Modeling and Forecasting the Markets Volatility and VaR Dynamics of Commodity

Pinar Kaya and Bulent Guloglu

Journal of BRSA Banking and Financial Markets, 2017, vol. 11, issue 1, 9-49

Abstract: The purpose of this paper is to model and forecast the risk of six commodities namely, crude oil, copper, gold, silver, palladium, and platinum during the period from 02/01/2002 to 29/04/2016 using volatility, value at risk and expected shortfall as risk measures. After showing that squared returns of all six commodities have a significant long memory, the volatility, the value at risk and expected shortfall based on fractional GARCH models are estimated and forecasted. Both forecast performance of volatility models and backtest for value at risk indicate that in many cases FIAPARCH model outperforms the other GARCH models. Then volatility, value at risk and expected shortfall estimates based on FIAPARCH model show that the volatility and market risk of oil is much higher than the other commodities. This casts doubt on the use of oil as a hedging tool.

Keywords: Volatility Modelling; Commodity Markets; VaR Forecasting; Expected Shortfall (search for similar items in EconPapers)
JEL-codes: C22 C53 C58 G17 Q02 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:bdd:journl:v:11:y:2017:i:1:p:9-49

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