Research Article

Financial Portfolio Optimization using Monte Carlo and Operation Research

by  Noureen M. Noaman, Mohamed A. El-Dosuky, Abdelrahman Karawia
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Issue 34
Published: Dec 2020
Authors: Noureen M. Noaman, Mohamed A. El-Dosuky, Abdelrahman Karawia
10.5120/ijca2020920896
PDF

Noureen M. Noaman, Mohamed A. El-Dosuky, Abdelrahman Karawia . Financial Portfolio Optimization using Monte Carlo and Operation Research. International Journal of Computer Applications. 175, 34 (Dec 2020), 43-46. DOI=10.5120/ijca2020920896

                        @article{ 10.5120/ijca2020920896,
                        author  = { Noureen M. Noaman,Mohamed A. El-Dosuky,Abdelrahman Karawia },
                        title   = { Financial Portfolio Optimization using Monte Carlo and Operation Research },
                        journal = { International Journal of Computer Applications },
                        year    = { 2020 },
                        volume  = { 175 },
                        number  = { 34 },
                        pages   = { 43-46 },
                        doi     = { 10.5120/ijca2020920896 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2020
                        %A Noureen M. Noaman
                        %A Mohamed A. El-Dosuky
                        %A Abdelrahman Karawia
                        %T Financial Portfolio Optimization using Monte Carlo and Operation Research%T 
                        %J International Journal of Computer Applications
                        %V 175
                        %N 34
                        %P 43-46
                        %R 10.5120/ijca2020920896
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Financial portfolio optimization is a difficult problem as it deals with many variables. Modern Portfolio Theory (MPT) is used for minimizing risk for a specific expected return. Many approaches are proposed to optimize portfolios. This paper proposes financial portfolio optimization using Monte Carlo and operation research. Results show an effective financial portfolio optimization.

References
  • KONNO, Hiroshi; WAKI, Hayato; YUUKI, Atsushi. Portfolio optimization under lower partial risk measures. Asia-Pacific Financial Markets, 2002, 9.2: 127-140.‏
  • Markowitz, Harry. Portfolio Selection. Journal of Finance, March 1952.
  • Esfahani, Hamed Nasr, Mohammad hossein Sobhiyah, and Vahid Reza Yousefi. Project portfolio selection via harmony search algorithm and modern portfolio theory. Procedia-Social and Behavioral Sciences 2016, 226: 51-58.
  • SHARPE, William F. The sharpe ratio. Journal of portfolio management, 1994, 21.1: 49-58.‏
  • PONSICH, Antonin; JAIMES, Antonio Lopez; COELLO, Carlos A. Coello. A survey on multi-objective evolutionary algorithms for the solution of the portfolio optimization problem and other finance and economics applications. IEEE Transactions on Evolutionary Computation, 2012, 17.3: 321-344.‏
  • ΖΈΝΙΟΣ, Σταύρος Α. (ed.). Financial optimization. Cambridge university press, 1996.‏
  • DEMIGUEL, Victor, et al. A generalized approach to portfolio optimization: Improving performance by constraining portfolio norms. Management science, 2009, 55.5: 798-812.‏
  • RICHARDSON, Henry R. A minimum variance result in continuous trading portfolio optimization. Management Science, 1989, 35.9: 1045-1055.‏
  • BANK, Peter; BAUM, Dietmar. Hedging and portfolio optimization in financial markets with a large trader. Mathematical Finance: An International Journal of Mathematics, Statistics and Financial Economics, 2004, 14.1: 1-18.‏
  • BJÖRK, Tomas; MURGOCI, Agatha; ZHOU, Xun Yu. Mean–variance portfolio optimization with state‐dependent risk aversion. Mathematical Finance: An International Journal of Mathematics, Statistics and Financial Economics, 2014, 24.1: 1-24.
  • TRIPPI, Robert R.; PREFACE BY-LEE, Jae K. Artificial intelligence in finance and investing: state-of-the-art technologies for securities selection and portfolio management. McGraw-Hill, Inc., 1995.‏‏
  • Lin, Chi-Ming, and Mitsuo Gen. An effective decision-based genetic algorithm approach to multi-objective portfolio optimization problem. Applied Mathematical Sciences 2007, no. 5: 201-210.
  • Dimmock, Stephen G., Neng Wang, and Jinqiang Yang. The endowment model and modern portfolio theory. No. w25559. National Bureau of Economic Research, 2019.
  • Grasse, Nathan J., Kayla M. Whaley, and Douglas M. Ihrke. Modern portfolio theory and nonprofit arts organizations: Identifying the efficient frontier. Nonprofit and Voluntary Sector Quarterly 2016, 45, no. 4: 825-843.
  • deLlano-Paz, Fernando, Anxo Calvo-Silvosa, Susana Iglesias Antelo, and Isabel Soares. Energy planning and modern portfolio theory: A review. Renewable and Sustainable Energy Reviews 2017, 77 : 636-651.
  • Runting, Rebecca K., Hawthorne L. Beyer, Yann Dujardin, Catherine E. Lovelock, Brett A. Bryan, and Jonathan R. Rhodes. Reducing risk in reserve selection using Modern Portfolio Theory: Coastal planning under sea‐level rise. Journal of applied ecology 2018, 55, no. 5 : 2193-2203.
  • MCLEISH, Don L. Monte Carlo simulation and finance. John Wiley & Sons, 2011.‏
  • KANT, Elaine; RANDALL, Curt. System and method for financial instrument modeling and using Monte Carlo simulation. U.S. Patent No 6,772,136, 2004.‏
  • GLASSERMAN, Paul. Monte Carlo methods in financial engineering. Springer Science & Business Media, 2013.‏
  • . PAPAGEORGIOU, Anargyros; TRAUB, J. F. Beating monte carlo. Risk, 1996, 9.6: 63-65.‏
  • . CREAL, Drew. A survey of sequential Monte Carlo methods for economics and finance. Econometric reviews, 2012, 31.3: 245-296.‏
  • DIXON, Matthew; ZUBAIR, Mohammad. Calibration of stochastic volatility models on a multi-core CPU cluster. In: Proceedings of the 6th Workshop on High Performance Computational Finance. 2013. p. 1-7.‏
  • LOPEZ DE PRADO, Marcos. A Journey Through the Mathematical Underworld of Portfolio Optimization. Available at SSRN 2214771, 2013.‏
  • VO, Nhi NY, et al. Deep learning for decision making and the optimization of socially responsible investments and portfolio. Decision Support Systems, 2019, 124: 113097.
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Financial Portfolio Optimization Monte Carlo

Powered by PhDFocusTM