• Title/Summary/Keyword: Markowitz portfolio theory

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Investment Performance of Markowitz's Portfolio Selection Model in the Korean Stock Market (한국 주식시장에서 비선형계획법을 이용한 마코위츠의 포트폴리오 선정 모형의 투자 성과에 관한 연구)

  • Kim, Seong-Moon;Kim, Hong-Seon
    • Korean Management Science Review
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    • v.26 no.2
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    • pp.19-35
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    • 2009
  • This paper investigated performance of the Markowitz's portfolio selection model with applications to Korean stock market. We chose Samsung-Group-Funds and KOSPI index for performance comparison with the Markowitz's portfolio selection model. For the most recent one and a half year period between March 2007 and September 2008, KOSPI index almost remained the same with only 0.1% change, Samsung-Group-Funds showed 20.54% return, and Markowitz's model, which is composed of the same 17 Samsung group stocks, achieved 52% return. We performed sensitivity analysis on the duration of financial data and the frequency of portfolio change in order to maximize the return of portfolio. In conclusion, according to our empirical research results with Samsung-Group-Funds, investment by Markowitz's model, which periodically changes portfolio by using nonlinear programming with only financial data, outperformed investment by the fund managers who possess rich experiences on stock trading and actively change portfolio by the minute-by-minute market news and business information.

Developing an Investment Framework based on Markowitz's Portfolio Selection Model Integrated with EWMA : Case Study in Korea under Global Financial Crisis (지수가중이동평균법과 결합된 마코위츠 포트폴리오 선정 모형 기반 투자 프레임워크 개발 : 글로벌 금융위기 상황 하 한국 주식시장을 중심으로)

  • Park, Kyungchan;Jung, Jongbin;Kim, Seongmoon
    • Journal of the Korean Operations Research and Management Science Society
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    • v.38 no.2
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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.

The Optimization of the Production Ratio by the Mean-variance Analysis of the Chemical Products Prices (화학 제품 가격의 변동으로 인한 위험을 최소화하며 수익을 극대화하기 위한 생산 비율 최적화에 관한 연구)

  • Park, Jeong-Ho;Park, Sun-Won
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.12
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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.

Optimal Portfolio Models for an Inefficient Market

  • GINTING, Josep;GINTING, Neshia Wilhelmina;PUTRI, Leonita;NIDAR, Sulaeman Rahman
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.2
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    • pp.57-64
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    • 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.

Black-Litterman Portfolio with K-shape Clustering (K-shape 군집화 기반 블랙-리터만 포트폴리오 구성)

  • Yeji Kim;Poongjin Cho
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.4
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    • pp.63-73
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    • 2023
  • This study explores modern portfolio theory by integrating the Black-Litterman portfolio with time-series clustering, specificially emphasizing K-shape clustering methodology. K-shape clustering enables grouping time-series data effectively, enhancing the ability to plan and manage investments in stock markets when combined with the Black-Litterman portfolio. Based on the patterns of stock markets, the objective is to understand the relationship between past market data and planning future investment strategies through backtesting. Additionally, by examining diverse learning and investment periods, it is identified optimal strategies to boost portfolio returns while efficiently managing associated risks. For comparative analysis, traditional Markowitz portfolio is also assessed in conjunction with clustering techniques utilizing K-Means and K-Means with Dynamic Time Warping. It is suggested that the combination of K-shape and the Black-Litterman model significantly enhances portfolio optimization in the stock market, providing valuable insights for making stable portfolio investment decisions. The achieved sharpe ratio of 0.722 indicates a significantly higher performance when compared to other benchmarks, underlining the effectiveness of the K-shape and Black-Litterman integration in portfolio optimization.

Selecting Information Technology Projects in Non-linear Risk/Return Relationships of IT Investment

  • Cho, Wooje;Song, Minseok
    • Journal of Information Technology and Architecture
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    • v.9 no.1
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    • pp.21-31
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    • 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.

Development and Evaluation of an Investment Algorithm Based on Markowitz's Portfolio Selection Model : Case Studies of the U.S. and the Hong Kong Stock Markets (마코위츠 포트폴리오 선정 모형을 기반으로 한 투자 알고리즘 개발 및 성과평가 : 미국 및 홍콩 주식시장을 중심으로)

  • Choi, Jaeho;Jung, Jongbin;Kim, Seongmoon
    • Korean Management Science Review
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    • v.30 no.1
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    • pp.73-89
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    • 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.

Decision Support System for Mongolian Portfolio Selection

  • Bukhsuren, Enkhtuul;Sambuu, Uyanga;Namsrai, Oyun-Erdene;Namsrai, Batnasan;Ryu, Keun Ho
    • Journal of Information Processing Systems
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    • v.18 no.5
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    • pp.637-649
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    • 2022
  • Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizing related risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocks portfolio selection model. This model is based on data mining clustering techniques that reflect the ensuing impact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selected stock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocks that were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns and risks, we have used k-means clustering techniques. We have combined both k-means clustering with Markowitz's portfolio theory to create an optimal and efficient portfolio. We constructed an efficient frontier, creating 15 portfolios, and computed the weight of stocks in each portfolio. From these portfolio options, the investor is given a choice to choose any one option.

Optimal Transmission Expansion Planning Considering the Uncertainties of the Power Market

  • Bae, In-Su;Son, Min-Kyun;Kim, Jin-O
    • Journal of Electrical Engineering and Technology
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    • v.5 no.2
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    • pp.239-245
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    • 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.

Optimal Transmission Expansion Planning Considering the Uncertainties of Power Market (전력시장 불확실성을 고려한 최적 송전시스템 확장계획)

  • Son, Min-Kyun;Kim, Jin-O
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.4
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    • pp.560-566
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    • 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.