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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 43890 (02)
- University: Sharif University of Technology
- Department: Mathematical Sciences
- Advisor(s): Rmezanian, Rasoul
- Abstract:
- Portfolio is a collection of different stocks for investment. The investors' objectives in portfolio formation are to get the highest return against exposure to the lowest risk. Portfolio Optimization Problem is one of the most complicated problems in investment and finance. It may be simply explained as follows: Let's imagine a set of N stocks for selection. We would like to see what percentage of the total amount of investment should be dedicated to each stock to maximize portfolio's total return and minimize its total risk.
Portfolio Optimization Problem is a NP-Hard problem and generally there exists no polynomial-time deterministic algorithm to find a precise solution to such a problem; therefore, using intelligent and metaheuristic methods may be considered.
In this thesis, a new metaheuristic method called Cuckoo Search is used to solve the Portfolio Optimization Problem. This search method, introduced by X.Yang in 2009, was inspired from implantation process of some cuckoo species.
This research tries to form optimal portfolio of the stocks of 50 top companies of Tehran Stock Exchange from January 2010 to December 2011 by applying the Cuckoo Search method for Portfolio Optimization Problem.
According to the special characteristics of Iraninvestment market, many theories proposed in foreign markets are not applicable in Iran. The model used in this thesis to solve the Portfolio Optimization Problem is Markowitz Mean-Variance model in which the return and risk are measured with mean and variance, respectively. The result of previous studies show the compatibility of this model with the characteristics of Tehran Stock Exchange Organization, where the algorithm proposed in this thesis is implemented.
Finally, the convergence speed of the proposed algorithm is compared with the Genetic Algorithm, Genetic-NeldermeadHybridizedAlgorithm, PSO and Imperialist Competitive Algorithm. The results of this comparison indicate that the algorithm offered in this research is convergent to the optimal pointin much less period of time, and obtains more precise solutions with less coefficient errors - Keywords:
- Optimization ; Stock Portfolio ; Efficiency ; Risk ; Meta Heuristic Algorithm ; Tehran Stock Exchange ; Cuckoo Search
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