CARL and His POT: Measuring Risks in Commodity Markets

Bernardina Algieri and Arturo Leccadito
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Arturo Leccadito: Department of Economics, Statistics and Finance, University of Calabria, Ponte Bucci, 87030 Rende (CS), Italy

Risks, 2020, vol. 8, issue 1, 1-15

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.

Keywords: commodities; risk measures; tail probability forecast (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:8:y:2020:i:1:p:27-:d:332245

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