• 한국경영과학회지
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• 제38권2호
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• pp.75-93
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• 2013

In applying Markowitz's portfolio selection model to the stock market, we developed a comprehensive investment decision-making framework including key inputs for portfolio theory (i.e., individual stocks' expected rate of return and covariance) and minimum required expected return. For estimating the key inputs of our decision-making framework, we utilized an exponentially weighted moving average (EWMA) which places more emphasis on recent data than the conventional simple moving average (SMA). We empirically analyzed the investment results of the decision-making framework with the same 15 stocks in Samsung Group Funds found in the Korean stock market between 2007 and 2011. This five-year investment horizon is marked by global financial crises including the U.S. subprime mortgage crisis, the collapse of Lehman Brothers, and the European sovereign-debt crisis. We measure portfolio performance in terms of rate of return, standard deviation of returns, and Sharpe ratio. Results are compared with the following benchmarks : 1) KOSPI, 2) Samsung Group Funds, 3) Talmudic portfolio based on the na$\ddot{i}$ve 1/N rule, and 4) Markowitz's model with SMA. We performed sensitivity analyses on all the input parameters that are necessary for designing an investment decision-making framework : smoothing constant for EWMA, minimum required expected return for the portfolio, and portfolio rebalancing period. In conclusion, appropriate use of the comprehensive investment decision-making framework based on the Markowitz's model integrated with EWMA proves to achieve outstanding performance compared to the benchmarks.

• 경영과학
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• 제25권1호
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• pp.1-9
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• 2008

This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. In order to obtain the non-dominated portfolio that a decision maker or a user is satisfied with, we devise a user-interface algorithm, in that the user provides the maximum/minimum input values for each project attribute. Then the system searches the non-dominated portfolio that satisfies all the given constraints if such a portfolio exists. The process that the user adjusts the maximum/minimum values on the basis of the portfolio found continues repeatedly until the user is optimally satisfied with. We illustrate the algorithm proposed, and the computational results show the efficacy of our procedure.

• Journal of the Korean Data and Information Science Society
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• 제28권6호
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• pp.1481-1500
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• 2017

본 연구는 우리나라 주식시장을 대상으로 회계 정보 기반 포트폴리오 투자전략의 안정성과 우수성을 확인하였다. 포트폴리오를 구성 하는 과정에서 재무비율의 다양한 조합을 활용하여 기대수익률이 높고, 투자 위험이 낮은 종목군을 선정하고 그 성과를 측정하였다. 또한 회계 정보 기반 유전자 알고리즘 최적화 아이디어를 제시하여 투자성과를 높이고자 했다. 본 연구의 결과로 회계 정보를 활용한 포트폴리오 구성 전략이 투자 의사결정에 유효하며, 이를 통하여 높은 투자성과를 얻을 수 있음을 확인했다. 또한 유전자 알고리즘을 활용한 포트폴리오 투자전략이 실무적으로 투자 의사결정에 유용하게 활용될 수 있음을 검증하였다.

• 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.

• 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.

• The Journal of Asian Finance, Economics and Business
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• 제9권9호
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• pp.351-360
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• 2022

This study aims to determine the factors that can influence investors in selecting stocks in the Indonesian capital market to establish an optimal portfolio, and find phenomena that occurred during the COVID-19 pandemic so that buying interest / the number of investors increased in the Indonesian capital market. This study collection technique uses primary data obtained from the survey questionnaire and secondary data which is market data, stock price movement data sourced from the Indonesia Stock Exchange, Indonesian Central Securities Depository, and Bank Indonesia, as well as empirical literature on behavior finance, investment decision, and interest in buying stock. The method used in this research is the survey questionnaire analysis with the SEM (statistical approach). The results of the analysis using SEM show that investor behavior influences the stock-buying interest, investor behavior, and the stock-buying interest influences investor decision-making. However, risk management does not influence investor-decision making. This occurs when the investigator's psychological capacity produces more decision information by decreasing all potential biases, allowing the best stock selection model to be selected. When the investigator's psychological capacity creates more decision information by reducing biases, the optimum stock selection model can be chosen.

• 디지털융복합연구
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• 제10권10호
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• pp.97-106
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• 2012

과거에는 경영의사결정에 적절한 정보를 적시에 제공할 수 없기 때문에 불확실한 경영을 했으며 경영자는 주관적인 경험과 판단 등에 의지하였다. 정보기술의 발달과 더불어 발전한 정보시스템과 기술은 비즈니스 운영면에서 고도의 효율성과 생산성을 달성하기 위하여 관리자가 활용할 수 있는 가장 중요한 도구 중에 속한다. 이것의 효과는 비즈니스 실무와 관리행태의 변화가 동반되었을때 더욱 크게 나타난다. 본 연구에서는 기업의 전략적 의사결정에 필요한 문제를 해결하기 위하여 정보기술을 활용하여 필요한 정보를 획득하고 문제해결 방법론을 시뮬레이션 하여 객관적이고 정형화된 경영의사결정을 지원하는 시스템을 개발하기위한 기능요소 및 솔루션을 구조화하였다. 본 연구에서 제안하는 전략의사결정지원 시스템은 기업경영 지원기술에 관련된 것으로 IT기술을 활용하여 경영의사결정에서 요구되는 전략의사결정 문제에 있어서 최적의 시나리오를 선택하도록 하여 신뢰성 있는 기업경영에 도움을 줄 수 있는 시스템이다. 전략의사결정시스템은 개별사업 시뮬레이션과 전사사업 시뮬레이션, 전사사업 포트폴리오 관리 등 크게 세 가지 기능부문으로 나누어 볼 수 있다. 본 시스템은 객관적이고 정형화된 컨설팅 결과를 제공함으로써 신뢰성을 보장할 수 있고, 급변하는 경영 여건에 효율적으로 대응할 수 있는 유용한 효과를 기대할 수 있다.

• 한국경영과학회지
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• 제6권2호
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• pp.35-49
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• 1981

This paper is concerned with developing a Multi-period Behavioral Model for the portfolio selection problem. The unique feature of the model is that it treats a number of factors and decision variables considered germane in decision making on an interrelated basis. The formulated problem has the structure of a Chance Constrained programming Model. Then empoloying arguments of Central Limit Theorem and normality assumption the stochastic model is reduced to that of a Non-Linear Programming Model. Finally, a number of interesting properties for the reduced model are established.

• 산업공학
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• 제20권2호
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• pp.94-102
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• 2007

Portfolio management deals with decision making on 'when' and 'how' to revise an existing portfolio. In this paper, we show that a classical statistical process control (SPC) chart for normal data, a wellestablished tool in quality engineering, can effectively be used for signaling times for revising a portfolio. Noting that the day-to-day performance of a portfolio may be auto-correlated, we use the exponentially weighted moving average center-line chart to develop an automatic portfolio management procedure. The portfolio management procedure is extensively tested on historical data of equities traded in the Korea Exchange (KRX), the American Stock Exchange (AMEX), and the New York Stock Exchange (NYSE). In comparison with the performances of the KOSPI, XAX, and NYA indices during the same time periods, results from these experiments show that SPC chart-based portfolio revision presents itself a convenient and reliable method for optimally managing portfolios.

• 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.