 Jump Dynamics and Leverage Effect: Evidences from Energy Exchange Traded Fund (ETFs)Jo-Hui, Chen and Sabbor Hussain Journal of Applied Finance & Banking, 2022, vol. 12, issue 6, 7 Abstract: This paper is concerned with the behavior of energy ETF prices. It applies three models: autoregressive moving average (ARMA) and generalized autoregressive conditional heteroskedasticity (GARCH), along with their revised forms, ARMA–Exponential-GARCH, Glosten-Jagannathan-Runkle (GJR), and GARCH diffusion process with jump models. This study looks at the volatility behavior and jumps dynamics of Energy and Master Limited Partnership's (MLP) ETFs. The results show that ARMA-GARCH is appropriate for modeling energy and MLP ETFs. Both ETFs offer positive leverage and asymmetric volatility. The results show that the jump model with a GARCH volatility specification has an actual amount of jump presence and time variation in the jump size distribution. The conclusion of the ARMA - EGARCH model gives evidence of the reverse leverage effect. The leverage term positively influences the conditional variance, while the asymmetry coefficient for the GJR model is positive and significant. These results reveal that both Energy and MLPs ETF have high volatility.  JEL classification numbers: F3. Keywords: Energy ETFs; MLPs; ARMA-GARCH model; Volatility Asymmetry; Leverage and Jump Effect. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spt:apfiba:v:12:y:2022:i:6:f:12_6_7 Access Statistics for this article More articles in Journal of Applied Finance & Banking from SCIENPRESS Ltd |
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