Economics at your fingertips  

Comparison of Forecasting Volatility in the Czech Republic Stock Market

El Thalassinos (), Erginbay Ugurlu () and Yusuf Muratoğlu ()

Applied Economics and Finance, 2015, vol. 2, issue 1, 11-18

Abstract: The aim of this paper is to examine different GARCH models with three different distributions in order to compare their forecasting power in terms of volatility existing in the returns of the Czech Stock Market and more specific in the PX index, for the period 08.01.2001-20.07.2012. We have employed GARCH, GJR-GARCH and EGARCH models against normal, student-t and generalized error distributions. Then, we have forecasted stock market volatility for the Czech Republic by its returns using the same models, GARCH, GJR-GARCH and EGARCH comparing their forecasting performance. The results show that return volatility can be characterized by significant persistence and asymmetric effects. We have estimated the corresponding variances for all models for the full sample period using static forecasts. After comparing the forecasting performance of all nine models it was found that the EGARCH model has the best forecasting performance compared to others. JEL classification: G15, G17

Keywords: GARCH models; stock market volatility; forecasting performance (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (16) Track citations by RSS feed

Downloads: (external link) (application/pdf) (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

More articles in Applied Economics and Finance from Redfame publishing Contact information at EDIRC.
Bibliographic data for series maintained by Redfame publishing ().

Page updated 2021-05-31
Handle: RePEc:rfa:aefjnl:v:2:y:2015:i:1:p:11-18