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İLK HALKA ARZLARDA UZUN DÖNEM GETİRİLERİNİN TAHMİNİ: YAPAY SİNİR AĞLARI İLE İMKB İÇİN AMPİRİK BİR ÇALIŞMA

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Abstract (2. Language): 
The purpose of this study is to estimate the long run IPO (Initial Public Offerings) returns using artificial neural network (ANN) and linear regression (LR). In wide-ranging literature linear regression is commonly preferred to estimate long run IPO returns. This study applies ANN addition to LR. As a result of comparing the performance of ANN and LR, ANN has better performance than OLS for long run IPO returns in Turkey.
Abstract (Original Language): 
Bu çalışmanın amacı ĐMKB’de ilk defa halka arz edilen hisse senetlerinin uzun dönem getirilerini yapay sinir ağı kullanarak tahmin etmektir. Literatürde uzun dönem halka arz getirilerinin tahmin edilmesinde yaygın olarak Doğrusal regresyon yönteminden yararlanıldığı görülmektedir. Bu çalışmada ise doğrusal regresyon yöntemine ek olarak yapay sinir ağı teknolojisi kullanılmıştır. Uzun dönem getirileri tahmin etmede doğrusal regresyon ve yapay sinir ağı modellerinin performansları karşılaştırılmıştır. Elde edilen bulgular yapay sinir ağının uzun dönem halka arz getirilerini tahmin etmede doğrusal regresyon yönteminden daha başarılı olduğunu ortaya koymaktadır.
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