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
Englisch

Bibliographic citation
Series: FinMaP-Working Paper ; No. 31

Classification
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
Crude oil prices
GARCH
Multifractal processes
SPA test

Event
Geistige Schöpfung
(who)
Lux, Thomas
Segnon, Mawuli
Gupta, Rangan
Event
Veröffentlichung
(who)
Kiel University, FinMaP - Financial Distortions and Macroeconomic Performance
(where)
Kiel
(when)
2015

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Lux, Thomas
  • Segnon, Mawuli
  • Gupta, Rangan
  • Kiel University, FinMaP - Financial Distortions and Macroeconomic Performance

Time of origin

  • 2015

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