• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.12
• /
• pp.1169-1172
• /
• 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.

• Journal of Electrical Engineering and Technology
• /
• v.5 no.2
• /
• pp.239-245
• /
• 2010

Today, as power trades between generators and loads are liberalized, the uncertainty level of power systems is rapidly increasing. Therefore, transmission operators are required to incorporate these uncertainties when establishing an investment plan for effective operation of transmission facilities. This paper proposes the methodology for an optimal solution of transmission expansion plans for the long-term in a deregulated power system. The proposed model uses the probabilistic cost of transmission congestion for various scenarios and the annual increasing rates of loads. The locations and the installation times of expanded transmissions lines with minimum cost are acquired by the model. To minimize the investment risk, the Mean-Variance Markowitz portfolio theory is applied to the model. In a case study, the optimal solution of a transmission expansion plan is obtained considering the uncertain power market.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.4
• /
• pp.560-566
• /
• 2008

Today, as the power trades between generation companies and power customer are liberalized, the uncertainty level of operated power system is rapidly increased. Therefore, transmission operators as decision makers for transmission expansion are required to establish a deliberate investment plan for effective operations of transmission facilities considering forecasted conditions of power system. This paper proposes the methodology for the optimal solution of transmission expansion in deregulated power system. The paper obtains the expected value of transmission congestion cost for various scenarios by using occurrence probability. In addition, the paper assumes that increasing rates of loads are the probability distribution and indicates the location of expanded transmission line, the time for transmission expansion with the minimum cost for the future by performing the Montecarlo simulation. To minimize the investment risk as the variance of the congestion cost, Mean-Variance Markowitz portfolio theory is applied to the optimization model by the penalty factor of the variance. By the case study, the optimal solution for transmission expansion plan considering the feature of market participants is obtained.

• Korean Management Science Review
• /
• v.30 no.1
• /
• pp.73-89
• /
• 2013

This paper develops an investment algorithm based on Markowitz's Portfolio Selection Theory, using historical stock return data, and empirically evaluates the performance of the proposed algorithm in the U.S. and the Hong Kong stock markets. The proposed investment algorithm is empirically tested with the 30 constituents of Dow Jones Industrial Average in the U.S. stock market, and the 30 constituents of Hang Seng Index in the Hong Kong stock market. During the 6-year investment period, starting on the first trading day of 2006 and ending on the last trading day of 2011, growth rates of 12.63% and 23.25% were observed for Dow Jones Industrial Average and Hang Seng Index, respectively, while the proposed investment algorithm achieved substantially higher cumulative returns of 35.7% in the U.S. stock market, and 150.62% in the Hong Kong stock market. When compared in terms of Sharpe ratio, Dow Jones Industrial Average and Hang Seng Index achieved 0.075 and 0.155 each, while the proposed investment algorithm showed superior performance, achieving 0.363 and 1.074 in the U.S. and Hong Kong stock markets, respectively. Further, performance in the U.S. stock market is shown to be less sensitive to an investor's risk preference, while aggressive performance goals are shown to achieve relatively higher performance in the Hong Kong stock market. In conclusion, this paper empirically demonstrates that an investment based on a mathematical model using objective historical stock return data for constructing optimal portfolios achieves outstanding performance, in terms of both cumulative returns and Sharpe ratios.

• The Korean Journal of Applied Statistics
• /
• v.34 no.1
• /
• pp.39-56
• /
• 2021

Many researches have been done on portfolio optimization since Markowitz (1952) published a diversified investment model. Markowitz's mean-variance portfolio optimization problem is established under the assumption that the distribution of returns follows a normal distribution. However, in real life, the distribution of returns does not follow a normal distribution, and variance is not a robust statistic as it is heavily influenced by outliers. To overcome these potential issues, mean-shortfall portfolio model was proposed that utilized downside risk, shortfall, as a risk index. In this paper, we propose a perturbation method that uses the shortfall as a risk index of the portfolio. The proposed portfolio utilizes an adaptive Lasso to obtain a sparse and stable asset selection because it can reduce management and transaction costs. The proposed optimization is easily applicable as it can be computed using an efficient linear programming. In our real data analysis, we show the validity of the proposed perturbation method.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.4
• /
• pp.1551-1556
• /
• 2012

This study proposes an efficient portfolio selection methodology for the listed corporations in KOSPI with consideration of managerial efficiency. For each industrial sector classified by KRX(Korea Exchange), the proposed method carries out an efficiency analysis using DEA (Data envelopment analysis) approach and for the efficient corporations filtered by DEA, construct portfolio using Markowitz's Model. In order to show the effectiveness of the proposed method, we constructed annually portfolios for 4 years (2007-2010) out of 600 listed corporations in KOSPI and KOSDAQ, and proved that our portfolios are superior to benchmark portfolios in terms of rate of returns.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.57-64
• /
• 2021

This research attempts to formulate a new mean-risk model to replace the Markowitz mean-variance model by altering the risk measurement using ARCH variance instead of the original variance. In building the portfolio, samples used are closing prices of Indonesia Composite Stock Index and Indonesia Composite Bonds Index from 2013 to 2018. This study is a qualitative study using secondary data from the Indonesia Stock Exchange and Indonesia Bonds Pricing Agency. This research found that Markowitz's model is still superior when utilized in daily data, while the mean-ARCH model is appropriate with wider gap data like monthly observation. The Historical return has also proven to be more appropriate as a benchmark in selecting an optimal portfolio rather than a risk-free rate in an inefficient market. Therefore Mean-ARCH is more appropriate when utilized under data that have a wider gap between the period. The research findings show that the portfolio combination produced is inefficient due to the market inefficiency indicated by the meager return of the stock, while bears notable standard deviation. Therefore, the researcher of this study proposed to replace the risk-free rate as a benchmark with the historical return. The Historical return proved to be more realistic than the risk-free rate in inefficient market conditions.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.1
• /
• pp.103-110
• /
• 2022

This paper deals with portfolio optimization problem that you could lower the total risk of an investment portfolio by adding risky assets to the mix than the minimum risk of single asset. Popular Markowitz's mean-variance(MV) model construct the portfolio with the point in the efficient frontier using principle of domination where the variance is minimized for a given mean return. While this paper suggest the portfolio with minimum risk asset with non-positive(negative and uncorrelated) correlation assets to it. As a result of experiments, the proposed method shows lower risk(standard deviation) than MV.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1995.09a
• /
• pp.363-369
• /
• 1995

본 연구에서는 선형계획법 프로그램의 수치오차보정과 행렬희소도 유지를 통하여 수행 속도를 향상시키는 방안에 대해 다룬다. 수치오차를 줄이기 위 해 규모화를 도입하였으며, 계산 과정에서의 상하삼각행렬의 수치오차를 근 사적으로 측정하는 방법을 고려하였다. 기저행렬의 상하분해에 널리 사용되 는 Markowitz 순서화의 효율적인 구현에 대해 연구하였으며, Reid의 기저수 정방법의 효율성에 대해 실험적으로 검토하였다. 또, 행렬의 희소도에 의한 재역산 기준을 수립하여 수행 속도를 개선하였다.

• Journal of Information Technology and Architecture
• /
• v.9 no.1
• /
• pp.21-31
• /
• 2012

We focus on the issues of the non-linear return/risk relationship of IT investment and the balance between return and risk of IT portfolio. We develop an IT project selection model by integrating DEA models with Markowitz portfolio selection theory. The project data collected from a Fortune 100 company are used to illustrate the implementation of the model. In addition, computational experiments are conducted to demonstrate the validity of the proposed model.