\sim}term$ debts rather than on equity issues. Second, as is the case with previous studies using US firms sample indicates, the financing deficit variable can not explain perfectly the net debt issue. However, compared with net equity issue variable, net debt issue variable is more closely related to the financing deficit variable. Third, when financing deficit variable is added to the current list of explanatory variables of financial structure determinants model, it has a significant and positive explanatory power. In addition, the coefficients of determinants are much improved. Thus, it is concluded that although pecking order theory is not perfect, it appears to be more useful compared to static tradeoff theory, at least in explaining the recent financing behavior of Korean manufacturing firms.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.12 no.1
• /
• pp.1-13
• /
• 2017

The purpose of this study is to find out which factors determine the success of start-up in the initial market and what are the most important determinants. For the empirical analysis, the questionnaire related to the analysis of success factors for start-up success was designed according to the quantitative analysis (AHP technique). First, we selected 8 representative success factors for successful start-up in the initial market. In order to determine the degree of priority among these factors, we surveyed 12 entrepreneurs who are interested in entrepreneurship, universities, research institutes, and public officials. As a result of the empirical analysis, 51% of the funds in the tier 1 were ranked as the top priority to determine success factors. Followed by research and development (32.5%), management (8.7%) and marketing (7.8%). In particular, when each of the four items is calculated as 100 according to the result of the tier 1, and the tier 2 is converted, the foreign investment is analyzed as 43.7%. It was followed by 15.14% of R & D facilities, 14.07% of ideas, 8.7% of managerial ability, 7.29% of domestic investment, 5.85% of buyer feedback, 3.3% of development strategy and 1.95% of marketing strategy. Among the eight success factors, overseas investment items showed the closest preference to half, and it was the most important variable that determines the success or failure of market entry. The implication of this study is that many start-ups in Korea expect to receive investment and support from overseas accelerators. This means that overseas investment itself has been recognized as a start-up that makes services and products that can be used in the global market. A high preference for attracting foreign investment is due to the fact that the amount of investment is larger than that of Korea and that it can flexibly cope with the pressure on the performance compared to domestic investors. In this study, it was meaningful that we could confirm this fact through questionnaires of start-up experts. In future research, we need to find a viable alternative through studying how to provide start-up to foreign direct investment at the national level.

• Journal of Intelligence and Information Systems
• /
• v.17 no.3
• /
• pp.25-41
• /
• 2011

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved them more powerful than traditional artificial neural networks (ANNs) (Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al., 2005; Kim, 2003).The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.

• Journal of Intelligence and Information Systems
• /
• v.24 no.3
• /
• pp.157-176
• /
• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• Management & Information Systems Review
• /
• v.36 no.4
• /
• pp.117-127
• /
• 2017

In recent times the size of the world IPO in general has skyrocketed. Specifically, China's financial market development is becoming important as both the size of China's capital market and the number of companies going public are gradually increasing. This has led to a rapid development of venture vapital(VC) institutions in China for the past couple of decades. This study focuses on one of the three markets of China's Shenzhen Stock Exchange-the Growth Enterprise Board((GEB) hereafter, ChiNext). The ChiNext is established in October, 2009 to enable hi-tech or high growth potential technology companies that find it relatively difficult to fulfil the listing requirements of either the Shenzhen Main Board or Small and Medium Size Enterprise Board(SMEB) to go public. This study covers a three-year period(2012/01/-2015/01) and analyze first day initial return of 83 venture capital-backed companies and 53 non-venture capital-backed companies using T-test. Regression analysis is used as to examine the variables affecting IPO's first-day return. The empirical results are four-fold. First, the level of first day return of venture-backed is significantly lower than non venture capital backed support in the Chinese venture capital market. Second, the level of first-day return of listed companies supported by foreign venture capital is significantly higher than that of companies receiving domestic venture capital support. Third, the firms that have a large number of venture capital firms showed a low level of first-day return. Fourth, regression result for the IPO first-day return which is as dependent variable indicates that the venture capital support(VCAP), number of venture capital(VCNum), offering size(Lnsize) and PER all affect have negative effect on the first day initial return. Also, the venture capital type(VCType), turnover ratio and the the firm type(Tech-firms) statistically affect IPO first day return positively. Finally, by shedding more light on the IPO first-day return, this paper provides meaningful information to investors about the Chinese IPO market.

• The Korean Journal of Financial Management
• /
• v.23 no.1
• /
• pp.243-266
• /
• 2006

This paper tests cross hedging performance of the KOSPI 200 stock index futures to hedge the downside risk of the KOSPI, KOSPI 200 and KOSDAQ50 spot market. For this purpose we introduce the minimum variance hedge model, bivariate GARCH(1,1) and EGARCH(1,1) model as hedge models. The main results are as follows; First, we find that the direct hedge performance of KOSPI 200 index futures is better than those of indirect hedge performance. second, in case or cross hedge performance the hedge effect of KOSPI 200 stock index futures market against KOSPI 200 stock index spot market is relatively better than those of KOSPI 200 index futures against KOSPI and KOSDAQ spot position. Third, for the out-sample, hedging effectiveness of the risk-minimization with constant hedge ratios is higher than those of the time varying bivariate GARCH(1,1) and EGARCH(1,1) model. In conclusion, investors are encouraged to use simple risk-minimization model rather than the time varying hedge models like GARCH and EGARCH model to hedge the position of the Korean stock index cash markets.