• Title/Summary/Keyword: Markowitz's MV Model

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Portfolio Optimization of Diversified Investments with Minimum Risk Asset and Non-Positive Correlation Assets (최소위험 종목과 비양의 상관관계를 갖는 종목들 분산투자 포트폴리오 최적화)

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

Optimization Methodology for Sales and Operations Planning by Stochastic Programming under Uncertainty : A Case Study in Service Industry (불확실성하에서의 확률적 기법에 의한 판매 및 실행 계획 최적화 방법론 : 서비스 산업)

  • Hwang, Seon Min;Song, Sang Hwa
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.39 no.4
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    • pp.137-146
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    • 2016
  • In recent years, business environment is faced with multi uncertainty that have not been suffered in the past. As supply chain is getting expanded and longer, the flow of information, material and production is also being complicated. It is well known that development service industry using application software has various uncertainty in random events such as supply and demand fluctuation of developer's capcity, project effective date after winning a contract, manpower cost (or revenue), subcontract cost (or purchase), and overrun due to developer's skill-level. This study intends to social contribution through attempts to optimize enterprise's goal by supply chain management platform to balance demand and supply and stochastic programming which is basically applied in order to solve uncertainty considering economical and operational risk at solution supplier. In Particular, this study emphasizes to determine allocation of internal and external manpower of developers using S&OP (Sales & Operations Planning) as monthly resource input has constraint on resource's capability that shared in industry or task. This study is to verify how Stochastic Programming such as Markowitz's MV (Mean Variance) model or 2-Stage Recourse Model is flexible and efficient than Deterministic Programming in software enterprise field by experiment with process and data from service industry which is manufacturing software and performing projects. In addition, this study is also to analysis how profit and labor input plan according to scope of uncertainty is changed based on Pareto Optimal, then lastly it is to enumerate limitation of the study extracted drawback which can be happened in real business environment and to contribute direction in future research considering another applicable methodology.