• Title/Summary/Keyword: Portfolio Management

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Investigating the Global Financial Markets from a Social Network Analysis Perspective (소셜네트워크분석 접근법을 활용한 글로벌 금융시장 네트워크 분석)

  • Kim, Dae-Sik;Kwahk, Kee-Young
    • Journal of the Korean Operations Research and Management Science Society
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    • v.38 no.4
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    • pp.11-33
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    • 2013
  • We analyzed the structures and properties of the global financial market networks using social network analysis approach. The Minimum Spanning Tree (MST) lengths and networks of the global financial markets based on the correlation coefficients have been analyzed. Firstly, similar to the previous studies on the global stock indices using MST length, the diversification effects in the global multi-asset portfolio can disappear during the crisis as the correlations among the asset class and within the asset class increase due to the system risks. Second, through the network visualization, we found the clustering of the asset class in the global financial markets network, which confirms the possible diversification effect in the global multi-asset portfolio. Meanwhile, we found the changes in the structure of the network during the crisis. For the last one, in terms of the degree centrality, the stock indices were the most influential to other assets in the global financial markets network, while in terms of the betweenness centrality, Gold, Silver and AUD. In the practical perspective, we propose the methods such as MST length and network visualization to monitor the change of the correlation risk for the risk management of the multi-asset portfolio.

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.

Effects of Learning Activities on Application of Learning Portfolio in Nursing Management Course (간호관리학 교과에서 학습포트폴리오를 활용한 학습활동의 효과)

  • Choi, So Eun;Kim, Eun A
    • Journal of Korean Academy of Nursing
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    • v.46 no.1
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    • pp.90-99
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    • 2016
  • Purpose: This study was conducted to examine effects of a learning portfolio by identifying the learning of nursing students taking a learning portfolio-utilized nursing management class. Methods: A non-equivalent control group pretest-posttest design was used. Participants were 83 senior students taking the nursing management course in one of the Departments of Nursing at 2 Universities. Experimental group (n=42) received a learning portfolio-utilized nursing management class 15 times over 15 weeks (3 hours weekly). Self-directed learning abilities, approaches to learning and learning flow of the participants were examined with self-report structured questionnaires. Data were collected between September 2 and December 16, 2014, and were analyzed using chi-square test, Fisher's exact test, independent t-test and ANCOVA with SPSS/PC version 21.0. Results: After the intervention the experimental group showed significant increases in self-directed learning abilities, deep approaches to learning and learning flow compared to the control group. However, no significant difference was found between groups for surface approaches to learning. Conclusion: Learning activities using the learning portfolios could be effective in cultivating the learning competency for growth of knowledge, technology and professionalism by increasing personal concentration and organization ability of the nursing students so that they can react to the rapidly changing environment.

Determination Conversion Weight of Convertible Bonds Using Mean/Value-at-Risk Optimization Models (평균/VaR 최적화 모형에 의한 전환사채 주식전환 비중 결정)

  • Park, Koohyun
    • Korean Management Science Review
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    • v.30 no.3
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    • pp.55-70
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    • 2013
  • In this study we suggested two optimization models to determine conversion weight of convertible bonds. The problem of this study is same as that of Park and Shim [1]. But this study used Value-at-Risk (VaR) for risk measurement instead of CVaR, Conditional-Value-at-Risk. In comparison with conventional Markowitz portfolio models, which use the variance of return, our models used VaR. In 1996, Basel Committee on Banking Supervision recommended VaR for portfolio risk measurement. But there are difficulties in solving optimization models including VaR. Benati and Rizzi [5] proved NP-hardness of general portfolio optimization problems including VaR. We adopted their approach. But we developed efficient algorithms with time complexity O(nlogn) or less for our models. We applied examples of our models to the convertible bond issued by a semiconductor company Hynix.

Enhanced Indexation Strategy with ETF and Black-Litterman Model (ETF와 블랙리터만 모형을 이용한 인핸스드 인덱스 전략)

  • Park, Gigyoung;Lee, Youngho;Seo, Jiwon
    • Korean Management Science Review
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    • v.30 no.3
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    • pp.1-16
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    • 2013
  • In this paper, we deal with an enhanced index fund strategy by implementing the exchange trade funds (ETFs) within the context of the Black-Litterman approach. The KOSPI200 index ETF is used to build risk-controlled portfolio that tracks the benchmark index, while the proposed Black-Litterman model mitigates estimation errors in incorporating both active investment views and equilibrium views. First, we construct a Black-Litterman model portfolio with the active market perspective based on the momentum strategy. Then, we update the portfolio with the KOSPI200 index ETF by using the equilibrium return ratio and weighted averages, while devising optimization modeling for improving the information ratio (IR) of the portfolio. Finally, we demonstrate the empirical viability of the proposed enhanced index strategies with KOSPI 200 data.

Covariance Estimation and the Effect on the Performance of the Optimal Portfolio (공분산 추정방법에 따른 최적자산배분 성과 분석)

  • Lee, Soonhee
    • Journal of the Korean Operations Research and Management Science Society
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    • v.39 no.4
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    • pp.137-152
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    • 2014
  • In this paper, I suggest several techniques to estimate covariance matrix and compare the performance of the global minimum variance portfolio (GMVP) in terms of out of sample mean standard deviation and return. As a result, the return differences among the GMVPs are insignificant. The mean standard deviation of the GMVP using historical covariance is sensitive to the estimation window and the number of assets in the portfolio. Among the model covariance, the GMVP using constant systematic risk ratio model or using short sale restriction shows the best performance. The performance difference between the GMVPs using historical covariance and model covariance becomes insignificant as the historical covariance is estimated with longer estimation window. Lastly, the implied volatilities from ELW prices do not lead to superior performance to the historical variance.

R&D Opportunity Scan Framework for Information and Telecommunications Company in Aging Society (고령화 환경에서 정보통신 산업의 유망 R&D 영역 발굴 방법 설계)

  • Lee, Young-Ho;Jang, Kyu-Nam;Kim, Young-Wook;Kim, Young-Jin;Park, Myung-Soon
    • Korean Management Science Review
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    • v.25 no.3
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    • pp.59-72
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    • 2008
  • This paper proposes an R&D opportunity scan framework for information and telecommunications company in aging society. The framework consists of trend analysis, market-oriented search, technology-oriented search, and R&D Portfolio development. We identify technology themes in the market-oriented search by developing market scenarios and analyzing a new business model framework. And then we search prospective technologies in the technology-oriented recess by technology scanning and patent analysis. By matching technology themes with prospective technologies, generate an R&D portfolio. Finally, we evaluate the risk of the proposed R&D portfolio.

FUZZY RISK MEASURES AND ITS APPLICATION TO PORTFOLIO OPTIMIZATION

  • Ma, Xiaoxian;Zhao, Qingzhen;Liu, Fangai
    • Journal of applied mathematics & informatics
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    • v.27 no.3_4
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    • pp.843-856
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    • 2009
  • In possibility framework, we propose two risk measures named Fuzzy Value-at-Risk and Fuzzy Conditional Value-at-Risk, based on Credibility measure. Two portfolio optimization models for fuzzy portfolio selection problems are formulated. Then a chaos genetic algorithm based on fuzzy simulation is designed, and finally computational results show that the two risk measures can play a role in possibility space similar to Value-at-Risk and Conditional Value-at-Risk in probability space.

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A Study on the Analysis of Optimal Asset Allocation and Welfare Improvemant Factors through ESG Investment (ESG투자를 통한 최적자산배분과 후생개선 요인분석에 관한 연구)

  • Hyun, Sangkyun;Lee, Jeongseok;Rhee, Joon-Hee
    • Journal of Korean Society for Quality Management
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    • v.51 no.2
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    • pp.171-184
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    • 2023
  • Purpose: First, this paper suggests an alternative approach to find optimal portfolio (stocks, bonds and ESG stocks) under the maximizing utility of investors. Second, we include ESG stocks in our optimal portfolio, and compare improvement of welfares in the case with and without ESG stocks in portfolio. Methods: Our main method of analysis follows Brennan et al(2002), designed under the continuous time framework. We assume that the dynamics of stock price follow the Geometric Brownian Motion (GBM) while the short rate have the Vasicek model. For the utility function of investors, we use the Power Utility Function, which commonly used in financial studies. The optimal portfolio and welfares are derived in the partial equilibrium. The parameters are estimated by using Kalman filter and ordinary least square method. Results: During the overall analysis period, the portfolio including ESG, did not show clear welfare improvement. In 2017, it has slightly exceeded this benchmark 1, showing the possibility of improvement, but the ESG stocks we selected have not strongly shown statistically significant welfare improvement results. This paper showed that the factors affecting optimal asset allocation and welfare improvement were different each other. We also found that the proportion of optimal asset allocation was affected by factors such as asset return, volatility, and inverse correlation between stocks and bonds, similar to traditional financial theory. Conclusion: The portfolio with ESG investment did not show significant results in welfare improvement is due to that 1) the KRX ESG Leaders 150 selected in our study is an index based on ESG integrated scores, which are designed to affect stability rather than profitability. And 2) Korea has a short history of ESG investment. During the limited analysis period, the performance of stock-related assets was inferior to bond assets at the time of the interest rate drop.

Effects of Additional Constraints on Performance of Portfolio Selection Models with Incomplete Information : Case Study of Group Stocks in the Korean Stock Market (불완전 정보 하에서 추가적인 제약조건들이 포트폴리오 선정 모형의 성과에 미치는 영향 : 한국 주식시장의 그룹주 사례들을 중심으로)

  • Park, Kyungchan;Jung, Jongbin;Kim, Seongmoon
    • Korean Management Science Review
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    • v.32 no.1
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    • pp.15-33
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    • 2015
  • Under complete information, introducing additional constraints to a portfolio will have a negative impact on performance. However, real-life investments inevitably involve use of error-prone estimations, such as expected stock returns. In addition to the reality of incomplete data, investments of most Korean domestic equity funds are regulated externally by the government, as well as internally, resulting in limited maximum investment allocation to single stocks and risk free assets. This paper presents an investment framework, which takes such real-life situations into account, based on a newly developed portfolio selection model considering realistic constraints under incomplete information. Additionally, we examined the effects of additional constraints on portfolio's performance under incomplete information, taking the well-known Samsung and SK group stocks as performance benchmarks during the period beginning from the launch of each commercial fund, 2005 and 2007 respectively, up to 2013. The empirical study shows that an investment model, built under incomplete information with additional constraints, outperformed a model built without any constraints, and benchmarks, in terms of rate of return, standard deviation of returns, and Sharpe ratio.