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## The Portfolio Optimization Based on Sharp Performance Ratio

#### Azize Zehra CELENLİ BASARAN [1] , Vedide Rezan USLU [2]

In recent years investors evaluate their portfolio using modern portfolio theory developed by Markowitz while in the past they evaluated portfolio types according to the traditional portfolio theory based on simple diversification. In modern portfolio theory, it has been defended that the relationships among financial assets included in the portfolio should be taken into account. In addition, the return and risk of the portfolio can be calculated by the mean-variance model. Investors always expect the maximum return and the minimum risk. Therefore they want to choose the optimum one. In Economics literature there are some measurements to evaluate the performances of the different portfolios. In this study, it is aimed at the portfolio analysis to do for the data of the BIST 30 index. For portfolio optimization, some Artificial Intelligence techniques such as the Genetic Algorithm and Particular Swarm Optimization were used for the data belonging to the year 2018. In these algorithms, different values for the parameters were tried and Sharp Performance Ratio (SPR) was used as a performance criterion. The portfolio found with the maximum SPR has been determined as the optimum portfolio. Finally, the risk and the expected return of the portfolio, the included financial assets and their weights have been obtained. The values of the parameters of the final result are considered as the best.

The portfolio Optimization, Genetic Algorithm, Particular Swarm optimization, Sharp Performance Ratio
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Birincil Dil en Matematik Ağustos Articles Orcid: 0000-0002-1027-0982Yazar: Azize Zehra CELENLİ BASARAN (Sorumlu Yazar)Kurum: ONDOKUZ MAYIS ÜNİVERSİTESİÜlke: Turkey Yazar: Vedide Rezan USLUKurum: ONDOKUZ MAYIS ÜNİVERSİTESİÜlke: Turkey Yayımlanma Tarihi : 31 Ağustos 2019
 Bibtex @araştırma makalesi { forecasting557613, journal = {Turkish Journal of Forecasting}, issn = {}, eissn = {2618-6594}, address = {Giresun Üniversitesi Fen Edebiyat Fakültesi İstatistik Bölümü, Güre Yerleşkesi, 28100 Merkez, Giresun}, publisher = {Giresun Üniversitesi}, year = {2019}, volume = {03}, pages = {7 - 14}, doi = {}, title = {The Portfolio Optimization Based on Sharp Performance Ratio}, key = {cite}, author = {Celenli Basaran, Azize Zehra and Uslu, Vedide Rezan} } APA Celenli Basaran, A , Uslu, V . (2019). The Portfolio Optimization Based on Sharp Performance Ratio . Turkish Journal of Forecasting , 03 (1) , 7-14 . Retrieved from https://dergipark.org.tr/tr/pub/forecasting/issue/50239/557613 MLA Celenli Basaran, A , Uslu, V . "The Portfolio Optimization Based on Sharp Performance Ratio" . Turkish Journal of Forecasting 03 (2019 ): 7-14 Chicago Celenli Basaran, A , Uslu, V . "The Portfolio Optimization Based on Sharp Performance Ratio". Turkish Journal of Forecasting 03 (2019 ): 7-14 RIS TY - JOUR T1 - The Portfolio Optimization Based on Sharp Performance Ratio AU - Azize Zehra Celenli Basaran , Vedide Rezan Uslu Y1 - 2019 PY - 2019 N1 - DO - T2 - Turkish Journal of Forecasting JF - Journal JO - JOR SP - 7 EP - 14 VL - 03 IS - 1 SN - -2618-6594 M3 - UR - Y2 - 2019 ER - EndNote %0 Turkish Journal of Forecasting The Portfolio Optimization Based on Sharp Performance Ratio %A Azize Zehra Celenli Basaran , Vedide Rezan Uslu %T The Portfolio Optimization Based on Sharp Performance Ratio %D 2019 %J Turkish Journal of Forecasting %P -2618-6594 %V 03 %N 1 %R %U ISNAD Celenli Basaran, Azize Zehra , Uslu, Vedide Rezan . "The Portfolio Optimization Based on Sharp Performance Ratio". Turkish Journal of Forecasting 03 / 1 (Ağustos 2019): 7-14 . AMA Celenli Basaran A , Uslu V . The Portfolio Optimization Based on Sharp Performance Ratio. TJF. 2019; 03(1): 7-14. Vancouver Celenli Basaran A , Uslu V . The Portfolio Optimization Based on Sharp Performance Ratio. Turkish Journal of Forecasting. 2019; 03(1): 7-14. IEEE A. Celenli Basaran ve V. Uslu , "The Portfolio Optimization Based on Sharp Performance Ratio", Turkish Journal of Forecasting, c. 03, sayı. 1, ss. 7-14, Ağu. 2019

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