Borsada İşlem Sırası Kapanmaları için Tahmin Modeli: Borsa İstanbul Örneği

Amaç – Araştırmanın amacı, Borsa İstanbul Pay Piyasası’ndaki zorunlu işleme kapanmaların tahmininde kullanılacak bir model geliştirilmesi ve tahmin gücünün test edilmesidir. Yöntem – Araştırmanın kapsamını, 2000-2018 döneminde Borsa İstanbul’da işlem sırası kapatılan 79 şirket oluşturmaktadır. Kontrol grubu ile beraber, araştırmanın örneklemine 147 şirket dahil edilmiştir. Model geliştirilmesinde başarısızlık literatüründen yararlanılmıştır. Modele seçilecek değişkenler; “likidite”, “karlılık”, “mali yapı ve yükümlülükleri karşılama”, “çalışma etkinliği”, “piyasa çarpanları” ve “büyüklük” olmak üzere altı boyutta toplanmıştır. Çalışmada, araştırma örneklemindeki veri sayısının kısıtlı olması da dikkate alınarak, lojistik regresyon yöntemi kullanılmıştır. Lojistik modelde yer alacak değişkenlerin belirlenmesinde, korelasyon katsayıları ile birlikte değişkenlerin boyutları ve literatürdeki kullanım sayıları da dikkate alınmıştır. 22 finansal oran arasından yapılan seçim işlemi sonunda, 11 finansal oran bağımsız değişken olarak modele eklenmiştir. Bulgular – Model sonuçlarının beklentilerle ve literatürle uyumlu olduğu görülmüştür. En uygun kesme değeri olan 0,5’e göre model, gözlemlerin %83’ünü doğru bir şekilde sınıflandırmıştır. Modelin işleme kapanmaya ilişkin verdiği sinyallerin %79’u gerçekleşmiştir. Diğer taraftan, modelin öngöremediği işleme kapanmalar (kaçan sinyaller) %13’te sınırlı kalmıştır. Tartışma – Başarısızlık literatüründe lojistik regresyon yönteminin kullanıldığı çalışmalardaki modellere ait “doğru sınıflandırma yüzdeleri” (%77 ile %95 arasında) dikkate alındığında, elde edilen modelin başarı düzeyi (%83) kabul edilebilir düzeydedir. Elde edilen bulgular, işleme kapanmaların tahmininde erken uyarı modellerinden yararlanılabileceğini ortaya koymaktadır.

Prediction Model for Delistings: Empirical Evidence from Borsa İstanbul

Purpose – The aim of the research is to develop a model to predict involuntary delisting from Borsa Istanbul and to test its predictive power. Design/methodology/approach – The scope of the research consists of 79 delisted firms in Borsa Istanbul in the period of 2000-2018. Sample of the research, covering control group, is 147 firms. The model is based on the literature of failure. The variables selected for the model are classified in six dimensions: “liquidity”, “profitability”, “leverage and solvency”, “efficiency”, “market multiples” and “size”. In the research, considering the limited size of data in the research sample, the logistic regression method is applied. While determining the variables to be included in the logistic model, in addition to correlation coefficients, the dimensions of the variables and the number of uses in the literature are also taken into account. At the end of the selection process among 22 financial ratios, 11 financial ratios are used in the model as independent variables. Findings – Model results are found to be compatible with expectations and literature. According to the most appropriate cut-off value of 0.5, the model correctly classifies 83% of the observations. 79% of the signals given by the model regarding delisting is realized. On the other hand, delisting that the model could not predict (missing signals) is limited at 13%. Discussion – When the accurate classification of the models in the studies using the method of logistic regression in the literature of failure (between 77% and 95%) is taken into consideration, the success level of the applied model (83%) is acceptable. The findings reveal that early warning models can be used for predicting delisting.

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