Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/257982 
Year of Publication: 
2020
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 8 [Issue:] 1 [Article No.:] 27 [Publisher:] MDPI [Place:] Basel [Year:] 2020 [Pages:] 1-15
Publisher: 
MDPI, Basel
Abstract: 
The present study aims at modelling market risk for four commodities, namely West Texas Intermediate (WTI) crude oil, natural gas, gold and corn for the period 2007-2017. To this purpose, we use Extreme Value Theory (EVT) together with a set of Conditional Auto-Regressive Logit (CARL) models to predict risk measures for the futures return series of the considered commodities. In particular, the Peaks-Over-Threshold (POT) method has been combined with the Indicator and Absolute Value CARL models in order to predict the probability of tail events and the Value-at-Risk and the Expected Shortfall risk measures for the selected commodities. Backtesting procedures indicate that generally CARL models augmented with specific implied volatility outperform the benchmark model and thus they represent a valuable tool to anticipate and manage risks in the markets.
Subjects: 
commodities
risk measures
tail probability forecast
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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