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Review of Quantitative Finance and Accounting

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10.09.2018 | Original Research

Crude oil and gasoline volatility risk into a Realized-EGARCH model

verfasst von: Bernard Ben Sita

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 3/2019

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Abstract

This paper disentangles oil volatility risk to two components. The first component is attributed to crude oil, while the second is related to gasoline. This disentanglement serves the purpose of investigating the extent to which crude oil and gasoline are complementary in impacting return and variance residuals. The Realized-EGARCH model of Hansen et al. (J Appl Econom 29(5):774–799, 2014) is used to test the hypothesis that stock markets show some delay in incorporating oil information. This study shows that both crude oil- and gasoline-based information impact stock markets contemporaneously in a complementary fashion. Unlike the underreaction hypothesis, which is suggested as an explanation to the negative lagged effect of crude oil price change on return, the sequential information hypothesis explains better the ways information about oil is disseminated among U.S. industry portfolios.

Vorheriger Artikel Multiple directorships and the value of cash holdings

Nächster Artikel Information disclosure, transparency ranking system and firms’ value deviation: evidence from Taiwan

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See for instance, Chen et al. (1986), Cong et al. (2008), and Jones and Kaul (1996).

See for instance, Radchenko and Shapiro (2011), Ben Sita and Abosedra (2013), and Wang and Ngene (2017).

See for instance, Marvel (1976), Kaufmann and Laskowski (2005), Yang and Ye (2008), Kaufmann and Ullman (2009), Kaufmann (2011), Kilian (2010), Cifarelli and Paladino (2010), Radchenko and Shapiro (2011), and Polemis and Fotis (2014).

This is consistent with the underreaction hypothesis according to which investors exhibit conservatism bias, which is a tendency to underweight new information when updating prior beliefs (Barberis et al. 1998).

This is in line with the sequential information hypothesis, investors receive information signals at different trading times. As a result, prices are partially revealing at the start, but fully revealing when bits of information are integrated through continuous trading (Copeland 1976).

See for instance, El Hedi Arouri et al. (2011), and Sadorsky (2014).

See Appendix 2 for the derivation of Eqs. (2), (3) and (4).

The hedge ratio shows the number of crude oil units that is protected in terms of the number of gasoline units.

I use monthly minimum and maximum volatilities, which has the disadvantage of being drawn from another distribution (extreme value distribution), but has the advantage of being generated by richer information dynamics, which are free from strong biases in intraday and interday bid-ask prices (Brandt and Jones 2006).

See Hansen et al. (2012) for the properties of these log-likelihood functions.

The crude oil spot prices are West Texas Intermediate (WTI) series, while the gasoline prices are a combination of New York Harbor (NYH) regular gasoline from June 2, 1986 to September 30, 2005 and reformulated RBOB regular gasoline series from October 3, 2005 to June 30, 2014.

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html.

http://www.federalreserve.gov/pubs/bulletin/2005/winter05_index.pdf.

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Titel: Crude oil and gasoline volatility risk into a Realized-EGARCH model
verfasst von: Bernard Ben Sita
Publikationsdatum: 10.09.2018
Verlag: Springer US
Erschienen in: Review of Quantitative Finance and Accounting / Ausgabe 3/2019
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI: https://doi.org/10.1007/s11156-018-0763-0

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