• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.15-30
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• 2019

This study investigates the effects of venture capital investment and corporate venture capital investment on the performance of IPOs listed on KOSDAQ between 2000 and 2014. We classified venture firms with venture capital-backed companies and non-venture capital-backed companies, having the former of which further divided into corporate venture capital-backed companies and independent venture capital-backed companies. The time window of the analysis was set to between 2 years before and 3 years after IPO. Main results of this study reveal that there is little difference between venture capital-backed companies and non-venture capital-backed companies in terms of profitability before and after going public. However, we found out that after IPO venture capital-backed companies display higher ROA than independent venture capital-backed companies or non-venture capital-backed companies, suggesting that corporate venture capital-backed companies might be more advantageous in growing a venture capital ecosystem in Korea.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.2
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• pp.463-474
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• 2016

As IT environment has changed, paths of information security in financial environment which is based on IT have become more diverse and damage caused by information leakage has been more serious. Among security incidents, personal information leakage incident is liable to give the greatest damage. Personal information leakage incident is more serious than any other types of information leakage incidents in that it may lead to secondary damage. The purpose of this study is to find how much personal information leakage incident influences corporate value by analyzing 21 cases of personal information leakage incident for the last 15 years 1,899 listing firm through case research method and inferring investors' response of to personal information leakage incident surveying a change in transaction before and after personal information leakage incident. This study made a quantitative analysis of what influence personal information leakage incident has on outcome of investment by types of investors by classifying types of investors into foreign investors, private investors and institutional investors. This study is significant in that it helps improve awareness of importance of personal information security by providing data that personal information leakage incident can have a significant influence on outcome of investment as well as corporate value in Korea stock market.

• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.165-187
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• 2005

This paper tries to investigate the relationships among stock return volatility, time-varying risk premium and Korea Discount. Using Korean Composite Stock Price Index (KOSPI) return from January 4, 1980 to August 31, 2005, this study finds possible links between time-varying risk premium and Korea Discount. First of all, this study classifies Korean stock returns during the sample period by three regime-switching volatility period that is to say, low-volatile period medium-volatile period and highly-volatile period by estimating Markov-Switching ARCH model. During the highly volatile period of Korean stock return (09/01/1997-05/31/2001), the estimated time-varying unit risk premium from the jump-diffusion GARCH model was 0.3625, where as during the low volatile period (01/04/1980-l1/30/1985), the time-varying unit risk premium was estimated 0.0284 from the jump diffusion GARCH model, which was about thirteen times less than that. This study seems to find the evidence that highly volatile Korean stock market may induce large time-varying risk premium from the investors and this may lead to Korea discount.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.6
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• pp.1625-1633
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• 2007

In this paper, influences of financing method on management accomplishments for KOSDAQ listed venture firms has been objectively verified. The results of this study revealed that explanatory variable had significant influences on management outcomes of firms, and some part of pecking order theory has not gotten the supported result and other part has gotten the supported result. Also, it was analyzed that fixed asset investment had significant influences on management accomplishments.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.291-295
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• 2006

비상대처계획(EAP, Emergency Action Plan) 수립 및 홍수위험지도 작성의 목적은 댐.제방 붕괴 등 비상상황이 발생하였을 때 하류부의 생명과 재산 손실을 최소화하기 위한 것으로서 댐 운영 및 관리책임자가 극한홍수 및 지진발생 조건하에서 댐의 물리적, 지형적, 구조적 특성에 따른 발생 가능한 비상상황을 예상하고 이에 효율적으로 대처하기 위한 가능한 최선의 사전계획을 수립하는 것이다. 또한, 댐의 비상상황에 대처하기 위한 비상대처계획 수립 의무화 및 이에 대한 실제적인 모의훈련 등에 필요한 기초자료를 체계적으로 제공하고자 함에 있다. 국내에서 EAP를 수립하여야 할 대상 댐 저수지는 한국수자원공사에서 관리하는 다목적댐, 생공용수댐과 한국농촌공사에서 관리하는 농업용저수지, 한국수력원자력주식회사에서 관리하는 수력발전댐 및 지방자치단체에서 관리하는 댐 등이 해당된다. 제방의 경우 인구가 밀집되어 있는 전 지역이 그 대상이 될 수 있다. EAP의 주요 내용에는 만약에 발생할 수 있는 붕괴 사고시 인명의 손실이나 재산상의 피해를 발생시킬 수 있는 댐 저수지들에 대해서는 EAP를 수립하거나 갱신하기 위한 지침들이 포함되어 있어야 한다. 댐으로부터의 하류 연안지역의 개발이나 소유권은 다양하며, 이로 인해 댐의 운영이나 붕괴로 인한 잠재적 인명손실 또한 다양할 수 있다. 따라서 모든 EAP는 댐, 저수지 하류부 현장 조건에 맞도록 구성되어야 한다. EAP 수립의 주체는 댐 및 저수지 관리자이며 EAP에는 비상상황 확인, 평가, 등급분류, 비상연락체계 및 경보전달체계 수립, 비상시 응급행동요령, 홍수범람예측지도 작성, 비상주민대피계획 및 훈련방안, 부록, 주기적 또는 필요시마다 보완 계획 등이 포함되어야 하며, EAP의 주요 구성요소인 홍수위험지도에는 홍수위험정보 및 대피정보를 제시함으로써 실제 주민 대피계획시 실제적이고 효율적인 대피계획 수립에 활용될 수 있다. 있는 기술가치평가 모형의 구축이 요구된다. 이에 본 연구에서는 효율적인 R&D 투자 정책 수립과 정부정책수립에 기여하고자 AHP(Analytic Hierarchy Process, 계층 분석 과정)기법을 이용, 수자원의 지속적 확보기술의 특성에 따른 4개의 평가기준과 26개의 평가속성으로 이루어진 2단계 기술가치평가 모형을 구축하였으며 2개의 개별기술에 대한 시범적용을 실행하였다.하는 것으로 추정되었다.면으로의 월류량을 산정하고 유입된 지표유량에 대해서 배수시스템에서의 흐름해석을 수행하였다. 그리고, 침수해석을 위해서는 2차원 침수해석을 위한 DEM기반 침수해석모형을 개발하였고, 건물의 영향을 고려할 수 있도록 구성하였다. 본 연구결과 지표류 유출 해석의 물리적 특성을 잘 반영하며, 도시지역의 복잡한 배수시스템 해석모형과 지표범람 모형을 통합한 모형 개발로 인해 더욱 정교한 도시지역에서의 홍수 범람 해석을 실시할 수 있을 것으로 판단된다. 본 모형의 개발로 침수상황의 시간별 진행과정을 분석함으로써 도시홍수에 대한 침수위험 지점 파악 및 주민대피지도 구축 등에 활용될 수 있을 것으로 판단된다. 있을 것으로 판단되었다.4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전략을 개발 및 활용할 수 있으며, 특히, 한국주식시장에 적합한 거래전략은 반전거래전략이고, 이 전략의 유용성은 투자자가 설정한 투자기간보다 더욱 긴 분석기간의 주

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.181-200
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• 2003

Comovement of international stock market prices has been lately a major controversy in the global stock market. This paper explores whether the common trend has really existed among the US, Japan and Korea's stock markets using the econometric techniques such as VAR, VECM as applied. Pair of indices from the exchange market and the over-the-counter market in each country has been tested, and the exchange market only has been turned out that the common trend existed. The dynamic analyses using the Granger causality test, impulse response function, and the forecast error decomposition have followed to show that the US stock market has played some important role in the Korea and Japan's market in the exchange as well as in the OTC market. The results of the paper imply that the more careful investigation with respect to the co-integration may be necessary in the global market integration studies.

• The Korean Journal of Financial Management
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• v.21 no.2
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• pp.1-25
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• 2004

From the perspective of corporate governance, we examine the acquirers' performance of mergers and acquisitions. The empirical results of our study show that outside active shareholders, such as block shareholders or institutional shareholders, affect acquirers' performance in M&A's : the ownership of outside active shareholders is positively correlated with the performance of acquirers. However, the ownership of insiders, such as that of encumbent manners or major shareholders, does not have any significant effect on the performance of M&A's. We also found that the ownership of foreign investors increased its explanatory power after the financial crisis of Asia. Since the current literature concludes that the improvement of corporate governance would enhance the shareholders' wealth, the results of our study implies that outside active investors, rather than insiders, are playing an important role in the corporate governance.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• The Korean Journal of Financial Studies
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• v.10 no.1
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• pp.191-214
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• 2004

VaR에 의한 금융위험의 측정은 국제결제은행 바젤위원회의 내부모델 허용에 힘입어 금융산업에서 표준방식으로 확고한 입지를 차지하고 있다. 본 연구에서는 한국주식시장포트폴리오를 거래투자자산으로 보유한 경우의 VaR를 극단치이론에 입각하여 측정하고 이의 성과를 RiskMetrics의 성과와 비교하여 검토하였다. GPD의 모수적 추정에 의한 VaR의 사후검정결과는 표본내 사후검정이나 표본외 사후검정에서 어떤 신뢰수준에서도 기대되는 범위와 크게 벗어나지 않은 안정된 결과를 보였다. RiskMetrics의 EWMA방식도 역시 표본내와 표본외 사후검정 어느 경우에나 기대되는 범위에서 크게 벗어나지 않았지만 높은 신뢰수준에서는 그 성과가 GPD VaR에 비하여 상대적으로 불안정하였으며 위험의 과소평가 성향을 확인할 수 있었다. 비모수적 GEV추정에 입각한 VaR의 경우에는 위험을 과대평가하고 지나치게 보수적인 성향을 나타내었다. GPD의 모수적 접근에 의한 VaR 측정은 다양한 신뢰수준에서 정확한 검정결과를 보여주고 있으며, 시간적 흐름에 따르는 VaR의 행태도 지나친 변동성을 보이지 않아 외부규제 및 내부통제를 위한 금융위험의 측정지표로서 실용적인 가치가 있음을 확인할 수 있다.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.28-33
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• 2021

Since the stock price is a measure of the future value of the company, when analyzing the stock price, the company's growth potential, such as sales and profits, is considered and invested in stocks. In order to set the criteria for selecting stocks, institutional investors look at current industry trends and macroeconomic indicators, first select relevant fields that can grow, then select related companies, analyze them, set a target price, then buy, and sell when the target price is reached. Stock trading is carried out in the same way. However, general individual investors do not have any knowledge of investment, and invest in items recommended by experts or acquaintances without analysis of financial statements or growth potential of the company, which is lower in terms of return than institutional investors and foreign investors. Therefore, in this study, we propose a research method to select undervalued stocks by analyzing ROE, an indicator that considers the growth potential of a company, such as sales and profits, and predict the stock price flow of the selected stock through deep learning algorithms. This study is conducted to help with investment.