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Risk Modeling of Commodities using CAViaR Models, the Encompassing Method and the Combined Forecasts
Dynamic Econometric Models
View Archive Info| Field | Value | |
| Title |
Risk Modeling of Commodities using CAViaR Models, the Encompassing Method and the Combined Forecasts
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| Creator |
Ratuszny, Ewa; Warsaw School of Economics
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| Subject |
CAViaR; VaR; encompassing method; combined forecasts; commodities
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| Description |
The aim of the research is to compare VaR methods/models for commodities. For risk measurement Conditional Autoregressive Value at Risk models (CAViaR), implied quantile model and encompassing method are used. The aim is to check whether simultaneous use of information both from historical time series and regarding markets' expectation can improve accuracy of forecasts. For this purpose four methods of combining forecasts are used: a simple average combining, an unrestricted linear combination, a weighted averaged combining and a weighted averaged combining using exponential weighting. In the case of the commodities neither the encompassing method nor the combining forecast method improve VaR forecasts. The method of choosing the most adequate model leads to simple CAViaR-SAV model as the source of most optimal measure of risk forecasts. The Kupiec test, the Christoffersen and the Dynamic Quantile test indicate the model as an adequate to forecast VaR for gold and oil for short positions at the 0.01 and the 0.05 significance level, and for a long position at the 0.05 significance level.
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| Publisher |
Nicolaus Copernicus University
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| Contributor |
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| Date |
2016-02-18
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion — — |
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| Format |
application/pdf
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| Identifier |
http://apcz.umk.pl/czasopisma/index.php/DEM/article/view/DEM.2015.006
10.12775/DEM.2015.006 |
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| Source |
Dynamic Econometric Models; Vol 15 (2015); 129-156
Dynamic Econometric Models; Vol 15 (2015); 129-156 2450-7067 1234-3862 |
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| Language |
eng
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| Relation |
http://apcz.umk.pl/czasopisma/index.php/DEM/article/view/DEM.2015.006/8950
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| Rights |
Copyright (c) 2016 Dynamic Econometric Models
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