• 한국콘텐츠학회논문지
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• 제17권5호
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• pp.552-564
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• 2017

본 연구는 전통적 학습역량 및 경력관리 시스템의 한계를 극복하면서, 대학의 교과 및 비교과 프로그램의 운영 관리를 위한 통합형 e포트폴리오의 기능과 시스템의 구성요소를 고안하고, 인쇄물 기반의 프로토타입을 개발하는 것을 목적으로 S대학의 맥락에서 실시되었다. 연구진은 2차에 걸친 전문가 타당화를 통해 통합형 e포트폴리오의 주요 메뉴와 기능을 도출하였으며 각 메뉴에 포함해야 할 하위기능을 찾고 타당성을 확보하였다. 통합형 e포트폴리오 시스템의 구성요소는 크게 6가지(기본정보, 학습 역량 관리, 진로 경력 관리, 포트폴리오 관리, 커뮤니티, 기타)로 도출되었다. 이 중 학습 역량 관리, 진로 경력 관리, 포트폴리오 관리는 전통적 e포트폴리오와 차별화된 기능으로 내용구성의 타당성이 우수하다고 평가받았다. 본 연구에서는 통합형 e포트폴리오 시스템을 바탕으로 인쇄물 기반의 e포트폴리오 프로토타입을 개발하여 실제 시스템 구현의 구체적 가이드를 제공함과 동시에 통합형 e포트폴리오의 개발 방향 설정에 대한 기관의 인식제고에 공헌한 것으로 분석되었다.

• 한국기술혁신학회:학술대회논문집
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• 한국기술혁신학회 2017년도 춘계학술대회 논문집
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• pp.357-391
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• 2017

In this study, we suggest a new perspective on the linkage between alliance portfolio diversity and innovation performance based on a contingency approach. Using a longitudinal data set on alliance portfolios and patents of 182 firms in the U.S. manufacturing industries, we examined that alliance portfolio diversity has a U-shaped relationship with firm-level innovation. Internal value creation capabilities in terms of routine and ability are found to moderate the relationship between alliance portfolio diversity and innovation performance: Organizational search routine strengthens the relationship of alliance portfolio diversity and innovation performance while technological capabilities weaken and flip the relationship.

• Management Science and Financial Engineering
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• 제10권1호
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• pp.25-41
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• 2004

There have been many studies to build a model that can help investors construct optimal portfolio. Most of the previous models, however, are based upon the path-breaking Markowitz model (1959) which is a quantitative model. One of the most important problems with that kind of quantitative model is that, in reality, most of the investors use not only quantitative, but also qualitative information when they select their optimal portfolio. Since collecting both types of information from the markets are time consuming and expensive, making a set of target assets smaller, without suffering heavy loss in the rate of return, would attract investors. To extract only desired assets among all available assets, we need knowledge that identifies investors' preference for the risk of the assets. This study suggests two-layer decision-making rules capable of identifying an investor's risk preference and an architecture applying them to a quantitative portfolio model based on risk and expected return. Our knowledge-based portfolio system is to build an investor's preference-oriented portfolio. The empirical tests using the data from Korean capital markets show the results that our model contributes significantly to the construction of a better portfolio in the perspective of an investor's benefit/cost ratio than that produced by the existing portfolio models.

• 한국경영과학회지
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• 제41권3호
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• pp.1-21
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• 2016

The Markowitz portfolio selection model uses estimators to deduce input parameters. However, the estimation errors of input parameters negatively influence the performance of portfolios. Therefore, this model cannot be reliably applied to real-world investments. To overcome this problem, we suggest an algorithm that can exclude stocks with large estimation error from the portfolio by applying a tracking signal to the Markowitz portfolio selection model. By calculating the tracking signal of each stock, we can monitor whether unexpected departures occur on the outcomes of the forecasts on rate of returns. Thereafter, unreliable stocks are removed. By using this approach, portfolios can comprise relatively reliable stocks that have comparatively small estimation errors. To evaluate the performance of the proposed approach, a 10-year investment experiment was conducted using historical stock returns data from 6 different stock markets around the world. Performance was assessed and compared by the Markowitz portfolio selection model with additional constraints and other benchmarks such as minimum variance portfolio and the index of each stock market. Results showed that a portfolio using the proposed approach exhibited a better Sharpe ratio and rate of return than other benchmarks.

• Journal of Construction Engineering and Project Management
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• 제1권3호
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• pp.28-37
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• 2011

Domestic construction companies are suffering from financing difficulties in the wake of the economic slump in Korea and abroad. During this economic slump, real estate investment trusts (REITs), facilitators for improving financing and stimulating construction businesses, have increasingly expanded since their introduction in 2001. However, in terms of growth speed and marketing size, Korean REITs are falling behind those of other nations. The purpose of this study is to suggest a method for composing a portfolio using the Markowitz portfolio selection model to stimulate REITs. The main contents are as follows. First, a comparative analysis was conducted of increased REIT profit with the application of the Markowitz model and the average REIT profit rate from July 3, 2007, to July 21, 2008, during the investment analysis periods. The results showed that the total profit rate from the Markowitz model was about 10% higher than the average REIT profit rate. Second, the sensitivity was analyzed according to the portfolio's data-gathering and replacement cycle to measure the optimum cycle and yield. The six-mouth profit data collection period showed about 16% higher profits with the Markowitz model than with the REITs. The two-week portfolio change period resulted in about 11% higher profits with the Markowitz model than with the REITs.

• 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.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제8권1호
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• pp.17-28
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• 2019

금융투자 관리 전략 중에서 여러 금융 상품을 선택하고 조합하여 분산 투자하는 것을 포트폴리오 관리 이론이라 부른다. 최근, 블록체인 기반 금융 자산, 즉 암호화폐들이 몇몇 유명 거래소에 상장되어 거래가 되고 있으며, 암호화폐 투자자들이 암호화폐에 대한 투자 수익을 안정적으로 올리기 위하여 효율적인 포트폴리오 관리 방안이 요구되고 있다. 한편 딥러닝이 여러 분야에서 괄목할만한 성과를 보이면서 심층 강화학습 알고리즘을 포트폴리오 관리에 적용하는 연구가 시작되었다. 본 논문은 기존에 발표된 심층강화학습 기반 금융 포트폴리오 투자 전략을 바탕으로 대표적인 비동기 심층 강화학습 알고리즘인 Asynchronous Advantage Actor-Critic (A3C)를 적용한 효율적인 금융 포트폴리오 투자 관리 기법을 제안한다. 또한, A3C를 포트폴리오 투자 관리에 접목시키는 과정에서 기존의 Cross-Entropy 함수를 그대로 적용할 수 없기 때문에 포트폴리오 투자 방식에 적합하게 기존의 Cross-Entropy를 변형하여 그 해법을 제시한다. 마지막으로 기존에 발표된 강화학습 기반 암호화폐 포트폴리오 투자 알고리즘과의 비교평가를 수행하여, 본 논문에서 제시하는 Deterministic Policy Gradient based A3C 모델의 성능이 우수하다는 것을 입증하였다.

• 아태비즈니스연구
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• 제13권2호
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• pp.123-138
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• 2022

Purpose - This study compares the performances of dynamic asset allocation strategies using Korean stocks and U.S. dollar, which have been negatively correlated for a long time, to examine the diversification effects in the portfolios of them. Design/methodology/approach - In the current study, we use KOSPI200 index, as a proxy of the aggregated portfolio of Korean stocks, and USDKRW foreign exchange rate to implement various portfolio management strategies. We consider the equally-weighted, risk-parity, minimum variance, most diversified, and growth optimal portfolios for comparison. Findings - We first find the enhancement of risk adjusted returns due to risk reduction rather than return increasement for all the portfolios of consideration. Second, the enhancement is more pronounced for the trading strategies using correlations as well as volatilities compared to those using volatilities only. Third, the diversification effect has become stronger after the global financial crisis in 2008. Lastly, we find that the performance of the growth optimal portfolio can be improved by utilizing the well-known momentum phenomenon in stock markets to select the length of the sample period to estimate the expected return. Research implications or Originality - This study shows the potential benefits of adding the U.S. dollar to the portfolios of Korean stocks. The current study is the first to investigate the portfolio of Korean stocks and U.S. dollar from investment perspective.

• 한국경영과학회지
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• 제39권1호
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• pp.113-127
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• 2014

The stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first-order stochastic dominance with maximum utility defined in terms of mean and variance by managing the constraint set and the objective function in an iterative manner. A nonlinear programming algorithm was developed and tested with promising results against Korean stock market data sets.

• 시스템엔지니어링학술지
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• 제7권1호
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• pp.31-41
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• 2011

The purpose of this paper is to provide an abstracted meta-model for executing Capabilities Portfolio Management (CPM) effectively based on DoDAF2.0. The purpose of developing an architecture is for beneficial use of it. A good set of architectural artifacts facilitates the manipulation and use of them in meeting its usage objectives well. Systems engineering methodologies evolve to accommodate or to deal with enterprise or SoS/FoS level problems. And DoD's Capabilities Portfolio Management (CPM) is a good example which demonstrates enterprise or SoS level problems. However, the complexity of the architecture framework makes it difficult to develop and use the architecture models and their associated artifacts. DoDAF states that it was established to guide the development of architectures and to satisfy the demands of a structured, repeatable method for evaluating alternatives which add value to decisions and management practices. One of the objectives of DoDAF2.0 is to define concepts and models usable in CPM which is one of DoD's six core processes. However, DoDAF and various guidelines state requirements for CPM rather than how to. This paper provides methodology for CPM which includes process and tailored meta-models based on DoDAF Meta Model (DM2).