• 경영과학
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• 제25권3호
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• pp.59-72
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• 2008

This paper proposes an R&D opportunity scan framework for information and telecommunications company in aging society. The framework consists of trend analysis, market-oriented search, technology-oriented search, and R&D Portfolio development. We identify technology themes in the market-oriented search by developing market scenarios and analyzing a new business model framework. And then we search prospective technologies in the technology-oriented recess by technology scanning and patent analysis. By matching technology themes with prospective technologies, generate an R&D portfolio. Finally, we evaluate the risk of the proposed R&D portfolio.

• 산업경영시스템학회지
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• 제32권4호
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• pp.63-71
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• 2009

The traditional portfolio optimization problem is to find an investment plan for securities with reasonable trade-off between the rate of return and the risk. The seminal work in this field is the mean-variance model by Markowitz, which is a quadratic programming problem. Since it is now computationally practical to solve the model, a number of alternative models to overcome this complexity have been proposed. In this paper, among the alternatives, we focus on the Mean Absolute Deviation (MAD) model. More specifically, we developed an algorithm to obtain an optimal portfolio from the MAD model. We showed mathematically that the algorithm can solve the problem to optimality. We tested it using the real data from the Korean Stock Market. The results coincide with our expectation that the method can solve a variety of problems in a reasonable computational time.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.534-541
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• 2011

Risk evaluation approaches for bidding on international construction projects are typically partitioned into three stages: country selection, project classification, and bid-cost evaluation. However, previous studies are frequently under attack in that they have several crucial limitations: 1) a dearth of studies about country selection risk tailored for the overseas construction market at a corporate level; 2) no consideration of uncertainties for input variable per se; 3) less probabilistic approaches in estimating a range of cost variance; and 4) less inclusion of covariance impacts. This study thus suggests a three-staged risk evaluation model to resolve these inherent problems. In the first stage, a country portfolio model that maximizes the expected construction market growth rate and profit rate while decreasing market uncertainty is formulated using multi-objective genetic analysis. Following this, probabilistic approaches for screening bad projects are suggested through applying various data mining methods such as discriminant logistic regression, neural network, C5.0, and support vector machine. For the last stage, the cost overrun prediction model is simulated for determining a reasonable bid cost, while considering non-parametric distribution, effects of systematic risks, and the firm's specific capability accrued in a given country. Through the three consecutive models, this study verifies that international construction risk can be allocated, reduced, and projected to some degree, thereby contributing to sustaining stable profits and revenues in both the short-term and the long-term perspective.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2008년도 추계 공동 국제학술대회
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• pp.365-384
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• 2008

Many studies on ASP outsourcing area have focused on the Critical Success Factors(CSFs) of ASP outsourcing projects or on the service quality of ASP Service. But these studies have limitations to explain how to succeed in doing ASP outsourcing project. The objective of this research is to overcome this limitation by using the concept of "IT Risk" in Outsourcing. The effective control of the risks-caused during the IS outsourcing process-gives (ASP service using) users a powerful tool to minimize the risks and thus maximizes the possibility of ASP outsourcing project success. In order to perform this objective, this research set up the research model which is composed of three concepts. The three concepts are 1. Undesirable Outcomes(:UO) as IT outsourcing Risks, 2. The Source of Risks(:SOR) influencing the UO, and 3. the intention to get/execute Real Option Portfolio to control the risk level of SORs and UOs. This research has some important and interesting implications on the ASP outsourcing area. First, this research classifies the risk factors as three concepts and finds the interactions among them. Second, Using Real Option portfolio can control the risks effectively occurred during outsourcing projects. Third, Vendors(ASP service providers) can offer users IN TIME the options which can minimize the occurrence of risks.

• 기술혁신연구
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• 제26권4호
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• pp.29-56
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• 2018

최근 글로벌 기업들은 신기술 확보를 위해 사내벤처캐피탈(Corporate Venture Capital, CVC)을 설립하여 기술벤처에 투자하고 있다. 본 연구의 목적은 CVC의 투자 포트폴리오 운영방식 차이가 모기업의 기술혁신 효과에 영향을 주는지 통계적으로 실증 분석하기 위함에 있다. 구체적으로 CVC의 '시드(Seed)', '초기(Early)', '확장(Expansion)', '후기(Late)' 4가지 투자 단계별로 투자된 금액비중에 따라 매년 투자 포트폴리오 성장잠재성과 리스크 수준이 달라진다는 것을 발견하였고, 포트폴리오의 공격적인 투자성향과 외부 파트너십이 모기업 기술 혁신효과에 미치는 영향에 대해 분석하였다. 연구를 위해 글로벌 70개 CVC들이 21년간 투자한 실적 데이터를 음이항 패널 회귀분석(negative binomial panel regression)을 통해 검증하였다. 연구의 결과, 벤처 포트폴리오 내 시드/초기 단계 기업들에 투자한 금액이 클수록 기술혁신 효과는 증가하지만, 일정 수준 이상부터는 오히려 효과가 감소하는 Inverted U형 관계를 확인하였다. 또한, 각 투자단계별 벤처기업들에 공동 투자한 외부 파트너 수가 포트폴리오 운영성향과 기술혁신 효과 사이의 Inverted U형 관계를 약화시키는 조절효과를 통계적으로 실증하였다. 본 논문은 기업이 투자포트폴리오를 구성할 때 투자 단계와 경과시점을 고려할 경우 투자성과를 극대화할 수 있다는 점에서 기획 담당자, 벤처 투자자, 정책 관리자 등에 시사점을 제공할 수 있다.

• 한국산학기술학회논문지
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• 제1권1호
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• pp.91-100
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• 2000

과거 국내금융기관의 신용공여는 소수 대기업과 그들의 계열사 및 일부 업종에 집중되었기 때문에 국내금융기관은 위험이 분산된 대출포트폴리오를 소유하지 못했었다. 이번 IMF 금융위기는 다수의 부실채권을 발생시킴으로써 개별 대출에 대한 위험관리뿐만 아니라 대출들로 구성되어진 포트폴리오에 대한 위험관리가 필수적이라는 것을 보여주었다. 본 논문의 목표는 국내금융기관들이 신용위험을 분산시켜 위험-수익 측면에서 효율적인 대출포트폴리오의 관리 방안을 제시하고자 하는 것이다. 본 논문에서는 대출포트폴리오의 효율적 관리를 위하여 선진 금융기관에서 많이 사용하는 계량적 신용위험관리 기법인 KMV Model과 CreditMetrics를 소개하였다. KMV Model은 옵션가격결정모형에 근거하여 기업의 주가수준 및 변동성으로 부터 대출기업의 부도확률을 도출하고, 주가의 상관관계를 토대로 개별 대출들간에 기대수익의 상관관계를 추정한다. 따라서 금융기관은 이 모형을 이용하여 위험이 잘 분산된 효율적인 대출포트폴리오를 구할 수 있다. CreditMetrics는 대출포트폴리오의 위험노출을 계량적으로 평가하는 VaR(Value at Risk)를 구하는 것으로 신용위험으로 인한 대출포트폴리오의 가치변동에 따른 잠재적 손실을 측정하는 기법이다. 이 기법에 따르면 금융기관은 과거 경험에 근거하여 신용등급별로 신용등급의 변동확률을 파악하고, 신용등급의 변동에 따른 대출포트폴리오 가치 변동과 손실가능성을 측정할 수 있다. 이와 같이 국내금융기관은 보다 과학적이고 계량화된 위험관리 기법을 적용하여 개별 대출의 한계위험공헌도 및 대출들 상호간에 위험의 상관관계를 고려하여 신용위험을 분산시키는 대출포트폴리오 관리를 실시해야 할 것이다.

• 경영과학
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• 제32권1호
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• pp.15-33
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• 2015

Under complete information, introducing additional constraints to a portfolio will have a negative impact on performance. However, real-life investments inevitably involve use of error-prone estimations, such as expected stock returns. In addition to the reality of incomplete data, investments of most Korean domestic equity funds are regulated externally by the government, as well as internally, resulting in limited maximum investment allocation to single stocks and risk free assets. This paper presents an investment framework, which takes such real-life situations into account, based on a newly developed portfolio selection model considering realistic constraints under incomplete information. Additionally, we examined the effects of additional constraints on portfolio's performance under incomplete information, taking the well-known Samsung and SK group stocks as performance benchmarks during the period beginning from the launch of each commercial fund, 2005 and 2007 respectively, up to 2013. The empirical study shows that an investment model, built under incomplete information with additional constraints, outperformed a model built without any constraints, and benchmarks, in terms of rate of return, standard deviation of returns, and Sharpe ratio.

• The Journal of Asian Finance, Economics and Business
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• 제7권9호
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• pp.135-145
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• 2020

This paper provides the practical application of a linear shrinkage framework on Vietnam stock market. The cumulative data points observed in this analysis are 468 weeks from January 2011 to December 2019. All the companies listed on Ho Chi Minh City Stock Exchange (HOSE), except the companies under two years period from Initial Public Offering (IPO), are considered. The cumulative number of stocks picked is therefore 350 companies. The VNINDEX, which is the Vietnam Stock Index, is used as a reference index for shrinking to a single-index model. The empirical results show that the shrinkage of covariance matrix for portfolio optimization gives the promising results for the investors on Vietnam stock market. The shrinkage method helps the investors to produce the optimal portfolio in the sense of having higher profit with lower levels of risk compared to the portfolio of the traditional SCM method. Moreover, the portfolio turnover of shrinkage method is always kept at low magnitudes, and this makes the shrinkage portfolios save much transaction costs and reduce the liquidity risks in the trading process. In addition, the ability of shrinkage method in making profit is once again confirmed by the Alpha coefficient that achieves a high positive value.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권1호
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• pp.44-51
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• 2016

Recently, artificial intelligence has reached the level of top information technologies that will have significant influence over many aspects of our future lifestyles. In particular, in the fields of machine learning technologies for classification and decision-making, there have been a lot of research efforts for solving estimation and control problems that appear in the various kinds of portfolio management problems via data-driven approaches. Note that these modern data-driven approaches, which try to find solutions to the problems based on relevant empirical data rather than mathematical analyses, are useful particularly in practical application domains. In this paper, we consider some applications of modern data-driven machine learning methods for portfolio management problems. More precisely, we apply a simplified version of the sparse Gaussian process (GP) classification method for classifying users' sensitivity with respect to financial risk, and then present two portfolio management issues in which the GP application results can be useful. Experimental results show that the GP applications work well in handling simulated data sets.

• 한국태양에너지학회 논문집
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• 제37권1호
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• pp.59-69
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• 2017

In 2012, Korea introduced a Renewable Portfolio Standard (RPS) scheme, replacing the Feed-in Tariff (FIT) scheme as a market support policy of renewable energy in the electricity market. RPS is to allocate obligatory quota of renewable energy sources for electricity suppliers, whereas FIT is to guarantee high prices for electricity from renewable energy sources. This study examines the effect of this policy change on solar photovoltaic market. According to the study, solar PV market grew fast under FIT as well as under RPS. However, under RPS the size of subsidy for solar PV suppliers was shrunk substantially. In addition, market risk increased severly under RPS due to the volatility of price of renewable energy certificate (REC) as well as of the electricity market price. The small and medium suppliers of solar PV were suffered the most severly from these policy effects. Therefore, the policy reform of RPS is needed to alleviate the market risk of small and medium suppliers of solar PV.