This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 537
Type: Contributed
Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Risk Analysis
Abstract - #307356
Title: WITHDRAWN: ARCH Models Application on Istanbul Stock Market Data
Author(s): Atilla Aslanargun and Berna Yazici and Betül Kan and Zeynep Ozgun
Companies: Anadolu University and Anadolu University and Anadolu University and Anadolu University
Keywords: ARCH ; GARCH ; EGARCH ; TGARCH ; Heteroscedasticity ; Volatility

In financial series, the nonlinear conditional heteroscedastic models are more commonly used than the linear time series models since the properties they have. Time series analysis requires the models that take into account the heteroscedasticity since the prediction errors do not have the constant variances. Robert F. Engle 1982 generalizes the assumption about the heteroscedasticity and proposes a new stochastic models class "Auto Regressive Conditional Heteroscedasticity (ARCH)". In this study different ARCH models; GARCH, GARCH-M, EGARCH, and TGARCH are applied on the volatility in Istanbul stock market, namely ISE-100 Index (ISE=Istanbul Stock Index). 22 years daily data (January 1988-January 2010) in US dollars are used. The resulting models are compared with each other and the best model for the problem in question is defined.

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