Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/112734 
Year of Publication: 
2015
Series/Report no.: 
FinMaP-Working Paper No. 46
Publisher: 
Kiel University, FinMaP - Financial Distortions and Macroeconomic Performance, Kiel
Abstract: 
This paper applies Markov-switching multifractal (MSM) processes to model and forecast carbon dioxide (CO2) emission price volatility, and compares their forecasting performance to the standard GARCH, fractionally integrated GARCH (FIGARCH) and the two-state Markov-switching GARCH (MS-GARCH) models via three loss functions (the mean squared error, the mean absolute error and the value-at-risk). We evaluate the performance of these models via the superior predictive ability test. We find that the forecasts based on the MSM model cannot be outperformed by its competitors under the vast majority of criteria and forecast horizons, while MS-GARCH mostly comes out as the least successful model. Applying various VaR backtesting procedures, we do, however, not find significant differences in the performance of the candidate models under this particular criterion. We also find that we cannot reject the null hypothesis of MSM forecasts encompassing those of GARCH-type models. In line with this result, optimally combined forecasts do indeed hardly improve upon the best single models in our sample.
Subjects: 
carbon dioxide emission allowance prices
GARCH
Markov-switching GARCH
FIGARCH
multifractal Processes
SPA test
encompassing test
backtesting
JEL: 
Q47
Document Type: 
Working Paper

Files in This Item:
File
Size
463.74 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.