• The Korean Journal of Financial Management
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• v.18 no.1
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• pp.107-128
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• 2001

금융기관이 직면하는 시장위험관리와 관련된 연구는 이자율과 주식가격 변동위험, 또는 환율과 이자율 변동위험만을 고려한 자산배분모델이므로 그 모형의 정교성에도 불구하고 국제금융기관의 시장위험관리 모형으로 이용하기에는 부족한 점이 있다. 시장위험인 VAR를 측정하는 방법 중 포트폴리오 VAR 측정방법인 델타-노말 방법을 응용하여 금융기관이 시장위험을 종합적으로 관리하는 한편, 기대수익을 최대화시키는 자산-부채의 최적배분에 대한 모형을 유도할 수 있다. 본 논문은 포트폴리오 접근법을 이용하여 금융기관의 시장위험을 종합적으로 관리할 수 있는 모형을 개발하는 동시에 미국, 일본, 영국, 독일의 주요 금융자산의 가격변동자료를 바탕으로 실증적 분석을 시도하였다. 이론적 모형과 관련하여 국제금융기관이 시장위험을 통제하는 한편 목표수익을 달성하는데 필요한 $m_1$ 종류의 국내자산과 부채의 규모, $m_2$ 종류의 외화자산과 부채의 규모를 동시적으로 결정할 수 있는 모델을 개발하였다. 이 모형은 금융기관의 위험포지션과 목표수익이 변동함에 따라 재구성되어야 할 국내외 자산과 부채의 포트폴리오에 대한 종류와 규모를 구체적으로 파악할 수 있게 한다. 실증분석을 위해 미국에 본점을 두고 미국, 일본, 영국, 독일에서 영업활동을 하는 국제금융기관이 16개의 국내외 금융자산을 이용 가능한 것으로 가정하였다. 1995년 1월부터 1999년 6월까지 이들 금융자산의 월별자료와 각 국 통화의 대 U.S. 달러 환율을 이용하여 목표이익 10,000천 달러를 실현하는 한편 이자율과 환율 위험을 최소화시키는 자산, 부채의 적정구성에 관한 결과를 제시하였다.구의 성과로는 특정 투자자 집단이 주가의 움직임에 따라 매매를 하는 수동적 전략의 의미보다는 적극적으로 주가를 움직이는 주체로서 외국인투자자와 일부 기관투자자의 존재를 확인할 수 있었다는 점이며, 주가 움직임에 따른 개인투자자와 일부 기관 투자자의 수동적 매매 스타일과 기관투자자 사이의 투자스타일의 이질성을 통계적으로 확인할 수 있었다는 데에 있다.남아 각국과 우리나라간에는 주가변동에 시차가 없는 것으로 나타났다. 그러나 각국간 표준시차 및 거래소 거래시간을 고려하면 미국, 영국, 독일의 경우에도 그 시차는 1일이내이거나 거의 시차가 없는 것으로 판단된다. 발견되어 선물의 선도효과가 지배적임을 발견하였다.적 일정하게 하는 소비행동을 목표로 삼고 소비와 투자에 대한 의사결정을 내리고 있음이 실증분석을 통하여 밝혀졌다. 투자자들은 무위험 자산과 위험성 자산을 동시에 고려하여 포트폴리오를 구성하는 투자활동을 행동에 옮기고 있다.서, Loser포트폴리오를 매수보유하는 반전거래전략이 Winner포트폴리오를 매수보유하는 계속거래전략보다 적합한 전략임을 알 수 있었다. 다섯째, Loser포트폴리오와 Winner포트폴리오를 각각 투자대상종목으로써 매수보유한 반전거래전략과 계속거래 전략에 대한 유용성을 비교검증한 Loser포트폴리오와 Winner포트폴리오 각각의 1개월 평균초과수익률에 의하면, 반전거래전략의 Loser포트폴리오가 계속거래전략의 Winner포트폴리오보다 약 5배정도의 높은 1개월 평균초과수익률을 실현하였고, 반전거래전략의 유용성을 충분히 발휘하기 위하여 장단기의 투자기간을 설정할 경우에 6개월에서 36개월로 이동함에 따라 6개월부터 24개월까지는 초과수익률이 상승하지만,

• Korean Journal of Construction Engineering and Management
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• v.6 no.4 s.26
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• pp.80-90
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• 2005

Activity durations retain probabilistic and stochastic natures due to diverse factors causing the delay or acceleration of activity completion. These natures make the final project duration to be a random variable. These factors are the major source of financial risk. Extending the Stochastic Project Scheduling Simulation system (SPSS) developed in previous research; this research presents a method to estimate how the final project duration behaves when activity durations change randomly. The final project cost is estimated by considering the fluctuation of indirect cost, which occurs due to the delay or acceleration of activity completion, along with direct cost assigned to an activity. The final project cost is estimated by considering how indirect cost behaves when activity duration change. The method quantifies the amount of contingency to cover the expected delay of project delivery. It is based on the quantitative analysis to obtain the descriptive statistics from the simulation outputs (final project durations). Existing deterministic scheduling method apply an arbitrary figures to the amount of delay contingency with uncertainty. However, the stochastic method developed in this research allows computing the amount of delay contingency with certainty and certain degree of confidence. An example project is used to illustrate the quantitative analysis method using simulation. When the statistical location and shape of probability distribution functions defining activity durations change, how the final project duration and cost behave are ascertained using automated sensitivity analysis method

• The Korean Journal of Financial Studies
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• v.10 no.1
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• pp.171-189
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• 2004

외환시장의 효율성을 증대시키고, 기업이나 금융기관들의 원/달러환율 변동위험관리가 보다 원활하게 이루어질 수 있도록 하며, 원/달러 환율과 연계된 다양한 투자전략 구사가 보다 용이하게 이루어질 수 있도록 하기 위하여 미국달러 선물시장과 미국달러 옵션시장에서의 유동성 확대 및 시장 활성화가 요구된다. 본 논문에서는 미국달러 선물시장과 미국달러 옵션시장의 유동성을 제고시키고 시장을 활성화 시키기 위한 방안들을 제시하였다. 미국달러선물의 만기시 최종결제와 미국달러옵션 만기시 옵션매입자가 옵션을 행사할 때 권리행사에 따른 결제는 실물인수도 방식으로 결제되며, 이러한 실물인수도 방식의 결제는 현물환 포지션을 취하여야 하는 불편함과 현물환 거래와 관련된 거래비용 등으로 인하여 투자자들의 시장 참여를 제약하는 주요 요인으로 작용하고 있다. 미국달러선물과 미국달러옵션의 만기시 결제방식을 현금결제 방식으로 바꾸게 되면 헤지거래자 등 투자자들의 참여가 확대되어 시장 유동성이 증대되고 시장이 활성화될 것이며, 차익거래자들도 적극적으로 참여하게 되어 시장의 효율성이 향상될 것이다. 그리고 미국달러선물과 미국달러옵션을 이용한 투자기법 및 투자전략에 대한 투자자들의 이해 수준을 높이고 환율변동위험 관리의 중요성에 대한 기업들의 인식을 제고시키기 위한 적극적인 노력이 요구되며, 중장기적으로 선물회사들의 지점망 확충과 선물거래소 회원사 확대 방안도 모색되어야 할 것이다. 미국달러 옵션은 거래가 매우 부진한 상태이므로 미국달러 옵션시장에서 유동성이 어느 정도 확보될 때까지는 선물회사들의 시장조성 기능 강화가 요구된다.주었다. 둘째, 주가 수익률을 결정하는 유의성있는 요인들은 당기순이익의 증감, 당해연도의 당기순이익의 분포, 자산증가율, 매매 유동성, 매출액 변동, 거래량 추세, 기업크기(시가총액), 과거 1개월간의 주가수익률, 자기자본증가율등으로 나타났다.이 있을 것으로 여겨진다.다중회귀분석에서 각각 일관되게 관찰할 수 있었다. 또한 이러한 결과는 IMF 이후에도 여전히 유지되는 것으로 나타났다.과와는 별개의 PER효과가 여전히 존재하며, 다만 이 PER 효과는 전통적 의미의 일반적으로 낮은 PER종목이 초과수익률을 내는 것이 아니라, 기업규모가 크더라도 그 기업의 개별특성을 고려했을 때 이와 비교해 상대적으로 PER가 낮은 종목에 투자하면 초과수익을 낼 수 있음을 의미한다. 발견하였다.적 일정하게 하는 소비행동을 목표로 삼고 소비와 투자에 대한 의사결정을 내리고 있음이 실증분석을 통하여 밝혀졌다. 투자자들은 무위험 자산과 위험성 자산을 동시에 고려하여 포트폴리오를 구성하는 투자활동을 행동에 옮기고 있다.서, Loser포트폴리오를 매수보유하는 반전거래전략이 Winner포트폴리오를 매수보유하는 계속거래전략보다 적합한 전략임을 알 수 있었다. 다섯째, Loser포트폴리오와 Winner포트폴리오를 각각 투자대상종목으로써 매수보유한 반전거래전략과 계속거래 전략에 대한 유용성을 비교검증한 Loser포트폴리오와 Winner포트폴리오 각각의 1개월 평균초과수익률에 의하면, 반전거래전략의 Loser포트폴리오가 계속거래전략의 Winner포트폴리오보다 약 5배정도의 높은 1개월 평균초과수익률을 실현하였고, 반전거래전략의 유용성을

• Information Systems Review
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• v.20 no.4
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• pp.79-96
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• 2018

This study started by focusing on the internalization of the technology appraisal model into the credit rating model to increase the discriminative power of the credit rating model not only for SMEs but also for all companies, reflecting the items related to the financial stability of the enterprises among the technology appraisal items. Therefore, it is aimed to verify whether the technology appraisal model can be applied to identify high-stability SMEs in advance. We classified companies into industries (manufacturing vs. non-manufacturing) and the age of company (initial vs. non-initial), and defined as a high-stability company that has achieved an average debt ratio less than 1/2 of the group for three years. The C5.0 was applied to verify the discriminant power of the model. As a result of the analysis, there is a difference in importance according to the type of industry and the age of company at the sub-item level, but in the mid-item level the R&D capability was a key variable for discriminating high-stability SMEs. In the early stage of establishment, the funding capacity (diversification of funding methods, capital structure and capital cost which taking into account profitability) is an important variable in financial stability. However, we concluded that technology development infrastructure, which enables continuous performance as the age of company increase, becomes an important variable affecting financial stability. The classification accuracy of the model according to the age of company and industry is 71~91%, and it is confirmed that it is possible to identify high-stability SMEs by using technology appraisal items.

• Journal of Korea Technology Innovation Society
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• v.21 no.1
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• pp.385-419
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• 2018

This study suggests an integrated model composed of factors of industrial environments and technology capacity for corporate diversification decision based on industrial organization theory and resource based perspectives. We examine the proposed model using patents and financial data of 272 applicants for 6 years (2010~2015) in the smart factory ICT convergence technology (application and platform field) sectors. The result of analyzing the fixed effect panel model shows that technological competitiveness has a positive effect on corporate diversification. Also, the additional result of analyzing the two-stage least square fixed effect model indicates that the convergence patent ratio increases technological competitiveness. Based on the results, we provide implications for corporate diversification strategies and government R & D policies for commercialization of corporate convergence technology resources and competencies.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.37-41
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• 2021

In recent years, ESG investment is increasing worldwide, and awareness of ESG risks such as environment, society, and governance is increasing, and non-financial investments are considered when making investment decisions. With the recent Corvid 19 crisis, the focus is on the environment, and investments related to bio and health are gaining popularity, while new investments are completely suspended in coal-related businesses, and decisions are made in the direction of sequential termination or withdrawal of existing businesses This has resulted in an increasing number of managers setting climate change and sustainability as top priorities in their investment portfolios. As a result, it is necessary to present effective countermeasures to changes in the investment environment, and to make efforts to respond and prepare an investment system that can help build a risk management system. Therefore, I would like to briefly review the ESG investment trends and present implications considering shared growth and mutual benefit.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.367-380
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• 2020

Recently, Korea's economy is facing a difficult economic situation due to sluggish domestic demand, low corporate investment and a cliff in youth employment. In order to overcome this problem and turn the economy into a virtuous circle, the government has introduced and implemented various economic policies. In this study, the effects of the corporate accumulated earnings tax system included in the 2014 tax code revision were to be verified. The validity of the business income was verified and analyzed using the financial data of the entity as to whether the income of the entity was being circulated to household income. First, validating the validity of whether the income tax on non-current income affects the level of an entity's investment, the results showed significant negative effects at a significant level of 5 per cent. Second, the analysis of whether the return tax on corporate income is affecting management decisions that increase the level of dividends for an entity has identified a metaphorical positive relationship. Third, it was confirmed that the income tax on uncurrency income does not have a significant effect on the increase in wages for workers. The result is presumed to be the main reason for the increased uncertainty in the economy and business environment.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.155-170
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• 2018

Predicting a company's financial bankruptcy is traditionally one of the most crucial forecasting problems in business analytics. In previous studies, prediction models have been proposed by applying or combining statistical and machine learning-based techniques. In this paper, we propose a novel intelligent prediction model based on the simulated annealing which is one of the well-known optimization techniques. The simulated annealing is known to have comparable optimization performance to the genetic algorithms. Nevertheless, since there has been little research on the prediction and classification of business decision-making problems using the simulated annealing, it is meaningful to confirm the usefulness of the proposed model in business analytics. In this study, we use the combined model of simulated annealing and machine learning to select the input features of the bankruptcy prediction model. Typical types of combining optimization and machine learning techniques are feature selection, feature weighting, and instance selection. This study proposes a combining model for feature selection, which has been studied the most. In order to confirm the superiority of the proposed model in this study, we apply the real-world financial data of the Korean companies and analyze the results. The results show that the predictive accuracy of the proposed model is better than that of the naïve model. Notably, the performance is significantly improved as compared with the traditional decision tree, random forests, artificial neural network, SVM, and logistic regression analysis.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.153-164
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• 2014

This study is to investigate the effects of intangible assets such as research & development, education & training and advertisement on firm values of high-technology firms and low-technology firms listed in the KOSDAQ market, and to analyze the value-relativeness between the audit quality of companies and the expenditure of intangible assets. The substitute measurement of firm values is Tobin's Q model. The sample period for positive analysis is from 2003 to 2008, and the samples, excepting for financial business, are manufacturing companies of closing accounts corporate on December, based on companies of KOSDAQ that are listed in security. Finally, data from about 305 companies are used in this analysis. Followings are the results of the analysis. First, research & development, education & training of high-technology firms have an effect on firm values, and education & training of low-technology have an effect on firm values. Second, we find that audit quality(BIG4) increases the value relevance of R&D expenditures of high-technology firms and audit quality(BIG4) increases the value relevance of education & training expenditures of low-technology firms. This paper is meaningful in that it verified the value-relativeness of cost of intangible assets compared with high-technology firms to low-technology firms.