Modeling of Mean-Value-at-Risk Investment Portfolio Optimization Considering Liabilities and Risk-Free Assets

被引:0
|
作者
Sukono [1 ,2 ]
Ghazali, Puspa Liza Binti [2 ]
Johansyah, Muhamad Deni [1 ]
Riaman [1 ]
Ibrahim, Riza Andrian [3 ]
Mamat, Mustafa [4 ]
Sambas, Aceng [4 ]
机构
[1] Univ Padjadjaran, Fac Math & Nat Sci, Dept Math, Sumedang 45363, Indonesia
[2] Univ Sultan Zainal Abidin, Fac Business & Management, Kuala Terengganu 21300, Malaysia
[3] Univ Padjadjaran, Fac Math & Nat Sci, Doctoral Program Math, Sumedang 45363, Indonesia
[4] Univ Sultan Zainal Abidin, Fac Informat & Comp, Kuala Terengganu 21300, Malaysia
关键词
investment portfolio; Markowitz model; risk aversion; value-at-risk; risk-free assets; liability;
D O I
10.3390/computation12060120
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper aims to design a quadratic optimization model of an investment portfolio based on value-at-risk (VaR) by entering risk-free assets and company liabilities. The designed model develops Markowitz's investment portfolio optimization model with risk aversion. Model development was carried out using vector and matrix equations. The entry of risk-free assets and liabilities is essential. Risk-free assets reduce the loss risk, while liabilities accommodate a fundamental analysis of the company's condition. The model can be applied in various sectors of capital markets worldwide. This study applied the model to Indonesia's mining and energy sector. The application results show that risk aversion negatively correlates with the mean and VaR of the return of investment portfolios. Assuming that risk aversion is in the 5.1% to 8.2% interval, the maximum mean and VaR obtained for the next month are 0.0103316 and 0.0138270, respectively, while the minimum mean and VaR are 0.0102964 and 0.0137975, respectively. The finding of this study is that the vector equation for investment portfolio weights is obtained, which can facilitate calculating investment portfolio weight optimization. This study is expected to help investors control the quality of appropriate investment, especially in some stocks in Indonesia's mining and energy sector.
引用
收藏
页数:18
相关论文
共 37 条
  • [21] Formulation of the Non-Parametric Value at Risk Portfolio Selection Problem Considering Symmetry
    Wang, Dazhi
    Chen, Yanhua
    Wang, Hongfeng
    Huang, Min
    SYMMETRY-BASEL, 2020, 12 (10): : 1 - 18
  • [22] Portfolio Optimization Using Period Value at Risk Based on Historical Simulation Method
    An, Ruizhi
    Wang, Dazhi
    Huang, Min
    Xu, Chunhui
    PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 324 - 328
  • [23] A New Approach in Multi-Objective Portfolio Optimization using Value-at-Risk based Risk Measure
    Fulga, Cristinca
    Dedu, Silvia
    2010 2ND IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND FINANCIAL ENGINEERING (ICIFE), 2010, : 765 - 769
  • [24] The optimal mean-variance investment strategy under value-at-risk constraints
    Ye, Jun
    Li, Tiantian
    INSURANCE MATHEMATICS & ECONOMICS, 2012, 51 (02): : 344 - 351
  • [25] Comments on "A mixed integer linear programming formulation of the optimal mean/Value-at-Risk portfolio problem"
    Lin, Chang-Chun
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2009, 194 (01) : 339 - 341
  • [26] A robust set-valued scenario approach for handling modeling risk in portfolio optimization
    Zhu, Shushang
    Ji, Xiaodong
    Li, Duan
    JOURNAL OF COMPUTATIONAL FINANCE, 2015, 19 (01) : 11 - 40
  • [27] Mean-risk stochastic electricity generation expansion planning problems with demand uncertainties considering conditional-value-at-risk and maximum regret as risk measures
    Tekiner-Mogulkoc, Hatice
    Coit, David W.
    Felder, Frank A.
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2015, 73 : 309 - 317
  • [28] Downside Risk and Portfolio Optimization of Energy Stocks: A Study on the Extreme Value Theory and the Vine Copula Approach
    Karmakar, Madhusudan
    Paul, Samit
    ENERGY JOURNAL, 2023, 44 (02): : 139 - 179
  • [29] Robust mean-risk portfolio optimization using machine learning-based trade-off parameter
    Min, Liangyu
    Dong, Jiawei
    Liu, Jiangwei
    Gong, Xiaomin
    APPLIED SOFT COMPUTING, 2021, 113
  • [30] Mean-value at risk portfolio efficiency: approaches based on data envelopment analysis models with negative data and their empirical behaviour
    Martin Branda
    4OR, 2016, 14 : 77 - 99