Comparison of stock selection methods: An empirical research on the borsa İstanbul

dc.contributor.advisor Tokmakçıoğlu, Kaya Özdemir, Ali Sezin
dc.contributor.authorID 403142012
dc.contributor.department Business Administration 2024-01-16T11:34:39Z 2024-01-16T11:34:39Z 2023-04-12
dc.description Thesis(Ph.D.) -- Istanbul Technical University, Graduate School, 2023
dc.description.abstract Various investment instruments or index-linked financial instruments in various markets, made with reference to stock indices, cause negative returns, i.e., loss, for investors in periods when the index is declining. In some cases, while the indices follow a course in line with the country's inflation, the funds or investment instruments linked to the relevant indices may not be at the desired level in terms of generating above market returns or above inflation. Investment companies have developed stock selection models for various portfolios, by using the literature for the funds and investment instruments they have created, to protect themselves from the negative movements of indices. Portfolio analysis methods developed to obtain positive returns from financial instruments can cause negative returns even in cases where the market is stable or stagnated due to adverse economic conditions and increased risks. In addition, investments made in financial instruments that reference only indices or various indices' derivatives may cause negative returns as the index is negatively affected by the economic effects in the relevant country. The issue of stock selection is an important issue not only for large investors but also for individual investors. Moreover, some funds (such as pension funds) belonging to the indices of different markets depend on the movements of the stocks in the market. For this reason, stock selection has been one of the most important issues in finance for the last hundred years. In the literature, a wide range of stock selection models with diverse theoretical underpinnings have been developed, particularly over the past seventy years. Moreover, numerous empirical and theoretical studies have been conducted to compare the performance of these models. In this thesis, three models that have not yet been empirically compared with each other in the literature have been identified, and an empirical study has been carried out on the stocks of Borsa Istanbul indices. The models compared are as follows: (1) Markowitz model stock selection (detection of the percentage distribution of stocks in the portfolio), (2) stock selection model with second-order stochastic dominance method, (3) stock selection method with artificial neural network method. All models are models that can be considered quantitative analysis, while the utilization of financial ratios within the ANN model signifies a fundamental approach in the realm of stock selection. In first section of this thesis, a review of relevant literature on stock selection is presented, with particular emphasis on the rationale behind selecting the Turkish stock market, specifically the Borsa Istanbul. The subsequent section of this study places emphasis on literature pertaining to the pertinent models. Within the third section, the theoretical foundations underpinning Markowitz's model, Second Order Stochastic Dominance, and Artificial Neural Networks, all of which are utilized within this research, are thoroughly expounded. The fourth section of this thesis provides a detailed account of the relevant 18-year dataset, alongside an explication of the technical structure of stock selection models. Specifically, the artificial neural network stock selection model was constructed using the MATLAB programming language, while Microsoft Excel application was utilized to conduct Markowitz and Stochastic Dominance tests. The fifth section of this thesis presents the results of a comparative analysis of the aforementioned models. Specifically, return values are tabulated and compared across the models. Based on the analysis, it has been determined that the stock selection model utilizing artificial neural networks demonstrates a relatively higher return potential compared to other models. Furthermore, all three models were found to be capable of generating portfolios with returns that were between 8 to 20 times higher than the BIST-100 index. This thesis aims to achieve several objectives, namely: (1) to conduct a comparative analysis of the return performance of three stock selection models whose relative performance has not yet been evaluated in the literature, (2) to undertake a quantitative analysis of the selected models, (3) to compare the alpha returns (i.e., portfolio return – index return) within a market context such as Turkey, where the stock market is consistently influenced by political and economic events, and (4) to contribute to the literature by introducing models that demonstrate the potential to generate portfolios with returns that surpass the market or index return. Ph. D.
dc.language.iso en_US
dc.publisher Graduate School
dc.sdg.type Goal 8: Decent Work and Economic Growth
dc.subject empirical portfolio
dc.subject ampirik portföy
dc.subject modern portfolio theory
dc.subject modern portföy teorisi
dc.subject optimal portfolio
dc.subject optimum portföy
dc.subject market portfolio
dc.subject pazar portföyü
dc.title Comparison of stock selection methods: An empirical research on the borsa İstanbul
dc.title.alternative Hisse senedi seçimi modellerini karşılaştırma: Borsa İstanbul hisse senetleri üzerinde ampirik bir uygulama
dc.type Doctoral Thesis
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