Document Type : Research Paper
Authors
Abstract
Modifications are an integrated part of economic evolution in financial section which include reforming the capital market structure, innovating in tools and an environment with more comprehensive discipline. Two dominant schools of thought in the literature on stock markets are fundamental and technical analysis. Selection the portfolio would be so important. So we use both fundamental and technical analysis to evaluate companies' stock and then in order to form a portfolio which consider different risk states and investor’s preferences utilize Mamdani Fuzzy and mixed integer linear programming model. The reasons for the use Mamdani Fuzzy system are its capability of working in vague environment and using human knowledge and for mixed integer linear programming model is its capability in finding the optimum solution among the several available ones. The results of evaluating the performance of formed portfolio for three cases of Risk averse, Risk neutral and Risk prone investor show that the performance of proposed portfolio is positive and proper, but in a more accurate scale the formed portfolio has a more proper condition for the risk averse investor.
Keywords
Fama, E. & Ferench, K. The Capital Asset Pricing Model: Theory and Evidence. Journal of Economic Perspectives 18. P:20. 2003
Maknickiene, N. Selection of orthogonal investment portfolio using Evolino RNN trading model. Social and Behavioral Sciences. (110) . 1158 – 1165. 2014.
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Strong، Robert A. Portfolio Construction, Management & Protection, 2d Edition، South-Western College، P .431. 2000.
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Alvarz Grima, M.; Bruines, PA.; Verhoef, p. Modeling tunnel machine performance by neure-fuzzy methods. Tunnelling and underground space technology. Pp. 259-269. 2000.
Asmuni, H.. Fuzzy methodologies for automated university. Timetabling Solution Construction and Evaluation. Ph.D Thesis. University of Nottingham, UK. P. 71. 2009.
Baralis, E.; cagliero, L.; Garza, P. Planning stock portfolios by means of weighted frequent itemsets. Expert Systems with Applications Volume 86, 15 November, Pages 1-17. 2017
Chong, H.Y.; Yap, H.; Loong, Y. Fuzzy-based risk prioritization for a hydrogen refueling facility in Malaysia. Applied Physics & Engineering. (24) Pp. 565-573. 2013.
Fernández, A. & Gómez, S. Portfolio selection using neural networks. Computers & Operations Research 34 ,1177–1191. 2007
Gupta, P.; Inuiguchi, M. & Mehlawat, M. A hybrid approach for constructing suitable and potimal portfolios. Expert Systems with Applications, 38 (5): 5620., 908–920. 2013.
Karsak, E. Fuzzy multiple objective programming framework to prioritize decision requirements in prioritize function deployment. Computers quality function deployment, computers & industrial engineering (47), 149-163. 2004.
Levy,H; Levy, M. The benefits of differential variance- based constraints in portfolio optimization. European Journal of Operational Research, Volume 234, Issue 2, PP. 372-381. 2014
Rada, R. Expert systems and evolutionary computing for financial investing: A review. Expert Systems with Applications, 34(4), 2232–2240. 2008.
Reilly, F. & Brown, C Investment Analysis and Portfolio Management. Publisher: Cengage Learning; 10 edition. P. 840. 2011.
Xidonas, P. & Psarras, J. Equity portfolio management within the MCDM frame: A literature review. International Journal of Banking, Accounting and Finance, 1(3), 285–309. 2009.
Yunusoglu, G. & Selim, H. A fuzzy rule based expert system for stock evaluation and portfolio construction: An application to Istanbul Stock Exchange. Expert Systems with Applications. (40). 908-920. 2013.
Zhou, R., Yang, Z., Yu, M., Ralescu, D. A.,. A portfoliooptimization model based on informationentropy and fuzzy time series. Fuzzy Optimization and Decision Making, 14(4), 381-397. 2015
Zhang, WG. & Nic, ZK. On admissible efficient portfolio selection problem. Applied Mathematic and Computations. 159 (2): 357-371. 2004.
Mamdani, E.H. & Assilian, S. (1975). An Experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7, 1-13. 1975.
Ross, T.J. Fuzzy logic with engineering application john wiley & sons. 2005
Fama, E. & Ferench, K. The Capital Asset Pricing Model: Theory and Evidence. Journal of Economic Perspectives 18. P:20. 2003
Maknickiene, N. Selection of orthogonal investment portfolio using Evolino RNN trading model. Social and Behavioral Sciences. (110) . 1158 – 1165. 2014.
Markowitz H. Portfolio selection; Journal of Finance: 77-91. 1952.
Strong، Robert A. Portfolio Construction, Management & Protection, 2d Edition، South-Western College، P .431. 2000.
Yunusoglu, G. & Selim, H. A fuzzy rule based expert system for stock evaluation and portfolio construction: An application to Istanbul Stock Exchange. Expert Systems with Applications. (40). 908-920. 2013.
Alvarz Grima, M.; Bruines, PA.; Verhoef, p. Modeling tunnel machine performance by neure-fuzzy methods. Tunnelling and underground space technology. Pp. 259-269. 2000.
Asmuni, H.. Fuzzy methodologies for automated university. Timetabling Solution Construction and Evaluation. Ph.D Thesis. University of Nottingham, UK. P. 71. 2009.
Baralis, E.; cagliero, L.; Garza, P. Planning stock portfolios by means of weighted frequent itemsets. Expert Systems with Applications Volume 86, 15 November, Pages 1-17. 2017
Chong, H.Y.; Yap, H.; Loong, Y. Fuzzy-based risk prioritization for a hydrogen refueling facility in Malaysia. Applied Physics & Engineering. (24) Pp. 565-573. 2013.
Fernández, A. & Gómez, S. Portfolio selection using neural networks. Computers & Operations Research 34 ,1177–1191. 2007
Gupta, P.; Inuiguchi, M. & Mehlawat, M. A hybrid approach for constructing suitable and potimal portfolios. Expert Systems with Applications, 38 (5): 5620., 908–920. 2013.
Karsak, E. Fuzzy multiple objective programming framework to prioritize decision requirements in prioritize function deployment. Computers quality function deployment, computers & industrial engineering (47), 149-163. 2004.
Levy,H; Levy, M. The benefits of differential variance- based constraints in portfolio optimization. European Journal of Operational Research, Volume 234, Issue 2, PP. 372-381. 2014
Rada, R. Expert systems and evolutionary computing for financial investing: A review. Expert Systems with Applications, 34(4), 2232–2240. 2008.
Reilly, F. & Brown, C Investment Analysis and Portfolio Management. Publisher: Cengage Learning; 10 edition. P. 840. 2011.
Xidonas, P. & Psarras, J. Equity portfolio management within the MCDM frame: A literature review. International Journal of Banking, Accounting and Finance, 1(3), 285–309. 2009.
Yunusoglu, G. & Selim, H. A fuzzy rule based expert system for stock evaluation and portfolio construction: An application to Istanbul Stock Exchange. Expert Systems with Applications. (40). 908-920. 2013.
Zhou, R., Yang, Z., Yu, M., Ralescu, D. A.,. A portfoliooptimization model based on informationentropy and fuzzy time series. Fuzzy Optimization and Decision Making, 14(4), 381-397. 2015
Zhang, WG. & Nic, ZK. On admissible efficient portfolio selection problem. Applied Mathematic and Computations. 159 (2): 357-371. 2004.
Mamdani, E.H. & Assilian, S. (1975). An Experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7, 1-13. 1975.
Ross, T.J. Fuzzy logic with engineering application john wiley & sons. 2005
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