Modeling Istanbul Stock Exchange 100 Daily Stock Returns A Nonparametric GARCH Approach
Journal of Business, Economics and Finance (JBEF), cilt.2, sa.1, ss.36-50, 2013 (Hakemli Dergi)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 2 Sayı: 1
- Basım Tarihi: 2013
- Dergi Adı: Journal of Business, Economics and Finance (JBEF)
- Sayfa Sayıları: ss.36-50
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- İstanbul Üniversitesi Adresli: Evet
Özet
Autoregressive conditional heteroscedasticity (ARCH) and GeneralizedARCH (GARCH) models with various alternatives have been widelyanalyzed in the finance literature in order to model the volatility of thereturns. In all of these models, the hidden variable volatility dependsparametrically on lagged values of the process and lagged values of volatility (Bühlmann and McNeill, 2002) where the parameters areestimated with a nonlinear maximum likelihood function. In this paper anonparametric approach to GARCH models proposed by Bühlmann andMcNeill (2002) is followed to model the volatility of daily stock returnsof the Istanbul Stock Exchange 100 (ISE 100) market from January1991 to November 2012.