Hossein Tavakolian; Seyed Amir Etemadi; Reza Tehrani
Abstract
The importance of oil price volatility spillover has significantly increased since the globalization and financial markets’ interaction have expanded. Based on this, the oil price impact on financial markets, as an exogenous variable, is also increased. In this paper, we study the “volatility ...
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The importance of oil price volatility spillover has significantly increased since the globalization and financial markets’ interaction have expanded. Based on this, the oil price impact on financial markets, as an exogenous variable, is also increased. In this paper, we study the “volatility spillover of Brent oil price return effects on return of Iran and USA financial markets during 2008-2016 using weekly data. Results show that volatility of Brent oil price return spillovers S&P500 and related industries to oil indexes in USA, so it does not spillover Tehran exchange price index return and related industries to oil indexes in Iran. Also financial market indexes return do not spillover together in short-time.
Seed Rasekhi; Amir Khanalipour
Volume 1, Issue 1 , January 2011, , Pages 101-132
Abstract
This paper has examined the long memory of oil market volatility. For this purpose, the paper has employed different types of long run ARCH models including FIGARCH-BBM, FIGARCH-chung, FIEGARCH, FIAPARCH-BBM and FIAPARCH-chung and short run ones including GARCH, EGARCH, GJR AND APARCH with three different ...
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This paper has examined the long memory of oil market volatility. For this purpose, the paper has employed different types of long run ARCH models including FIGARCH-BBM, FIGARCH-chung, FIEGARCH, FIAPARCH-BBM and FIAPARCH-chung and short run ones including GARCH, EGARCH, GJR AND APARCH with three different assumptions of normal, t-student and generalized error distributions. Results obtained from all long run models indicate the volatility persistence, i.e. the long memory of oil market volatility. Furthermore, with regard to Akaike’s information criterion, FIAPARCH-chung with assumption of t-student distribution has the best performance. Also, according to Schwarz Criterion, FIGARCH-chung model with assumption t-student distribution is the best model in modeling volatility of oil market. Based on the results, long run models considering long memory property of volatility indicate a better performance than the short run ones. Finally, based on obtained results, asymmetric distributions including t-student and GED are found to be more suitable than normal distribution.
