Provide a robust planning model Possibility to select a stock portfolio based on Sharp ratio
Subject Areas : Financial Knowledge of Securities AnalysisMaghsoud Amiri 1 , Mohammad Saeed Heidary 2
1 - Prof. Faculty of management and accounting, Allameh Tabataba'i University, Tehran, Iran
2 - Ph.D. student of financial management, Faculty of management and accounting, Allameh Tabataba'i University, Tehran, Iran
Keywords: Stable feasibility planning, Sharp Ratio, portfolio optimization, Fuzzy optimization,
Abstract :
Portfolio selection and asset management is one of the most important financial issues that seeks to distribute a specified budget over multiple time periods between available assets in such a way that the return of the portfolio is maximized and, at the same time, its risk does not exceed a certain amount. In this paper, we first propose a nonlinear mathematical programming model for Portfolio selection to maximize Sharpe ratios of stocks. Then, due to the uncertain nature of the input parameters of such a problem, a new robust possibilistic programming model has been developed, which is capable of adjusting the robust degree of output decisions to the uncertainty of the parameters. The proposed model was first tested and evaluated on 42 companies active in the Tehran stock market. In the end, the computational results of the proposed model show the high performance and the utility of the robust possibilistic programming model.
* Alem, D. J., Morabito, R., (2012), "Production planning in furniture settings via robust optimization", Computers & Operations Research 39 (2),139-150.
* ayub, Usman & Shah, Syed Zulfiqar Ali & Abbas, Qaisar, 2015. "Robust analysis for downside risk in portfolio management for a volatile stock market," Economic Modelling, Elsevier, vol. 44(C), pages 86-96.
* Balbas, A., Balbas, B. and Balbas, R., “Good deals and benchmarks in robust portfolio selection”, European Journal of Operational Research,250(2), (2016), 666-678.
* Ioannis Baltas, Anastasios Xepapadeas, Athanasios N. Yannacopoulos. “Robust portfolio decisions for financial institutions”. Journal of Dynamics & Games, 2018, 5 (2) : 61-94. Chang, T. J., Yang, S. C., & Chang, K. J. (2009)." Portfolio optimization problems in different risk measures using genetic algorithm". Expert Systems with Applications, 36(7), 10529-10537
* Dantzig G, Infanger G (1993). “Multi-stage stochastic linear programs for portfolio optimization”. Ann. Oper. Res., 45(1): 59-76.
* Elton, E. J., & Gruber, M. J. 1974. “On the optimality of some multiperiod portfolio selection criteria”. Journal of Business, 231-243.
* Fan, A., & Palaniswami, M. 2001. “Stock selection using support vector machines. In Neural Networks”, 2001. Proceedings. IJCNN'01. International Joint Conference on (Vol. 3, pp. 1793-1798). IEEE.
* Fabozzi Frank J., Woo Chang Kim and Jang Ho Kim “Deciphering robust portfolios” Journal of Banking & Finance, 2014, vol. 45, issue C, 1-8
* Fabozzi، frank j. kolm، petter n. pachamanova، dessislava a. focardi، sergio m. 2007. “Robust Portfolio Optimization and Management” ، John Wiley & Sons، Inc.
* Ghosh, Amitava Mahanti,Ambuj “Investment Portfolio Management: A Review from 2009 to 2014” Global Business and Social Science Research Conference 23 -24 June 2014
* Haack, S., 1979. Do we need fuzzy logic? Int. J. Man Mach. Stud.11, 437–445.
* Hakansson, N. H. 1971. “Multi-Period Mean-Variance Analysis: Toward A General Theory of Portfolio Choice”. The Journal of Finance, 26(4), 857-884.
* Huang, K. Y. (2009). "Application of VPRS model with enhanced threshold parameter selection mechanism to automatic stock market forecasting and portfolio selection". Expert Systems with Applications, 36(9), 11652-11661
* Kendall, G., & Su, Y. 2005. “A Particle Swarm Optimisation Approach in the Construction of Optimal Risky Portfolios”. In Artificial Intelligence and Applications (pp. 140-145).
* lintner, J. (1965), “The valuation of risk assets on the selection of risky investments in stock portfolios and capital budgets”, Review of Economics and Statisti cs47: 13-37
* Lin, P. C., & Ko, P. C. 2009. “Portfolio value-at-risk forecasting with GA-based extreme value theory”. Expert Systems with Applications, 36(2), 2503-2512.
* Li, D., & Ng, W. L. 2000. “Optimal Dynamic Portfolio Selection: Multiperiod Mean‐Variance Formulation”. Mathematical Finance, 10(3), 387-406.
* Loraschi, A., Tomassini, M., Tettamanzi, A., & Verda, P. 1995. “Distributed genetic algorithms with an application to portfolio selection problems”. In Artificial neural nets and genetic algorithms (pp. 384-387). Springer Vienna.
* Markowitz,H. (1952) "Portfolio selection," Journal of Finance, 7(1), 77–91.
* Montazer, G. A & Fasanghari, M. (2010). "Design and implementation of fuzzy expert system for Tehran Stock Exchange portfolio recommendation", Expert Systems with Applications, 37(9), 6138-6147.
* Mossin, J. 1968. “Optimal multiperiod portfolio policies”. Journal of Business,41(2), 215.
* Pishvaee, M.S., Razmi, J., and Torabi, S., (2012), "Robust possibilistic programming for socially responsible supply chain network design: A new approach", Fuzzy sets and systems 206, 1-20
* Pishvaee, M.S., Khanjarpanah, H., (2017), “A fuzzy robust programming approach to multi-objective portfolio optimisation problem under uncertainty”, International Journal of Mathematics in Operational Research, 2018 Vol.12 No.1, pp.45 - 65
* Sharpe, William, (1967)," Portfolio Analysis ", Journal of Financial and Quantitative Analysis, 2(2), 76-84
* Sharpe, W. F. (1964), “Capital asset prices: A theory of market equilibrium under conditions of risk”, Journal of Finance19: 425-442.
* Sharpe, W. F. 1967. “A linear programming algorithm for mutual fund portfolio selection”. Management Science, 13(7), 499-510.
* Sharpe, w (1963)."a simplified model for portfolio analysis" management science, 9, 277-293
* Samuelson, P. 1969. “Lifetime portfolio selection by dynamic stochastic programming”. The Review of Economics and Statistics, Vol. 51, No. 3 (Aug., 1969), pp. 239-246
* S.J. Sadjadi, S.M. Seyedhosseini, Kh. Hassanlou (2011), " Fuzzy multi period portfolio selection with different rates for borrowing and Lending", Applied Soft Computing 11, 3821–3826
* Soleimani, H., Golmakani, H. R., & Salimi, M. H. (2009). "Markowitz-based portfolio selection with minimum transaction lots, cardinality constraints and regarding sector capitalization using genetic algorithm". Expert Systems with Applications, 36(3), 5058-5063.
* Tiryaki, F., & Ahlatcioglu, B. (2009). "Fuzzy portfolio selection using fuzzy analytic hierarchy process". Information Sciences, 179(1), 53-69.
* TANAGA, H., GUO, P., TURKSEN, B., (2000). "Portfolio selection based on fuzzy probabilities and possibility distributions", Fuzzy sets and systems 111 (3), 387–397.
* Xia, Y., Liu, B., Wang, S., & Lai, K. K. 2000. “A model for portfolio selection with order of expected returns”. Computers & Operations Research, 27(5), 409-422.
* Woo ChangKim, Jang HoKim, Frank J.Fabozzi (2014), " Deciphering robust portfolios ", Journal of Banking & Finance 45, 1-8
* Woo Chang Kim, Frank Fabozzi (2014), "Controlling portfolio skewness and kurtosis without directly optimizing third and fourth moments", Economics Letters, 122(2), 154-158
* Zakamouline, V., & Koekebakker, S. 2009. “Portfolio performance evaluation with generalized Sharpe ratios: Beyond the mean and variance”. Journal of Banking & Finance, 33(7), 1242-1254.
_||_