الفهرس 
Generalized Autoregressive Conditional Heteroskedasticity Models Properties and Estimation
AbstractOnly 14 pages are availabe for public view
 |  | from | 232 |  |  |
| | | from | 232 | | |
Abstract
The volatility analysis of stock returns data is paramount in financial studies. We investigate the dynamics of volatility and randomness of the Egypt Stock Exchange (EGX30) and obtain insights into the behavior of investors before and after the floatation of a the Egyptian pound on the 6 of nov 2016.
GARCH models are widely accepted in modeling changing volatility in financial time series. One limitation of GARCH models is the implied symmetric effect of positive and negative innovation on conditional volatility.
The aims of this thesis was reviewed the GARCH family models and some of its properties, present the volatility estimations and its quantitative properties of EGX30. The methodology approaches: the implementation of GARCH (1,1), GARCH-M(1,1), and EGARCH(1,1),using the ML, QML, EMM and GMM estimation methods, under the distributions (Normal, Student’s t, GED) . The result was extracted to determine the model that expresses the volatility of the market and have the most accurate expectation.