An inverted U‐shaped crude oil price return‐implied volatility relationship

Abstract

We examined the return–volatility relationship for USO ETF oil price return and CBOE Crude Oil ETF Volatility Index, OVX. The data for the USO and OVX covers the period covering May 11, 2007 to February 28, 2013. Our OLS regression results suggest evidence of regular feedback and leverage effects. When we employ linear quantile regression techniques, we find evidence of regular and inverse feedback effects. The inverse feedback effects being noticeable in the upper quantile region of the oil return distribution. There is also support for a regular leverage effect in USO prices. We also examined the return–volatility relationship using quantile regression copula methods for measuring the degree of asymmetry in the relationships between the oil price return and implied volatility. The results of the analysis indicate, first, that there exists a negative relationship between contemporaneous oil VIX and USO ETF oil returns. Second, that the relationship between oil returns and implied volatilities depends on the quartile at which the relationship is being investigated. Third, there exists an inverted U‐shaped dependency relationship between returns and implied volatilities across quantiles. Fourth, though an inverted U‐shape exists, the shape is different from those observed in stock markets.

An S-Shaped Crude Oil Price Return-Implied Volatility Relation: Parametric and Nonparametric Estimations

“…Low (2004) had already suggested that the cause of the asymmetric effect of the return-volatility relation could be behavioral. In the same sense, other studies provide evidence of this asymmetric relation betwen return and implied volatility (see, for example, Agbeyegbe, 2015;Badshah, 2013). …”

“…Second, the relation of the variables presents a parabola format, with the concavity upwards, different from the results for Low (2004). On the other hand, Agbeyegbe (2015) tested the nonlinear relation between the variables using conditional copula and quantile regression methods. His results identified an inverted "U" through quantiles for the relation between USO and OVX.…”

“…Talukdar, Daigler and Parhizgari (2016) also suggest that the behavioral theory best explains the relation between return and volatility, in this case for the CBOE"s, VIX, SKEW (Note 3) and Volatility of VIX Index (VVIX) indices, than the other theories. Agbeyegbe (2016), similarly to Agbeyegbe (2015), also uses the conditional copula and quantile regression methods to evaluate the return-volatility relation of DJA, S&P500, S&P100 and NASDAQ indices and their respective volatility indices, DJIA Volatility Index (VXD), VIX, S&P Volatility Index (VXO) and VXN. With a sample of data from 2001 to 2012, their results suggest that there is an inverted U-shaped relation between the variables.…”

“…Even in the face of the great oscillations that oil prices have shown in recent years (for more information, see Reboredo, 2012) and the construction of the Crude Oil Volatility Index (OVX), based on the values of the options of United States Oil Fund (USO), few studies have been performed to verify the return-implied volatility relation (see, for example, Aboura & Chevallier, 2013;Padungsksawasdi & Daigler, 2014;Agbeyegbe, 2015). Thus, important aspects related to the asymmetry and nonlinearity of the relation between OVX and USO have not yet been explored by evaluation strategies that use flexible methodologies such as nonparametric methods.…”

New Challenge and Research Development in Global Energy Financialization

“…Energy financialization also provides new research ideas and directions for the study of price behavior, risk contagion mechanisms and risk management in the energy market. The price behavior characteristics of energy financialization in the energy market mainly manifest through four aspects: volatility (Ma, Ji, and Pan 2019b;Zavadska, Morales, and Coughlan 2018), uncertainty (Agbeyegbe 2015;Liu, Ji, and Fan 2017), complexity (Zhang, Ji, and Kutan 2019) and infectivity (Ji, Liu, and Fan 2019a;Mahadeo, Heinlein, and Legrenzi 2019).…”