Publication: Kripto paraların istatistiksel özellikleri ve çoklu fraktal yapısı : Bitcoin, Ethereum ve altcoinlerin incelenmesi
Abstract
Bu çalışmada kripto para birimleri olarak da adlandırılan Bitcoin Cash, Ethereum, Litecoin ve Ripple’ın fiyatlanmaları arasındaki ilişki ekonometrik olarak modellenmiştir. Çalışmada birim kök testi olarak Augmented Dickey-Fuller (ADF) testi uygulanarak serilerin durağan olduğu düzeyler saptanmış ve aralarındaki nedensellik ilişkisi Granger nedensellik testi ile sınanmıştır. Seriler arasındaki ilişkilerin yönü ve büyüklüğü, vektör otoregresif (VAR) model tekniğiyle belirlenmeye çalışılmıştır. Ayrıca, etki-tepki analizleri ve varyans ayrıştırma analizleri yapılarak serilerin standart sapmasında meydana gelen değişimin dönem bazında % kaçının diğer değişkenler tarafından açıklandığı ortaya konmuştur.
In this study, the relationship between the pricing of Bitcoin Cash, Ethereum, Litecoin and Ripple, also called cryptocurrencies, is modeled econometrically. In the study, the stationary levels of the series were determined by applying the Augmented Dickey Fuller (ADF) test as a unit root test, and the causality relationship between them was tested with the Granger causality test. The direction and size of the relationships between them were tried to be determined by the vector autoregressive (VAR) model technique. In addition, by performing impact-response analysis and variance decomposition analysis, it was revealed that what % of the change in the standart deviation of the series was explained by other variables on a period basis.
In this study, the relationship between the pricing of Bitcoin Cash, Ethereum, Litecoin and Ripple, also called cryptocurrencies, is modeled econometrically. In the study, the stationary levels of the series were determined by applying the Augmented Dickey Fuller (ADF) test as a unit root test, and the causality relationship between them was tested with the Granger causality test. The direction and size of the relationships between them were tried to be determined by the vector autoregressive (VAR) model technique. In addition, by performing impact-response analysis and variance decomposition analysis, it was revealed that what % of the change in the standart deviation of the series was explained by other variables on a period basis.
