Estimating and Forecasting Volatility of Financial Markets Using Asymmetric GARCH Models: An Application on Turkish Financial Markets

Rasim Ilker Gokbulut, Mehmet Pekkaya

Abstract


Volatility in financial markets, particularly stock exchange markets, is an important issue that concerns theorists and practitioners. Over the past 30 years, there has been a vast literature for modeling the temporal dependencies in volatility of financial markets. Also, more recently researches have been examining the asymmetry and non-linear properties in variance of financial assets, rather than the conditional mean. In this study, a comprehensive empirical analysis of the mean return and conditional variance of Turkish Financial Markets is performed by using various GARCH models. CGARCH and TGARCH appear to be superior for modeling the volatility of financial instruments in Turkey during the years 2002–2014. It is also found that return series of all markets include; leptokurtosis, asymmetry, volatility clustering, and long memory.

 


Full Text: PDF DOI: 10.5539/ijef.v6n4p23

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This work is licensed under a Creative Commons Attribution 3.0 License.

International Journal of Economics and Finance  ISSN  1916-971X (Print) ISSN  1916-9728 (Online)

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