[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i14p3906-d249371.html
   My bibliography  Save this article

Nonlinear Relationships between Oil Prices and Implied Volatilities: Providing More Valuable Information

Author

Listed:
  • Jeng-Bau Lin

    (Department of Business Administration, National Chung-Hsing University, Taichung 402, Taiwan)

  • Chin-Chia Liang

    (Department of Finance, Da-Yeh University, Changhua 51591, Taiwan)

  • Wei Tsai

    (Department of Business Administration, National Chung-Hsing University, Taichung 402, Taiwan)

Abstract
This paper investigates the linear/nonlinear long-run and short-run dynamic relationships between oil prices and two implied volatilities, oil price volatility index (OVX) and stock index options volatility index (VIX), representing panic gauges. The results show that there is a long-run equilibrium relationship between oil prices and OVX (VIX) using the linear autoregressive distributed lag (ARDL)-bounds test. Likewise, while using the nonlinear autoregressive distributed lag (NARDL)-bounds test, not only does a long-run equilibrium relationship exist, but also the rising OVX (VIX) has a greater negative influence on oil prices than the declining OVX (VIX), thus indicating that a long-run, asymmetric cointegration exists between the variables. Furthermore, OVX (VIX) oil prices have a linear Granger causality, while for the nonlinear Granger causality test, oil prices have a bidirectional relation with OVX (VIX). In addition, we find that once major international political and economic events occur, structural changes in oil prices change the behavior of oil prices, and thus panic indices, thereby switching from a linear relationship to a nonlinear one. The empirical results of this study provide market participants with more valuable information.

Suggested Citation

  • Jeng-Bau Lin & Chin-Chia Liang & Wei Tsai, 2019. "Nonlinear Relationships between Oil Prices and Implied Volatilities: Providing More Valuable Information," Sustainability, MDPI, vol. 11(14), pages 1-15, July.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:14:p:3906-:d:249371
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/14/3906/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/14/3906/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rafiq, Shuddhasattwa & Bloch, Harry, 2016. "Explaining commodity prices through asymmetric oil shocks: Evidence from nonlinear models," Resources Policy, Elsevier, vol. 50(C), pages 34-48.
    2. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    3. Arouri, Mohamed El Hédi & Lahiani, Amine & Lévy, Aldo & Nguyen, Duc Khuong, 2012. "Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models," Energy Economics, Elsevier, vol. 34(1), pages 283-293.
    4. Fan, Ying & Xu, Jin-Hua, 2011. "What has driven oil prices since 2000? A structural change perspective," Energy Economics, Elsevier, vol. 33(6), pages 1082-1094.
    5. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    6. Ahdi Noomen Ajmi & Ghassen El-montasser & Shawkat Hammoudeh & Duc Khuong Nguyen, 2014. "Oil prices and MENA stock markets: new evidence from nonlinear and asymmetric causalities during and after the crisis period," Applied Economics, Taylor & Francis Journals, vol. 46(18), pages 2167-2177, June.
    7. Dutta, Anupam, 2018. "Oil and energy sector stock markets: An analysis of implied volatility indexes," Journal of Multinational Financial Management, Elsevier, vol. 44(C), pages 61-68.
    8. Zhifang He & Fangzhao Zhou, 2018. "Time-varying and asymmetric effects of the oil-specific demand shock on investor sentiment," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-18, August.
    9. Bampinas Georgios & Panagiotidis Theodore, 2015. "On the relationship between oil and gold before and after financial crisis: linear, nonlinear and time-varying causality testing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 657-668, December.
    10. Gregory, Allan W & Hansen, Bruce E, 1996. "Tests for Cointegration in Models with Regime and Trend Shifts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(3), pages 555-560, August.
    11. repec:ipg:wpaper:2014-079 is not listed on IDEAS
    12. Dergiades, Theologos, 2012. "Do investors’ sentiment dynamics affect stock returns? Evidence from the US economy," Economics Letters, Elsevier, vol. 116(3), pages 404-407.
    13. Perron, Pierre, 1997. "Further evidence on breaking trend functions in macroeconomic variables," Journal of Econometrics, Elsevier, vol. 80(2), pages 355-385, October.
    14. Salisu, Afees A. & Isah, Kazeem O., 2017. "Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach," Economic Modelling, Elsevier, vol. 66(C), pages 258-271.
    15. 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.
    16. Ewing, Bradley T. & Malik, Farooq, 2016. "Volatility spillovers between oil prices and the stock market under structural breaks," Global Finance Journal, Elsevier, vol. 29(C), pages 12-23.
    17. Yu, Lean & Li, Jingjing & Tang, Ling & Wang, Shuai, 2015. "Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach," Energy Economics, Elsevier, vol. 51(C), pages 300-311.
    18. Bekiros, Stelios D. & Diks, Cees G.H., 2008. "The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality," Energy Economics, Elsevier, vol. 30(5), pages 2673-2685, September.
    19. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    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. John Baffes & Varun Kshirsagar, 2016. "Sources of volatility during four oil price crashes," Applied Economics Letters, Taylor & Francis Journals, vol. 23(6), pages 402-406, April.
    22. Atkins, Frank J. & Coe, Patrick J., 2002. "An ARDL bounds test of the long-run Fisher effect in the United States and Canada," Journal of Macroeconomics, Elsevier, vol. 24(2), pages 255-266, June.
    23. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    24. Aboura, Sofiane & Chevallier, Julien, 2013. "Leverage vs. feedback: Which Effect drives the oil market?," Finance Research Letters, Elsevier, vol. 10(3), pages 131-141.
    25. Gu, Rongbao & Zhang, Bing, 2016. "Is efficiency of crude oil market affected by multifractality? Evidence from the WTI crude oil market," Energy Economics, Elsevier, vol. 53(C), pages 151-158.
    26. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    27. Liu, Ming-Lei & Ji, Qiang & Fan, Ying, 2013. "How does oil market uncertainty interact with other markets? An empirical analysis of implied volatility index," Energy, Elsevier, vol. 55(C), pages 860-868.
    28. Robin L. Lumsdaine & David H. Papell, 1997. "Multiple Trend Breaks And The Unit-Root Hypothesis," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 212-218, May.
    29. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    30. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    31. Ji, Qiang & Fan, Ying, 2016. "Modelling the joint dynamics of oil prices and investor fear gauge," Research in International Business and Finance, Elsevier, vol. 37(C), pages 242-251.
    32. Bouri, Elie & Lien, Donald & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Directional predictability of implied volatility: From crude oil to developed and emerging stock markets," Finance Research Letters, Elsevier, vol. 27(C), pages 65-79.
    33. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    34. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    35. Fenghua Wen & Jihong Xiao & Chuangxia Huang & Xiaohua Xia, 2018. "Interaction between oil and US dollar exchange rate: nonlinear causality, time-varying influence and structural breaks in volatility," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 319-334, January.
    36. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    37. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    38. Kumar, Satish, 2017. "On the nonlinear relation between crude oil and gold," Resources Policy, Elsevier, vol. 51(C), pages 219-224.
    39. Fenghua Wen & Jihong Xiao & Xiaohua Xia & Bin Chen & Zhengyan Xiao & Jinyi Li, 2019. "Oil Prices and Chinese Stock Market: Nonlinear Causality and Volatility Persistence," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(6), pages 1247-1263, May.
    40. Bouri, Elie & Jain, Anshul & Biswal, P.C. & Roubaud, David, 2017. "Cointegration and nonlinear causality amongst gold, oil, and the Indian stock market: Evidence from implied volatility indices," Resources Policy, Elsevier, vol. 52(C), pages 201-206.
    41. Junsoo Lee & Mark C. Strazicich, 2003. "Minimum Lagrange Multiplier Unit Root Test with Two Structural Breaks," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1082-1089, November.
    42. Chunyan Hu & Xinheng Liu & Bin Pan & Bin Chen & Xiaohua Xia, 2018. "Asymmetric Impact of Oil Price Shock on Stock Market in China: A Combination Analysis Based on SVAR Model and NARDL Model," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(8), pages 1693-1705, June.
    43. 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.
    44. Ghosh, Sajal & Kanjilal, Kakali, 2016. "Co-movement of international crude oil price and Indian stock market: Evidences from nonlinear cointegration tests," Energy Economics, Elsevier, vol. 53(C), pages 111-117.
    45. Robin C. Sickles & William C. Horrace (ed.), 2014. "Festschrift in Honor of Peter Schmidt," Springer Books, Springer, edition 127, number 978-1-4899-8008-3, December.
    46. repec:dau:papers:123456789/9860 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bechir Raggad & Elie Bouri, 2023. "Quantile Dependence between Crude Oil Returns and Implied Volatility: Evidence from Parametric and Nonparametric Tests," Mathematics, MDPI, vol. 11(3), pages 1-23, January.
    2. Li, Shuping & Li, Jianfeng & Lu, Xinsheng & Sun, Yihong, 2022. "Exploring the dynamic nonlinear relationship between crude oil price and implied volatility indices: A new perspective from MMV-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    3. Marina V. Vasiljeva & Vadim V. Ponkratov & Larisa A. Vatutina & Maria V. Volkova & Marina I. Ivleva & Elena V. Romanenko & Nikolay V. Kuznetsov & Nadezhda N. Semenova & Elena F. Kireeva & Dmitrii K. G, 2022. "Crude Oil Market Functioning and Sustainable Development Goals: Case of OPEC++-Participating Countries," Sustainability, MDPI, vol. 14(8), pages 1-23, April.
    4. Li Jingjing & Tang Ling & Li Ling, 2020. "The Co-Movements Between Crude Oil Price and Internet Concerns: Causality Analysis in the Frequency Domain," Journal of Systems Science and Information, De Gruyter, vol. 8(3), pages 224-239, June.
    5. Parminder KAUR & Ravi SINGLA, 2023. "Asymmetric Effects of Commodity Prices on Stock Returns of BRICS Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 145-164, March.
    6. Yang, Jinxuan & Rizvi, Syed Kumail Abbas & Tan, Zhixiong & Umar, Muhammad & Koondhar, Mansoor Ahmed, 2021. "The competing role of natural gas and oil as fossil fuel and the non-linear dynamics of resource curse in Russia," Resources Policy, Elsevier, vol. 72(C).
    7. Krzysztof Echaust & Małgorzata Just, 2021. "Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic," Energies, MDPI, vol. 14(14), pages 1-21, July.
    8. Jeng-Bau Lin & Wei Tsai, 2019. "The Relations of Oil Price Change with Fear Gauges in Global Political and Economic Environment," Energies, MDPI, vol. 12(15), pages 1-17, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jeng-Bau Lin & Wei Tsai, 2019. "The Relations of Oil Price Change with Fear Gauges in Global Political and Economic Environment," Energies, MDPI, vol. 12(15), pages 1-17, August.
    2. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, June.
    3. Tarlok Singh, 2017. "Are Current Account Deficits in the OECD Countries Sustainable? Robust Evidence from Time-Series Estimators," The International Trade Journal, Taylor & Francis Journals, vol. 31(1), pages 29-64, January.
    4. Li, Shuping & Li, Jianfeng & Lu, Xinsheng & Sun, Yihong, 2022. "Exploring the dynamic nonlinear relationship between crude oil price and implied volatility indices: A new perspective from MMV-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    5. De Vita, Glauco & Trachanas, Emmanouil, 2016. "‘Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India’ — A failed replication (negative Type 1 and Type 2)," Energy Economics, Elsevier, vol. 56(C), pages 150-160.
    6. Heidari, Hassan & Katircioglu, Salih Turan & Davoudi, Narmin, 2012. "Are current account deficits sustainable? New evidence from Iran using bounds test approach to level relationships," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-18.
    7. Kyriakos Emmanouilidis & Christos Karpetis, 2020. "The Defense–Growth Nexus: A Review of Time Series Methods and Empirical Results," Defence and Peace Economics, Taylor & Francis Journals, vol. 31(1), pages 86-104, January.
    8. Brittle, Shane, 2009. "Ricardian Equivalence and the Efficacy of Fiscal Policy in Australia," Economics Working Papers wp09-10, School of Economics, University of Wollongong, NSW, Australia.
    9. David Greasley & Les Oxley, 2010. "Cliometrics And Time Series Econometrics: Some Theory And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 24(5), pages 970-1042, December.
    10. Dutta, Anupam & Bouri, Elie & Roubaud, David, 2019. "Nonlinear relationships amongst the implied volatilities of crude oil and precious metals," Resources Policy, Elsevier, vol. 61(C), pages 473-478.
    11. Vicente Esteve, 2004. "Política fiscal y productividad del trabajo en la economía española: un análisis de series temporales," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 19(1), pages 3-29, June.
    12. Maghyereh, Aktham & Abdoh, Hussein & Awartani, Basel, 2022. "Have returns and volatilities for financial assets responded to implied volatility during the COVID-19 pandemic?," Journal of Commodity Markets, Elsevier, vol. 26(C).
    13. Troster, Victor & Bouri, Elie & Roubaud, David, 2019. "A quantile regression analysis of flights-to-safety with implied volatilities," Resources Policy, Elsevier, vol. 62(C), pages 482-495.
    14. Makin, Anthony J. & Ratnasiri, Shyama, 2015. "Competitiveness and government expenditure: The Australian example," Economic Modelling, Elsevier, vol. 49(C), pages 154-161.
    15. Xiao, Jihong & Hu, Chunyan & Ouyang, Guangda & Wen, Fenghua, 2019. "Impacts of oil implied volatility shocks on stock implied volatility in China: Empirical evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 80(C), pages 297-309.
    16. Alqahtani, Abdullah & Klein, Tony, 2021. "Oil price changes, uncertainty, and geopolitical risks: On the resilience of GCC countries to global tensions," Energy, Elsevier, vol. 236(C).
    17. Ogali, Oscar I.O. & Okoro, Emeka E. & Olafuyi, Saburi G., 2023. "Assessing consensus on nexus between natural gas consumption and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    18. Dakpogan, Arnaud & Smit, Eon, 2018. "The effect of electricity losses on GDP in Benin," MPRA Paper 89545, University Library of Munich, Germany.
    19. Adewuyi, Adeolu O. & Ogebe, Joseph O., 2019. "The validity of uncovered interest parity: Evidence from african members and non-member of the organisation of petroleum exporting countries (OPEC)," Economic Modelling, Elsevier, vol. 82(C), pages 229-249.
    20. Giorgio Canarella & Rangan Gupta & Stephen M. Miller & Stephen K. Pollard, 2019. "Unemployment rate hysteresis and the great recession: exploring the metropolitan evidence," Empirical Economics, Springer, vol. 56(1), pages 61-79, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:14:p:3906-:d:249371. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.