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Does OVX affect WTI and Brent oil spot variance? Evidence from an entropy analysis

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  • Benedetto, Francesco
  • Mastroeni, Loretta
  • Quaresima, Greta
  • Vellucci, Pierluigi

Abstract

This paper examines the flow of information and its direction between the oil volatility index (OVX) and the spot variance of WTI and Brent returns. Since OVX is an indicator of the investor sentiment about oil market performance, we aim first at evidencing whether there is an exchange of information between OVX and the spot variance of the two crudes. Moreover, since OVX is linked to WTI crude oil, it is useful to investigate whether it shares an information content with Brent. To this purpose, we propose an entropy-based approach which exploits two non-parametric methods: the mutual information and the transfer entropy. The results show an increase in the information flow between OVX and the spot variance of Brent returns and a corresponding decrease in the information flow with WTI. Furthermore, the direction of the information flow comes from OVX to both oil spot variances, thus investor sentiment about oil market performance drives uncertainty in the corresponding spot market. However, the information flow from the oil spot variances to OVX is more statistically significant for WTI than for Brent and, since transfer entropy is a measure of resolution of uncertainty, we demonstrate that the spot variance of WTI returns helps more in reducing uncertainty about OVX (than Brent).

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  • Benedetto, Francesco & Mastroeni, Loretta & Quaresima, Greta & Vellucci, Pierluigi, 2020. "Does OVX affect WTI and Brent oil spot variance? Evidence from an entropy analysis," Energy Economics, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:eneeco:v:89:y:2020:i:c:s0140988320301559
    DOI: 10.1016/j.eneco.2020.104815
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    as
    1. Campos, I. & Cortazar, G. & Reyes, T., 2017. "Modeling and predicting oil VIX: Internet search volume versus traditional mariables," Energy Economics, Elsevier, vol. 66(C), pages 194-204.
    2. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    3. Qadan, Mahmoud & Nama, Hazar, 2018. "Investor sentiment and the price of oil," Energy Economics, Elsevier, vol. 69(C), pages 42-58.
    4. He, Jiayi & Shang, Pengjian, 2017. "Comparison of transfer entropy methods for financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 772-785.
    5. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    6. Cao, Charles & Yu, Fan & Zhong, Zhaodong, 2010. "The information content of option-implied volatility for credit default swap valuation," Journal of Financial Markets, Elsevier, vol. 13(3), pages 321-343, August.
    7. Kao, Chung-Wei & Wan, Jer-Yuh, 2012. "Price discount, inventories and the distortion of WTI benchmark," Energy Economics, Elsevier, vol. 34(1), pages 117-124.
    8. Lopez, Jose A, 2001. "Evaluating the Predictive Accuracy of Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(2), pages 87-109, March.
    9. Agnolucci, Paolo, 2009. "Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models," Energy Economics, Elsevier, vol. 31(2), pages 316-321, March.
    10. Lv, Wendai, 2018. "Does the OVX matter for volatility forecasting? Evidence from the crude oil market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 916-922.
    11. Liu, Zhengli & Shang, Pengjian, 2018. "Generalized information entropy analysis of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1170-1185.
    12. Benedetto, F. & Giunta, G. & Mastroeni, L., 2016. "On the predictability of energy commodity markets by an entropy-based computational method," Energy Economics, Elsevier, vol. 54(C), pages 302-312.
    13. Sadeghi, Mehdi & Shavvalpour, Saeed, 2006. "Energy risk management and value at risk modeling," Energy Policy, Elsevier, vol. 34(18), pages 3367-3373, December.
    14. Christiane Baumeister & Gert Peersman, 2013. "Time-Varying Effects of Oil Supply Shocks on the US Economy," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(4), pages 1-28, October.
    15. Peter Ferderer, J., 1996. "Oil price volatility and the macroeconomy," Journal of Macroeconomics, Elsevier, vol. 18(1), pages 1-26.
    16. Szakmary, Andrew & Ors, Evren & Kyoung Kim, Jin & Davidson, Wallace III, 2003. "The predictive power of implied volatility: Evidence from 35 futures markets," Journal of Banking & Finance, Elsevier, vol. 27(11), pages 2151-2175, November.
    17. Yin, Libo & Yang, Qingyuan, 2016. "Predicting the oil prices: Do technical indicators help?," Energy Economics, Elsevier, vol. 56(C), pages 338-350.
    18. Christoffersen, Peter & Pan, Xuhui (Nick), 2018. "Oil volatility risk and expected stock returns," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 5-26.
    19. Dimpfl, Thomas & Peter, Franziska J., 2018. "Analyzing volatility transmission using group transfer entropy," Energy Economics, Elsevier, vol. 75(C), pages 368-376.
    20. Awartani, Basel & Aktham, Maghyereh & Cherif, Guermat, 2016. "The connectedness between crude oil and financial markets: Evidence from implied volatility indices," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 56-69.
    21. Teng, Yue & Shang, Pengjian, 2017. "Transfer entropy coefficient: Quantifying level of information flow between financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 60-70.
    22. Loretta Mastroeni & Pierluigi Vellucci, 2020. "Chaos Versus Stochastic Paradigm in Energy Markets," World Scientific Book Chapters, in: Stéphane Goutte & Duc Khuong Nguyen (ed.), HANDBOOK OF ENERGY FINANCE Theories, Practices and Simulations, chapter 30, pages 765-786, World Scientific Publishing Co. Pte. Ltd..
    23. Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
    24. S. Sabesan & K. Narayanan & A. Prasad & L. D. Iasemidis & A. Spanias & K. Tsakalis, 2007. "Information Flow in Coupled Nonlinear Systems: Application to the Epileptic Human Brain," Springer Optimization and Its Applications, in: Panos M. Pardalos & Vladimir L. Boginski & Alkis Vazacopoulos (ed.), Data Mining in Biomedicine, pages 483-503, Springer.
    25. Scheitrum, Daniel P. & Carter, Colin A. & Revoredo-Giha, Cesar, 2018. "WTI and Brent futures pricing structure," Energy Economics, Elsevier, vol. 72(C), pages 462-469.
    26. Chen, Hongtao & Liu, Li & Li, Xiaolei, 2018. "The predictive content of CBOE crude oil volatility index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 837-850.
    27. Maghyereh, Aktham I. & Awartani, Basel & Bouri, Elie, 2016. "The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 57(C), pages 78-93.
    28. Marina Murdock & Nivine Richie, 2008. "The United States Oil Fund as a hedging instrument," Journal of Asset Management, Palgrave Macmillan, vol. 9(5), pages 333-346, December.
    29. Mastroeni, Loretta & Vellucci, Pierluigi & Naldi, Maurizio, 2018. "Co-existence of stochastic and chaotic behaviour in the copper price time series," Resources Policy, Elsevier, vol. 58(C), pages 295-302.
    30. Mastroeni, Loretta & Vellucci, Pierluigi & Naldi, Maurizio, 2019. "A reappraisal of the chaotic paradigm for energy commodity prices," Energy Economics, Elsevier, vol. 82(C), pages 167-178.
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