• 자원ㆍ환경경제연구
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• 제17권1호
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• pp.51-81
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• 2008

본 논문은 포트폴리오 분석 연구를 통하여 금융기관이 지속가능 경영을 추진하고 있는 환경 친화적 기업의 지속가능성을 평가할 수 있다는 것을 실증 분석하였다. 그 방법으로는 환경관련 펀드의 성과와 일반 펀드 성과를 비교하였다. 2004년 9월부터 2005년 9월까지 1년간 주식가치를 평가한 결과, 기업 가치 변화의 벤치마크지수인 KOSPI와 KOSPI200보다 수익률은 약 12~17% 우수한 결과가 나타났고, 리스크의 경우에도 동등하게 나타나는 것을 입증하였다. 산업별 지수와 비교에서도 의약품산업을 제외하고 금융 화학 전자 산업보다 효율적인 포트폴리오 결과가 도출되었으며, 그 외의 산업과는 자료의 어려움으로 비교를 할 수 없었다. 그러나 지속가능성에 입각한 금융기관의 성과 평가 활동은 새로운 사업 영역으로서의 가치가 있을 것으로 판단되며 미래에는 기업의 평가에서 중요한 역할을 할 것으로 보인다.

• 지식경영연구
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• 제19권1호
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• pp.97-118
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• 2018

The finance-investment industry is currently focusing on research related to artificial intelligence and big data, moving beyond conventional theories of financial engineering. However, the case of equity optimization portfolio by using an artificial intelligence, big data, and its performance is rarely realized in practice. Thus, the purpose of this study is to propose process improvements in equity selection, information analysis, and portfolio composition, and lastly an improvement in portfolio returns, with the case of an equity optimization model based on quantitative research by an artificial intelligence. This paper is an empirical study of the portfolio based on an artificial intelligence technology of "D" asset management, which is the largest domestic active-quant-fiduciary management in accordance with the purpose of this paper. This study will apply artificial intelligence to finance, analyzing financial and demand-supply information and automating factor-selection and weight of equity through machine learning based on the artificial neural network. Also, the learning the process for the composition of portfolio optimization and its performance by applying genetic algorithms to models will be documented. This study posits a model that the asset management industry can achieve, with continuous and stable excess performance, low costs and high efficiency in the process of investment.

• 대한산업공학회지
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• 제39권4호
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• pp.260-270
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• 2013

This paper proposes a strategic portfolio model for managing performance of online games. The portfolio matrix is composed of two dimensions: financial performance and non-financial performance. Financial performance is measured by the conventional measure, average revenue per user (ARPU). In terms of non-financial performance, five non-financial key performance indicators (KPIs) that have been widely used in the online game industry are utilized: RU (Register User), VU (Visiting User), TS (Time Spent), ACU (Average Current User), MCU (Maximum Current User). Data envelopment analysis (DEA) is then employed to produce a single performance measure aggregating the five KPIs. DEA is a linear programming model for measuring the relative efficiency of decision making unit (DMUs) with multiple inputs and outputs. This study employs DEA as a tool for multiple criteria decision making (MCDM), in particular, the pure output model without inputs. Combining the two types of performance produces the online game portfolio matrix with four quadrants: Dark Horse, Stop Loss, Jack Pot, Luxury Goods. A case study of 39 online games provided by company 'N' is provided. The proposed portfolio model is expected to be fruitfully used for strategic decision making of online game companies.

• 가정과삶의질연구
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• 제16권3호
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• pp.111-122
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• 1998

This study analyzed the copmposition of household portfolio over the family life cycle using a survey dta of 1996 Korea Household Panel Study. The finindings showed that over th family life cycle households diversified their portfolio to meet their financial needs. In the aged stage however households were more likely to have liquidity problem than the households in th other stages due to the estate concentrated portfoplio composition.

• 한국산학기술학회논문지
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• 제13권2호
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• pp.878-884
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• 2012

본 연구에서는 건설 기업을 중심으로 기업의 경영 효율성과 배당성향을 중심으로 한 효율적 포트폴리오를 선택하는 전략을 제시한다. 기업의 경영 효율성을 포트폴리오 선택에 반영하는 방안으로 DEA(Data Envelopment Analysis) 기법을 사용하였고 성장가능성은 기업의 배당 성향을 판단하는 배당 스코어링 테이블을 이용하여 평가하였다. 본 연구에서 제안한 포트폴리오 선택전략의 성능 실험을 위해 KOSPI와 KOSDAQ에 상장된 56개의 건설 산업 관련 기업의 주식을 대상으로 2007~2010년의 4년 동안 매해 3그룹의 포트폴리오를 구성하였고 각각의 포트폴리오 수익률을 벤치마크 수익률과 비교 분석하여 그 성능을 입증하였다.

• 한국산학기술학회논문지
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• 제14권2호
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• pp.899-904
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• 2013

본 연구에서는 KOSPI와 KOSDAQ에 상장된 건설 기업을 대상으로 효율적인 포트폴리오를 구성방안을 제시한다. 이를 위해 한국거래소(KRX)에서 구분하는 건설 업종을 DEA(Data Envelopment Analysis) 기법을 이용하여 기업효율성 분석을 실시하고 효율성이 우수한 기업들을 대상으로 마코위츠 모형을 통해 포트폴리오를 구성한다. 본 연구에서 제안한 포트폴리오 구성 방안의 성능 실험을 위해 KOSPI와 KOSDAQ에 상장된 53개의 기업의 주식을 대상으로 5년 (2007~2011) 동안 매해 포트폴리오를 구성하였고 각각의 포트폴리오 수익률을 경영 효율성을 고려하지 않고 구성한 포트폴리오 및 벤치마크 수익률과 비교 분석을 통해 그 우수성을 입증하였다.

• 한국경영과학회지
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• 제38권4호
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• pp.11-33
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• 2013

We analyzed the structures and properties of the global financial market networks using social network analysis approach. The Minimum Spanning Tree (MST) lengths and networks of the global financial markets based on the correlation coefficients have been analyzed. Firstly, similar to the previous studies on the global stock indices using MST length, the diversification effects in the global multi-asset portfolio can disappear during the crisis as the correlations among the asset class and within the asset class increase due to the system risks. Second, through the network visualization, we found the clustering of the asset class in the global financial markets network, which confirms the possible diversification effect in the global multi-asset portfolio. Meanwhile, we found the changes in the structure of the network during the crisis. For the last one, in terms of the degree centrality, the stock indices were the most influential to other assets in the global financial markets network, while in terms of the betweenness centrality, Gold, Silver and AUD. In the practical perspective, we propose the methods such as MST length and network visualization to monitor the change of the correlation risk for the risk management of the multi-asset portfolio.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1996년도 제10회 동계학술발표회 논문집
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• pp.265-295
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• 1996

This paper investigates empirically the relationship between various business portfolio properties (particularly technological properties) and chaebol′s performance using data on the 50 largest chaebols in Korea. In addition to the traditional indexes to measure diversification such as entropy index we calculated inter-industry technological similarity using R&D expenditure data by industry and 1990 Input-output Table in Korea, and obtained chaebol-level technological relatedness and internal transaction proportion from chaebols′business profile, inter-industry technological similarity and 1990 input-output table. We applied factor analysis on 13 business portfolio property indexes and showed that they could be grouped into 3 dimensions, diversification scope, inter-business relatedness and degree of vertical integration. In this paper, using 50 largest chaebols′financial data (1989-1994), we analyzed empirically the effect of business portfolio properties on ROS (Return On Sales) which is conventional index for firm performance and on TFP(Total Factor Productivity) growth which is a pure measure of firm performance. To utilize the advantage of panel data, FEM(Fixed Effect Model) and REM(Random Effect Model) were used. The empirical result shows that the entropy index as a measurement of inter-business relatedness is not significant but technological relatedness index is significant. OLS estimates on pooled data were considerably different from FEM or REM estimates on panel data. By introducing interaction effect among the three variables for business portfolio properties, we obtained three findings. First, only VI (Vertical integration) has a significant positive correlation with ROS. Second, when using TFP growth as an dependent variable, both TR(Technological Relatedness) and f[ are significant and positively related to the deepened variable. Third, the interaction term between TR and VI is significant and negatively affects TFP growth, meaning that TR and VI are substitutes. These results suggest strategic directions on restructuring business portfolio. As VI is increased, chaebols will get more profit. A higher level of either TR or W will increase TFP growth rate. but increase in both TR and VI will have a negative effect on TFP growth. To summarize, certain business portfolio properties such as VI and TR can be considered "resources" themselves since they can affect profit rate and productivity growth. VI and TR have a synergy effect of change in profit rate and productivity growth. VI increases ROS and productivity growth, while TR increases productivity growth representing a technological synergy effect.

• Asian Journal of Innovation and Policy
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• 제9권3호
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• pp.360-393
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• 2020

The space industry is a comprehensive and technology-intensive industry involving different converging technologies. However, most of the companies in Korea's space industry are small and medium-sized enterprises (SMEs) and need to strengthen global capacity to export their products. However, the link between the destination country and the product remains insufficient. Consequently, the purpose of this study is to propose an export roadmap for space products to provide SMEs with export opportunities and strategic guidelines. For this, technology roadmap and portfolio analysis are applied to this purpose. This study is expected to be helpful to SMEs and government agencies.

• 제어로봇시스템학회논문지
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• 제12권12호
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• pp.1169-1172
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• 2006

The prices of chemical products are fluctuated by several factors. The chemical companies can't predict and be ready to all of these changes, so they are exposed to the risk of a profit fluctuation. But they can reduce this risk by making a well-diversified product portfolio. This problem can be thought as the optimization of the product portfolio. We assume that the profits come from the 'spread' between a naphtha and a chemical product. We calculate a mean and a variation of each spread and develop an automatic module to calculate the optimal portion of each product. The theory is based on the Markowitz portfolio management. It maximizes the expected return while minimizing the volatility. At last we draw an investment selection curve to compare each alternative and to demonstrate the superiority. And we suggest that an investment selection curve can be a decision-making tool.