Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting

2021 ◽  
Vol 103 ◽  
pp. 105622
Author(s):  
Min Liu ◽  
Chien-Chiang Lee
Keyword(s):  
Crude Oil ◽  
Markov Switching ◽  
Volatility Forecasting ◽  
Oil Futures ◽  
Crude Oil Futures

The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China

2021 ◽  
Vol 73 ◽  
pp. 102173
Author(s):  
Zibo Niu ◽  
Yuanyuan Liu ◽  
Wang Gao ◽  
Hongwei Zhang
Keyword(s):  
Crude Oil ◽  
Futures Markets ◽  
Volatility Forecasting ◽  
Oil Futures ◽  
Crude Oil Futures

REGIME-SWITCHED VOLATILITY OF BRENT CRUDE OIL FUTURES WITH MARKOV-SWITCHING ARCH MODEL

2009 ◽  
Vol 12 (02) ◽  
pp. 113-124
Author(s):  
TIEN-YU CHIU ◽  
SHWU-JANE SHIEH
Keyword(s):  
Crude Oil ◽  
Goodness Of Fit ◽  
Terrorist Attack ◽  
Markov Switching ◽  
Persian Gulf War ◽  
Arch Model ◽  
Oil Futures ◽  
Forecast Performance ◽  
High Volatility ◽  
Crude Oil Futures

This paper investigates the volatility process of the Brent crude oil futures markets using Markov-switching ARCH (SWARCH) model. The SWARCH model allows the conditional disturbances to change as time passes and even to switch in different regimes. The empirical evidence shows that the SWARCH (3,3) model performs the best goodness of fit and the best forecast performance among different fitting models. The estimation of smoothing probabilities of data under different regimes facilitates to capture the characteristics of the data, and the high-volatility regime is associated with some extraordinary events, such as the 1990's Persian Gulf War, the 1997's Asia Financial Crisis, and the 2001's 911 terrorist attack.

scholarly journals Volatility forecasting for crude oil futures

2010 ◽  
Vol 17 (16) ◽  
pp. 1587-1599 ◽  
Author(s):  
Massimiliano Marzo ◽  
Paolo Zagaglia
Keyword(s):  
Crude Oil ◽  
Volatility Forecasting ◽  
Oil Futures ◽  
Crude Oil Futures
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