BibTex RIS Kaynak Göster

Oynaklık Tahmininde Simetrik ve Asimetrik GARCH Modellerinin Kullanılması: Seçilmiş BİST Alt Sektör Endeksleri Üzerine Bir Uygulama

Yıl 2016, , 83 - 106, 01.10.2016
https://doi.org/10.25095/mufad.396721

Öz

Bu çalışmada, Borsa İstanbul (BİST)’a kayıtlı seçilmiş alt sektörler arasında yer alan hizmet (XUHIZ), mali (XUMAL) ve sınai (XUSIN) endeks getiri serilerine ilişkin oynaklıkların modellenmesinde ve tahmin edilmesinde hangi modellerin daha başarılı sonuçlar verdiği tespit edilmeye çalışılmıştır. 05 Ocak 2000-09 Aralık 2015 tarihlerini kapsayan günlük veriler koşullu değişen varyans modelleri ile analiz edilmiş ve endekslere ait oynaklıkların hem ARCH hem de GARCH etkisi gösterdiği belirlenmiştir. Bununla birlikte, mali ve sınai endekslere ilişkin oynaklık tahminlerinde en uygun modelin TGARCH (1,1) , hizmet endeksine ait oynaklık tahmininde ise en uygun modelin CGARCH (1,1) olduğu da elde edilen bulgular arasında yer almaktadır. Ayrıca, oynaklık üzerindeki şokların asimetrikliğini dikkate alan EGARCH modeli de tahmin edilmiş ve her üç endeks getiri serisi üzerinde de kaldıraç etkisinin var olduğu tespit edilmiştir.

Volatility Forecasting with Symmetric and Asymmetric GARCH Models: An Application on Selected ISE Sub-Sectors

Yıl 2016, , 83 - 106, 01.10.2016
https://doi.org/10.25095/mufad.396721

Öz

In this study, the most successful model was performed to determine for modeling and forecasting the volatility of the selected sub-sector return series of each indices which is listed in ISE namely; service (XUHIZ), financial (XUMAL) and industrial (XUSIN) sectors. The findings indicate that the daily data which were analyzed with conditional variance models, covering a period from January 5, 2000 to December 9, 2015, show both ARCH and GARCH effects. In addition, the findings also show that TGARCH (1,1) is the best model for estimating volatility not also financial but also industrial indices, but on the other hand CGARCH (1,1) is the best model to forecast the volatility of service index. Furthermore, EGARCH model which is considering the asymmetry on volatility shocks are also estimated and it was determined that there have a leverage effect on each return series of three indices.

Toplam 0 adet kaynakça vardır.

Ayrıntılar

Diğer ID JA29YY29NN
Bölüm Araştırma Makalesi
Yazarlar

Berk Yıldız Bu kişi benim

Yayımlanma Tarihi 1 Ekim 2016
Gönderilme Tarihi 1 Ekim 2016
Yayımlandığı Sayı Yıl 2016

Kaynak Göster

APA Yıldız, B. (2016). Volatility Forecasting with Symmetric and Asymmetric GARCH Models: An Application on Selected ISE Sub-Sectors. The Journal of Accounting and Finance(72), 83-106. https://doi.org/10.25095/mufad.396721
AMA Yıldız B. Volatility Forecasting with Symmetric and Asymmetric GARCH Models: An Application on Selected ISE Sub-Sectors. The Journal of Accounting and Finance. Ekim 2016;(72):83-106. doi:10.25095/mufad.396721
Chicago Yıldız, Berk. “Volatility Forecasting With Symmetric and Asymmetric GARCH Models: An Application on Selected ISE Sub-Sectors”. The Journal of Accounting and Finance, sy. 72 (Ekim 2016): 83-106. https://doi.org/10.25095/mufad.396721.
EndNote Yıldız B (01 Ekim 2016) Volatility Forecasting with Symmetric and Asymmetric GARCH Models: An Application on Selected ISE Sub-Sectors. The Journal of Accounting and Finance 72 83–106.
IEEE B. Yıldız, “Volatility Forecasting with Symmetric and Asymmetric GARCH Models: An Application on Selected ISE Sub-Sectors”, The Journal of Accounting and Finance, sy. 72, ss. 83–106, Ekim 2016, doi: 10.25095/mufad.396721.
ISNAD Yıldız, Berk. “Volatility Forecasting With Symmetric and Asymmetric GARCH Models: An Application on Selected ISE Sub-Sectors”. The Journal of Accounting and Finance 72 (Ekim 2016), 83-106. https://doi.org/10.25095/mufad.396721.
JAMA Yıldız B. Volatility Forecasting with Symmetric and Asymmetric GARCH Models: An Application on Selected ISE Sub-Sectors. The Journal of Accounting and Finance. 2016;:83–106.
MLA Yıldız, Berk. “Volatility Forecasting With Symmetric and Asymmetric GARCH Models: An Application on Selected ISE Sub-Sectors”. The Journal of Accounting and Finance, sy. 72, 2016, ss. 83-106, doi:10.25095/mufad.396721.
Vancouver Yıldız B. Volatility Forecasting with Symmetric and Asymmetric GARCH Models: An Application on Selected ISE Sub-Sectors. The Journal of Accounting and Finance. 2016(72):83-106.

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