Value-at-risk estimation of crude oil price using MCA based transient risk modeling approach

Background and objective: Crude oil is an essential commodity in many countries of the world. This work studies the risk involved in the extreme crude oil price, using the daily crude oil price of the Brent and the West Texas benchmark from year 1990 to 2019. Materials and methods: The Peak Over Threshold (POT) approach of the Generalized Pareto Distribution (GPD) was used to model the extreme crude oil price while the value at risk and the expected shortfall was used to quantify the risk involved in extreme price of crude oil. The GPD, using the Q-Q plot was found to be a good model for the extreme values of the crude oil price. Results: The Value at Risk (VaR) and the Expected Shortfall (ES) calculated at 90%, 95% and 99% with the Maximum Likelihood estimators of GPD parameters and the threshold values were found to decrease with increase in quantile for both benchmark. This shows that risk involved in extreme crude oil price will be borne only by the investors and public. Conclusion: It was also found that the VaR and ES of the Brent are higher than that of West Texas. This implies that it is safer to invest in West Texas crude oil.

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Understanding the Crude Oil Price Value-at-Risk: The Case of Azeri Light

SSRN Electronic Journal ◽

10.2139/ssrn.2402622 ◽

2014 ◽

Author(s):

Huseyn Aghayev ◽

Islam Rizvanoghlu

Keyword(s):

At Risk ◽

Crude Oil ◽

Value At Risk ◽

Oil Price ◽

Crude Oil Price

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An evolving possibilistic fuzzy modeling approach for Value-at-Risk estimation

Applied Soft Computing ◽

10.1016/j.asoc.2017.04.028 ◽

2017 ◽

Vol 60 ◽

pp. 820-830 ◽

Cited By ~ 5

Author(s):

Leandro Maciel ◽

Rosangela Ballini ◽

Fernando Gomide

Keyword(s):

At Risk ◽

Value At Risk ◽

Risk Estimation ◽

Fuzzy Modeling ◽

Modeling Approach

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Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic

Energies ◽

10.3390/en14144147 ◽

2021 ◽

Vol 14 (14) ◽

pp. 4147

Author(s):

Krzysztof Echaust ◽

Małgorzata Just

Keyword(s):

At Risk ◽

Crude Oil ◽

Value At Risk ◽

Tail Dependence ◽

Oil Price ◽

Health Crisis ◽

Oil Market ◽

Volatility Index ◽

Conditional Copula ◽

The Impact

This study investigates the dependence between extreme returns of West Texas Intermediate (WTI) crude oil prices and the Crude Oil Volatility Index (OVX) changes as well as the predictive power of OVX to generate accurate Value at Risk (VaR) forecasts for crude oil. We focus on the COVID-19 pandemic period as the most violate in the history of the oil market. The static and dynamic conditional copula methodology is used to measure the tail dependence coefficient (TDC) between the variables. We found a strong relationship in the tail dependence between negative returns on crude oil and OVX changes and the tail independence for positive returns. The time-varying copula discloses the strongest tail dependence of negative oil price shocks and the index changes during the COVID-19 health crisis. The findings indicate the ability of the OVX index to be a fear gauge with respect to the oil market. However, we cannot confirm the ability of OVX to improve one day-ahead forecasts of the Value at Risk. The impact of investors’ expectations embedded in OVX on VaR forecasts seems to be negligible.

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