Open AccessModelling and Estimation of Volatility Using ARCH/GARCH Models in Jordan’s Stock Market
Author(s) -
Dana Al-Najjar
Publication year - 2016
Publication title -
asian journal of finance and accounting
Language(s) - English
Resource type - Journals
ISSN - 1946-052X
DOI - 10.5296/ajfa.v8i1.9129
Subject(s) - volatility clustering , volatility (finance) , autoregressive conditional heteroskedasticity , stock exchange , economics , econometrics , financial models with long tailed distributions and volatility clustering , leverage effect , financial economics , volatility smile , volatility swap , forward volatility , implied volatility , finance
Financials have been concerned constantly with factors that have impact on both taking and assessing various financial decisions in firms. Hence modelling volatility in financial markets is one of the factors that have direct role and effect on pricing, risk and portfolio management. Therefore, this study aims to examine the volatility characteristics on Jordan’s capital market that include; clustering volatility, leptokurtosis, and leverage effect. This objective can be accomplished by selecting symmetric and asymmetric models from GARCH family models. This study applies; ARCH, GARCH, and EGARCH to investigate the behavior of stock return volatility for Amman Stock Exchange (ASE) covering the period from Jan. 1 2005 through Dec.31 2014. The main findings suggest that the symmetric ARCH /GARCH models can capture characteristics of ASE, and provide more evidence for both volatility clustering and leptokurtic, whereas EGARCH output reveals no support for the existence of leverage effect in the stock returns at Amman Stock Exchange.