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HİSSE SENETLERİNİN KORELASYON UZAKLIKLARINA DAYALI OLARAK KÜMELENMESİ

CLUSTERING OF STOCKS BASED ON CORRELATION DISTANCES

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Abstract (2. Language): 
This study is aimed at demonstrating cluster analysis can be used to establish a starting point of efficient portfolio selection for investors in order to decrease portfolio risk. Weekly percentage incomes which were derived from daily closing prices of selected stocks from ISE National 50 Index were used as a dataset of this study. Hierarchical cluster analysis was employed and complete linkage method and pearson correlations measure were used in order to establish clusters. It is seen from the results that stocks were placed in different clusters than sectoral clusters. High correlations were observed between stocks in same clusters. To decrease the portfolio risk, this study proposes that stocks could be selected from different clusters that derived by using the method in the present study.
Abstract (Original Language): 
Bu çalışmada yatırımcıların portföy seçiminde portföy riskinin azaltılmasına yönelik menkul kıymet değerlendirmesinde kümeleme analizi kullanılarak etkin bir portföy seçimi için başlangıç noktası oluşturulabileceğinin gösterilmesi amaçlanmıştır. Araştırmada IMKB Ulusal 50 endeksinde yer alan seçilmiş hisse senetlerinin günlük kapanış fiyatlarından elde edilen haftalık yüzdelik getiriler kullanılarak korelasyonlara dayalı ve tam bağıntı yöntemini kullanan hiyerarşik kümeleme analizi uygulanmıştır. Uygulama sonucunda getirileri açısından firmaların sektörel kümelenmeden daha farklı kümelendiği ve elde edilen kümelerin kendi içinde yüksek korelasyon gösterdikleri görülmüştür. Portföy riskinin azaltılmasında, menkul kıymetlerin bu tür bir çalışmayla elde edilecek farklı kümelerden seçilmesi önerilmektedir.
395-400

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