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Panel quantile regressions for estimating and predicting the value‐at‐risk of commodities
Author(s) -
Čech František,
Baruník Jozef
Publication year - 2019
Publication title -
journal of futures markets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.88
H-Index - 55
eISSN - 1096-9934
pISSN - 0270-7314
DOI - 10.1002/fut.22017
Subject(s) - quantile , stylized fact , quantile regression , futures contract , econometrics , economics , ex ante , expected shortfall , value at risk , financial economics , commodity , risk management , finance , macroeconomics , portfolio
Using a flexible panel quantile regression framework, we show how the future conditional quantiles of commodities returns depend on both ex post and ex ante uncertainty. Empirical analysis of the most liquid commodities covering main sectors, including energy, food, agriculture, and precious and industrial metals, reveal several important stylized facts. We document common patterns of the dependence between future quantile returns and ex post as well as ex ante volatilities. We further show that the conditional returns distribution is platykurtic. The approach can serve as a useful risk management tool for investors interested in commodity futures contracts.