ISTFIX Balonlarını Ne Tetikler?

Year 2018, , 119 - 135, 21.10.2018

Abdullah Açık , Sadık Özlen Başer , Egemen Ertürk

https://doi.org/10.20979/ueyd.434031

Abstract

Denizcilik piyasasında arzın talebe olan tepkisindeki
gecikmelerden dolayı büyük veya küçük sürekli konjonktürel dalgalanmalar
gözlemlenmektedir. Bazı durumlarda gelirler gemi sahiplerine yaşam fırsatı
vermeyecek kadar düşerken, bazı durumlarda onlara sıfırdan çok büyük kazançlara
uzanma fırsatı sağlamaktadır. Tüm bu risklere rağmen denizcilik piyasası
özellikle Türkiye gibi gelişmekte olan ülkeler için çok önemlidir. Bu
çalışmanın amacı İstanbul Navlun Endeksi’nde (ISTFIX) fiyat balonları oluşma
olasılığına etki eden faktörleri tespit etmektir. Bu doğrultuda ilk olarak
genelleştirilmiş eküs Augmented-Dickey-Fuller (GSADF) testi ile fiyat balonları
tespit edilmiştir. GSADF testini takiben de balonların görüldüğü tarihlerden
kukla değişken oluşturularak lojistik regresyon modeli kurulmuştur ve balon
oluşumunu etkileyen faktörler tespit edilmeye çalışılmıştır. Veri seti
18.03.2011 ve 31.12.2017 tarihleri arasını kapsayan 354 gözlemden oluşmaktadır.
Sonuçlara göre uzunlukları 6 ila 12 hafta arasında değişen 4 balon dönemi
tespit edilmiştir. Lojistik regresyonda ise “avro” ve “yakıt fiyatı”
değişkenlerinin balon oluşma olasılığını arttırdıkları ve “avro” değişkeninin
marjinal etkisinin çok daha yüksek olduğu tespit edilmiştir. 

Keywords

Fiyat balonları, denizcilik, GSADF, lojistik regresyon, navlun endeksi.

What Triggers the ISTFIX Bubbles?

Abstract

Business cycles are constantly observed,
whether small or large, due to delays in response of supply to demand in the
maritime market. In some cases, the incomes are so low that it does not give
the shipowners a chance to live, and in some cases they go from rags to riches.
Despite these risks, the maritime market is vital especially for developing
countries such as Turkey. The aim of this study is to determine the factors
that influence the probability of price bubble formation in the İstanbul
Freight Index (ISTFIX). In this direction, firstly the price bubbles were
determined by generalized sup augmented Dickey-Fuller (GSADF) test. Following
the GSADF test, a logit regression model was established by creating dummy
variables from bubble dates and it was tried to determine the factors affecting
bubble formation. The dataset consists of 354 weekly observations and covers the
dates between 18.03.2011 and 31.12.2017. According to the results, 4 bubble
periods with lengths ranging from 6 to 12 weeks were detected. In the logit
model, it was found that “euro” and “fuel price” variables increase the
probability of bubble formation and the marginal effect of “euro” is much
higher. 

Keywords

Price bubbles, maritime, GSADF, logit regression, freight index

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