Genetik Algoritma Kullanımı ile Farklı Getiri Ölçümlerindeki Yatırım Optimizasyonu Problemi.
One of the biggest problems encountered by investors and fund managers in modern financial markets is finding a convenient investment combination. This problem framed as a portfolio optimization problem involves selection and optimal allocation of different financial assets to invest. The traditiona...
| Publicado en: | Itobiad: Journal of the Human & Social Science Researches / İnsan ve Toplum Bilimleri Araştırmaları Dergisi Vol. 10; no. 1; pp. 266 - 289 |
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| Formato: | Artículo |
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Itobiad: Journal of the Human & Social Science Researches
2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=149682839&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 149682839 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 21471185 GBL7 jtl: Itobiad: Journal of the Human & Social Science Researches / İnsan ve Toplum Bilimleri Araştırmaları Dergisi issn: 21471185 maglogo: N pubinfo: dt: 2021 vid: 10 iid: 1 pid: 87673 pub: Itobiad: Journal of the Human & Social Science Researches artinfo: ui: 149682839 10.15869/itobiad.818016 ppf: 266 ppct: 23 formats: tig: atl: Genetik Algoritma Kullanımı ile Farklı Getiri Ölçümlerindeki Yatırım Optimizasyonu Problemi. aug: au: ACAR, Elif affil: Dr. Öğr. Üyesi, Yozgat Bozok Üniversitesi, İİBF, İşletme Bölümü su: Portfolio management (Investments) Investment advisors Monte Carlo method Genetic algorithms Return on assets Stock exchanges sug: subj: Portfolio Management Investment Advice Securities and Commodity Exchanges Portfolio management (Investments) Investment advisors Monte Carlo method Genetic algorithms Return on assets Stock exchanges keyword: Excel Evolutionary Genetic Algorithm Optimization Portfolio Simulation Excel Açılım Genetik Algoritma Optimizasyon Portföy Simülasyon Excel Evolutionary Genetic Algorithm Optimization Portfolio Simulation Excel Açılım Genetik Algoritma Optimizasyon Portföy Simülasyon ab: One of the biggest problems encountered by investors and fund managers in modern financial markets is finding a convenient investment combination. This problem framed as a portfolio optimization problem involves selection and optimal allocation of different financial assets to invest. The traditional mean-variance model presented by Harry Markowitz has underlined many models used to resolve portfolio optimization problem. Although there are many instruments in estimating asset returns, expected return of an asset is calculated by arithmetic average in the mean-variance model. Different forecasting techniques instead of arithmetic average should be included in portfolio optimization process. Also, portfolio optimization problems are mostly non-linear, and the applicability of the genetic algorithm to these problems should be investigated since portfolio problem involving restrictions such as investing to maximum certain number of assets is complex. In this paper, a heuristic approach genetic algorithm is applied to the portfolio optimization problem in different return measures by Excel Solver (Evolutionary). Three different return measures based upon; average, Monte Carlo (MC) simulation and forecast returns are used for estimating the returns. It is shown this portfolio optimization problem can be solved by Excel engine if these three techniques are used as the measures of return. Data set obtained from Istanbul Stock market is applied. Along with the three techniques, performances of optimal scenarios which contain various constraints, give different degrees of importance to risk and return, create with scaled objective function, are compared with the coefficient of variation and the values realized at the future periods. Empirical results indicate Monte Carlo technique is more successful than others. The necessity of using a scaled objective function in dual-objective problems is demonstrated. It is concluded use of GA in portfolio optimization problem where scenarios should would be produced have a disadvantage in terms of time. pubtype: Academic Journal doctype: Article src: R language: Turkish refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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