Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/107767
Authors: 
Lux, Thomas
Segnon, Mawuli
Gupta, Rangan
Year of Publication: 
2015
Series/Report no.: 
FinMaP-Working Paper 31
Abstract: 
This paper uses the Markov-switching multifractal (MSM) model and generalized autoregressive conditional heteroscedasticity (GARCH)-type models to forecast oil price volatility over the time periods from January 02, 1875 to December 31, 1895 and from January 03, 1977 to March 24, 2014. Based on six different loss functions and by means of the superior predictive ability (SPA) test, we evaluate and compare their forecasting performance at short and long horizons. The empirical results indicate that none of our volatility models can uniformly outperform other models across all six different loss functions. However, the new MSM model comes out as the model that most often across forecasting horizons and subsamples cannot be outperformed by other models, with long memory GARCH-type models coming out second best.
Subjects: 
Crude oil prices
GARCH
Multifractal processes
SPA test
JEL: 
C52
C53
C22
Document Type: 
Working Paper
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