Arbeitspapier
Modeling and forecasting crude oil price volatility: Evidence from historical and recent data
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.
- Language
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Englisch
- Bibliographic citation
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Series: FinMaP-Working Paper ; No. 31
- Classification
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Wirtschaft
Model Evaluation, Validation, and Selection
Forecasting Models; Simulation Methods
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Subject
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Crude oil prices
GARCH
Multifractal processes
SPA test
- Event
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Geistige Schöpfung
- (who)
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Lux, Thomas
Segnon, Mawuli
Gupta, Rangan
- Event
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Veröffentlichung
- (who)
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Kiel University, FinMaP - Financial Distortions and Macroeconomic Performance
- (where)
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Kiel
- (when)
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2015
- Handle
- Last update
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10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Lux, Thomas
- Segnon, Mawuli
- Gupta, Rangan
- Kiel University, FinMaP - Financial Distortions and Macroeconomic Performance
Time of origin
- 2015