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Journals / Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi / 2009 / Cilt: 26 - Sayı: 1

STOCK RETURN FORECASTS WITH ARTIFICIAL NEURAL NETWORK MODELS

YAPAY SİNİR AĞLARI MODELLERİ İLE HİSSE SENEDİ GETİRİ TAHMİNLERİ

Emin AVCI
Pages
443–461
Publication Date
2015-03-11
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results of the study presented that the neural network models could beat the buy-and-hold strategy for most of the periods under investigation.

📌 3 Key Takeaways

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Objective & Hypothesis:Although several studies have examined the power of the artificial neural network models in predicting Istanbul Stock Exchange (ISE) indexes, there is no evidence on the predictive power of these models for ISE traded stock returns.
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Key Findings & Data:This paper intends to examine the power of neural network models in prediction of daily returns of the selected stocks from ISE-30 index.
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Conclusion & Impact:The results of the study presented that the neural network models could beat the buy-and-hold strategy for most of the periods under investigation.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Yapay Sinir Ağları Modelleri · Hisse Senedi Getirilerinin Tahmin Edilmesi · Çok katmanlı Algılama Modelleri

Abstract

Although several studies have examined the power of the artificial neural network models in predicting Istanbul Stock Exchange (ISE) indexes, there is no evidence on the predictive power of these models for ISE traded stock returns. This paper intends to examine the power of neural network models in prediction of daily returns of the selected stocks from ISE-30 index. The performance of the neural network models are evaluated by trading profits. The results of the study presented that the neural network models could beat the buy-and-hold strategy for most of the periods under investigation.

Özet

İstanbul Menkul Kıymetler Borsası (İMKB) endekslerinin yapay sinir ağları modelleri ile tahmin edilebilirliği çeşitli çalışmalarda irdelenmiştir. Fakat söz konusu modellerle İMKB’de işlem gören hisse senetlerinin getirileri tahmin edilebilirliği üzerine bulgular bulunmamaktadır. Bu çalışmada yapay sinir ağları modellerinin, IMKB-30 endeksi içersinden seçilmiş hisse senetlerinin günlük getirilerini tahmin güçleri araştırılacaktır. Modellerin tahmin güçleri,işlem karlılık ölçütü doğrultusunda değerlendirilecektir. Çalışmanın sonuçları yapay sinir ağları modellerinin incelenen dönemlerin büyük çoğunluğunda al-ve-tut stratejisine üstünlük sağladıklarını göstermiştir.

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Cite This Article

AVCI, E. (2015). STOCK RETURN FORECASTS WITH ARTIFICIAL NEURAL NETWORK MODELS. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, Cilt: 26 - Sayı: 1, 443–461. https://ajindex.com/articles/6698

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