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 di erent 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
di erent 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.
