Price risk in the NYMEX energy complex: An extreme value approach

Abstract

We estimate tail parameters and construct risk statistics for unconditional distributions of daily logarithmic price changes of the NYMEX energy complex and apply the conditional extreme value method proposed by A. J. McNeil and R. Frey (2000) for estimating VAR and related risk statistics from the tails of conditional distributions for these commodities. The unconditional distribution of spot market price declines is found to be fat tailed relative to the normal for all commodities examined. Backtesting of candidate conditional risk measurement methods indicates that the conditional extreme value method is significantly more accurate for measuring risk exposure due to price declines for 7 of the 10 price series examined.

A Stochastic Factor Model for Risk Management of Commodity Derivatives

“…Therefore, risk management of energy products prices becomes very important for both academicians and market participants, and many risk measurement tools have been proposed in the literature. A non-exhausted list includes: Cabedo and Moya (2003), Costello, Asem and Gardner (2008), Krehbiel and Adkins (2005), Marimoutou, Raggad and Trabelsi (2009), Kang and Yoon (2013), Youssef, Belkacem, and Mokni (2015), and Fiano and Grossi (2015). These papers employ a widely-used risk measure, Value-at-Risk (VaR) originally proposed by J.P. Morgan in 1994 (see Duffie and Pan, 1997, for a discussion of this measure), but differ in the model assumptions.…”

Extreme Value Theory and Value at Risk: Application to oil market

“…To the best of our knowledge, very few studies have focused on measuring the risk forecasts in the oil market despite the significant need and interest to manage energy price risks. Among the few studies on estimating VaR on energy market with EVT, is the paper of Krehbiel and Adkins (2005) who analyzed the price risk in the NYMEX Energy Complex using an extreme value theory approach. Given the importance for an effective price risk management tool, a more comprehensive study seems prudent.…”

Models with Short-Term Variations and Long-Term Dynamics in Risk Management of Commodity Derivatives

“…Therefore, risk management of energy products prices becomes very important for both academicians and market participants, and many risk measurement tools have been proposed in the literature. A non-exhausted list includes: Cabedo and Moya (2003), Costello, Asem and Gardner (2008), Krehbiel and Adkins (2005), Marimoutou, Raggad and Trabelsi (2009), Kang and Yoon (2013), Youssef, Belkacem, and Mokni (2015), and Fiano and Grossi (2015). These papers employ a widely-used risk measure, Value-at-Risk (VaR) originally proposed by J.P. Morgan in 1994 (see Duffie and Pan, 1997, for a discussion of this measure), but differ in the model assumptions.…”