IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v80y2019icp277-296.html
   My bibliography  Save this article

Temporal and spectral dependence between crude oil and agricultural commodities: A wavelet-based copula approach

Author

Listed:
  • Yahya, Muhammad
  • Oglend, Atle
  • Dahl, Roy Endré

Abstract

This paper investigates the temporal and frequency domain connectedness between the price of crude oil and ten major agricultural commodities. We decompose returns into short-, medium- and long-run movements using the MODWT and investigate cross-commodities dependence structures in the decomposed returns using a DCC-Student-t copula. The method allows us to analyze variation in dependencies across time as well as frequencies of return movements. Structural variation is considered through subsample analysis. Consistent with previous research, we find that connectedness between oil and agricultural products increases post-2006 across all considered frequencies of return movements. However, the rate of increase is higher for longer investment horizons. The wavelet decomposition reveals that interconnectedness as a function of investment horizon is negative during the pre-2006, but positive during the post-2006 subsample. These findings support stronger connectedness primarily due to stronger connection between long-run return movements. Analysis of connectedness dynamics shows no strong pre- and post-2006 differences, suggesting that the recent higher connectedness is primarily a correlation level effect. We do find that persistence of connectedness variation is higher for long-run return movements. Overall, we document a more connected crude oil and agricultural commodities complex after 2006, with lower commodities diversification benefits in general, and higher correlation risk for longer investment horizons.

Suggested Citation

  • Yahya, Muhammad & Oglend, Atle & Dahl, Roy Endré, 2019. "Temporal and spectral dependence between crude oil and agricultural commodities: A wavelet-based copula approach," Energy Economics, Elsevier, vol. 80(C), pages 277-296.
  • Handle: RePEc:eee:eneeco:v:80:y:2019:i:c:p:277-296
    DOI: 10.1016/j.eneco.2019.01.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S014098831930026X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2019.01.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Berger, Theo & Gençay, Ramazan, 2018. "Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 30-46.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Xiaodong Du and Lihong Lu McPhail, 2012. "Inside the Black Box: the Price Linkage and Transmission between Energy and Agricultural Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    4. Vacha, Lukas & Barunik, Jozef, 2012. "Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis," Energy Economics, Elsevier, vol. 34(1), pages 241-247.
    5. Christiane Baumeister & Lutz Kilian, 2014. "Do oil price increases cause higher food prices? [Biofuels, binding constraints, and agricultural commodity price volatility]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 29(80), pages 691-747.
    6. Gallegati, Marco, 2012. "A wavelet-based approach to test for financial market contagion," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3491-3497.
    7. Nazlioglu, Saban & Soytas, Ugur, 2011. "World oil prices and agricultural commodity prices: Evidence from an emerging market," Energy Economics, Elsevier, vol. 33(3), pages 488-496, May.
    8. Fowowe, Babajide, 2016. "Do oil prices drive agricultural commodity prices? Evidence from South Africa," Energy, Elsevier, vol. 104(C), pages 149-157.
    9. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    10. Pal, Debdatta & Mitra, Subrata K., 2017. "Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis," Energy Economics, Elsevier, vol. 62(C), pages 230-239.
    11. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 535-551, December.
    12. Liu, Li & Ma, Guofeng, 2014. "Cross-correlation between crude oil and refined product prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 284-293.
    13. Berger, Theo, 2015. "A wavelet based approach to measure and manage contagion at different time scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 338-350.
    14. Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2011. "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," Energy Economics, Elsevier, vol. 33(3), pages 497-503, May.
    15. Wang, Sun Ling & McPhail, Lihong, 2014. "Impacts of energy shocks on US agricultural productivity growth and commodity prices—A structural VAR analysis," Energy Economics, Elsevier, vol. 46(C), pages 435-444.
    16. Dewandaru, Ginanjar & Masih, Rumi & Masih, A. Mansur M., 2015. "Why is no financial crisis a dress rehearsal for the next? Exploring contagious heterogeneities across major Asian stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 241-259.
    17. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2014. "Oil price shocks and agricultural commodity prices," Energy Economics, Elsevier, vol. 44(C), pages 22-35.
    18. Hanson, Kenneth & Robinson, Sherman & Schluter, Gerald E., 1993. "Sectoral Effects Of A World Oil Price Shock: Economywide Linkages To The Agricultural Sector," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(1), pages 1-21, July.
    19. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Huang, Xuan, 2016. "Time–frequency featured co-movement between the stock and prices of crude oil and gold," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 985-995.
    20. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    21. Marco Gallegati & Willi Semmler (ed.), 2014. "Wavelet Applications in Economics and Finance," Dynamic Modeling and Econometrics in Economics and Finance, Springer, edition 127, number 978-3-319-07061-2, July-Dece.
    22. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    23. Gençay, Ramazan & Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon J., 2001. "An Introduction to Wavelets and Other Filtering Methods in Finance and Economics," Elsevier Monographs, Elsevier, edition 1, number 9780122796708.
    24. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    25. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," The Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    26. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    27. Huang, Xuan & An, Haizhong & Gao, Xiangyun & Hao, Xiaoqing & Liu, Pengpeng, 2015. "Multiresolution transmission of the correlation modes between bivariate time series based on complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 493-506.
    28. Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.
    29. Berger, Theo & Uddin, Gazi Salah, 2016. "On the dynamic dependence between equity markets, commodity futures and economic uncertainty indexes," Energy Economics, Elsevier, vol. 56(C), pages 374-383.
    30. Bekiros, Stelios & Nguyen, Duc Khuong & Sandoval Junior, Leonidas & Uddin, Gazi Salah, 2017. "Information diffusion, cluster formation and entropy-based network dynamics in equity and commodity markets," European Journal of Operational Research, Elsevier, vol. 256(3), pages 945-961.
    31. Nazlioglu, Saban, 2011. "World oil and agricultural commodity prices: Evidence from nonlinear causality," Energy Policy, Elsevier, vol. 39(5), pages 2935-2943, May.
    32. Koirala, Krishna H. & Mishra, Ashok K. & D'Antoni, Jeremy M. & Mehlhorn, Joey E., 2015. "Energy prices and agricultural commodity prices: Testing correlation using copulas method," Energy, Elsevier, vol. 81(C), pages 430-436.
    33. Geetesh Bhardwaj & Gary Gorton & Geert Rouwenhorst, 2015. "Facts and Fantasies about Commodity Futures Ten Years Later," NBER Working Papers 21243, National Bureau of Economic Research, Inc.
    34. Liu, Li, 2014. "Cross-correlations between crude oil and agricultural commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 293-302.
    35. Robert J. Myers & Stanley R. Johnson & Michael Helmar & Harry Baumes, 2014. "Long-run and Short-run Co-movements in Energy Prices and the Prices of Agricultural Feedstocks for Biofuel," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(4), pages 991-1008.
    36. Mensi, Walid & Tiwari, Aviral & Bouri, Elie & Roubaud, David & Al-Yahyaee, Khamis H., 2017. "The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indexes," Energy Economics, Elsevier, vol. 66(C), pages 122-139.
    37. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    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. Dahl, Roy Endré & Oglend, Atle & Yahya, Muhammad, 2020. "Dynamics of volatility spillover in commodity markets: Linking crude oil to agriculture," Journal of Commodity Markets, Elsevier, vol. 20(C).
    2. Hanif, Waqas & Areola Hernandez, Jose & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2021. "Tail dependence risk and spillovers between oil and food prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 195-209.
    3. Naeem, Muhammad Abubakr & Hasan, Mudassar & Arif, Muhammad & Suleman, Muhammad Tahir & Kang, Sang Hoon, 2022. "Oil and gold as a hedge and safe-haven for metals and agricultural commodities with portfolio implications," Energy Economics, Elsevier, vol. 105(C).
    4. Tiwari, Aviral Kumar & Khalfaoui, Rabeh & Solarin, Sakiru Adebola & Shahbaz, Muhammad, 2018. "Analyzing the time-frequency lead–lag relationship between oil and agricultural commodities," Energy Economics, Elsevier, vol. 76(C), pages 470-494.
    5. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    6. Yip, Pick Schen & Brooks, Robert & Do, Hung Xuan & Nguyen, Duc Khuong, 2020. "Dynamic volatility spillover effects between oil and agricultural products," International Review of Financial Analysis, Elsevier, vol. 69(C).
    7. Cheng, Natalie Fang Ling & Hasanov, Akram Shavkatovich & Poon, Wai Ching & Bouri, Elie, 2023. "The US-China trade war and the volatility linkages between energy and agricultural commodities," Energy Economics, Elsevier, vol. 120(C).
    8. Pal, Debdatta & Mitra, Subrata K., 2019. "Correlation dynamics of crude oil with agricultural commodities: A comparison between energy and food crops," Economic Modelling, Elsevier, vol. 82(C), pages 453-466.
    9. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    10. Mensi, Walid & Tiwari, Aviral & Bouri, Elie & Roubaud, David & Al-Yahyaee, Khamis H., 2017. "The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indexes," Energy Economics, Elsevier, vol. 66(C), pages 122-139.
    11. Cao, Yan & Cheng, Sheng, 2021. "Impact of COVID-19 outbreak on multi-scale asymmetric spillovers between food and oil prices," Resources Policy, Elsevier, vol. 74(C).
    12. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    13. Tiwari, Aviral Kumar & Boachie, Micheal Kofi & Suleman, Muhammed Tahir & Gupta, Rangan, 2021. "Structure dependence between oil and agricultural commodities returns: The role of geopolitical risks," Energy, Elsevier, vol. 219(C).
    14. Khaled Mokni & Manel Youssef, 2020. "Empirical analysis of the cross‐interdependence between crude oil and agricultural commodity markets," Review of Financial Economics, John Wiley & Sons, vol. 38(4), pages 635-654, October.
    15. Pal, Debdatta & Mitra, Subrata K., 2017. "Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis," Energy Economics, Elsevier, vol. 62(C), pages 230-239.
    16. Yoon, Seong-Min, 2022. "On the interdependence between biofuel, fossil fuel and agricultural food prices: Evidence from quantile tests," Renewable Energy, Elsevier, vol. 199(C), pages 536-545.
    17. Mokni, Khaled & Ben-Salha, Ousama, 2020. "Asymmetric causality in quantiles analysis of the oil-food ‏ ‏nexus since the 1960s," Resources Policy, Elsevier, vol. 69(C).
    18. Ahmadi, Maryam & Bashiri Behmiri, Niaz & Manera, Matteo, 2016. "How is volatility in commodity markets linked to oil price shocks?," Energy Economics, Elsevier, vol. 59(C), pages 11-23.
    19. Kang, Sang Hoon & Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu & Yoon, Seong-Min, 2019. "Exploring the time-frequency connectedness and network among crude oil and agriculture commodities V1," Energy Economics, Elsevier, vol. 84(C).
    20. Eissa, Mohamad Abdelaziz & Al Refai, Hisham, 2019. "Modelling the symmetric and asymmetric relationships between oil prices and those of corn, barley, and rapeseed oil," Resources Policy, Elsevier, vol. 64(C).

    More about this item

    Keywords

    Crude oil; Agricultural commodities; Dependence; Wavelet analysis; Copula;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    Statistics

    Access and download statistics

    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:eee:eneeco:v:80:y:2019:i:c:p:277-296. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.