Skip to main content

Volatility Linkages Between Price Returns of Crude Oil and Crude Palm Oil in the ASEAN Region: A Copula Based GARCH Approach

  • Conference paper
  • First Online:
Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2015)

Abstract

This paper used the copula based ARMA-GARCH to examine the dependence structure between the weekly prices of two commodities, namely Crude oil and Crude palm oil. We found evidence of a weak positive dependence between two commodities prices. These findings suggest that the crude oil market of the Middle East and the crude palm oil market of Malaysia are linked together. This information is useful for decision making in various area, such as the risk management in financial field and the international trade in agricultural commodities.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. USDA: Table 11: Palm Oil: World Supply and Distribution. United States Department of Agriculture (2015). https://apps.fas.usda.gov/psdonline/circulars/oilseeds.pdf/ (accessed April 16, 2015)

  2. Sheil, D., et al.: The impacts and opportunities of oil palm in Southeast Asia: What do we know and what do we need to know? Occasional paper no. 51. CIFOR, Bogor, Indonesia (2009)

    Google Scholar 

  3. Baffes, J.: Oil spills on other commodities. Resources Policy 32, 126–134 (2007)

    Article  Google Scholar 

  4. Balcombe, K.: The nature and determinants of volatility in agricultural prices: an empirical study. In: Prakash, A. (ed.) Safeguarding Food Security in Volatile Global Markets, pp. 85–106. FAO, Rome (2011)

    Google Scholar 

  5. Nazlioglu, S., Soytas, U.: Oil Price, agricultural commodity prices, and the dollar: a panel cointegration and causality analysis. Energy Economics 34, 1098–1104 (2012)

    Article  Google Scholar 

  6. Asian Development Bank: Global food price inflation and developing Asia. Asian Development Bank (2011). http://www.adb.org/publications/global-food-price-inflation-and-developing-asia (accessed May 23, 2013)

  7. Arshad, F.M., Abdel Hameed, A.A.: Crude Oil, Palm Oil Stock and Prices: How They Link. Review of Economics & Finance 3, 48–57 (2012)

    Google Scholar 

  8. Kochaphum, C., et al.: Does biodiesel demand affect palm oil prices in Thailand? Energy for Sustainable Development 17, 658–670 (2013)

    Article  Google Scholar 

  9. Mukherjee, I., Sovacool, B.K.: Palm oil-based biofuels and sustainability in southeast Asia: A review of Indonesia, Malaysia, and Thailand. Renewable and Sustainable Energy Reviews 37, 1–12 (2014)

    Article  Google Scholar 

  10. Johari, A., et al.: The challenges and prospects of palm oil based biodiesel in Malaysia. Energy 81, 255–261 (2015)

    Article  Google Scholar 

  11. Speed, P.A.: ASEAN. The 45 Year Evolution of a Regional Institution. POLINARES working paper no. 61, University of Westminster (2012)

    Google Scholar 

  12. Reboredo, J.C.: How do crude oil prices co-move? A copula approach. Energy Economics 33, 948–955 (2011)

    Article  Google Scholar 

  13. Kiatmanaroch, T., Sriboonchitta, S.: Dependence Structure between World Crude Oil Prices: Evidence from NYMEX, ICE, and DME Markets. Thai Journal of Mathematics, Special Issue on Copula Mathematics and Econometrics 181–198 (2014)

    Google Scholar 

  14. Adelman, M.A.: International oil agreements. The Energy Journal 5, 1–9 (1984)

    Google Scholar 

  15. Adelman, M.A.: Is the world oil market “One Great Pool”?-Comment. The Energy Journal 13, 95–107 (1992)

    Article  Google Scholar 

  16. Sriboonchitta, S., et al.: Modeling volatility and dependency of agricultural price and production indices of Thailand: Static versus time-varying copulas. International Journal of Approximate Reasoning 54(6), 793–808 (2013)

    Article  Google Scholar 

  17. Kiatmanaroch, T., Sriboonchitta, S.: Relationship between exchange rates, palm oil prices, and crude oil prices: a vine copula based GARCH approach. In: Huynh, V.-N., Kreinovich, V., Sriboonchitta, S. (eds.) Modeling Dependence in Econometrics. AISC, vol. 251, pp. 399–413. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  18. Puarattanaarunkorn, O., et al.: Dependence Structure between TOURISM and TRANS Sector Indices of the Stock Exchange of Thailand. Thai Journal of Mathematics. Special Issue on: Copula Mathematics and Econometrics 199–210 (2014)

    Google Scholar 

  19. Sriboonchitta, S., Liu, J., Wiboonpongse, A.: Vine copula-cross entropy evaluation of dependence structure and financial risk in agricultural commodity index returns. In: Huynh, V.-N., Kreinovich, V., Sriboonchitta, S. (eds.) Modeling Dependence in Econometrics. AISC, vol. 251, pp. 275–287. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  20. Bollerslev, T.: Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics 31, 307–327 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  21. Sklar, A.: Fonctions de rpartition n dimensions et leurs marges. Publications de l’Institut de Statistique de L’Université de Paris 8, 229–231 (1959)

    MathSciNet  Google Scholar 

  22. Nelson, R.B.: An Introduction to Copulas, 2nd edn. Springer, New York (2006)

    Google Scholar 

  23. Joe, H.: Multivariate Models and Dependence Concepts. Chapman and Hall, London (1997)

    Book  MATH  Google Scholar 

  24. Trivedi, P.K., Zimmer, D.M.: Copula Modeling: An Introduction for Practitioners. Foundations and Trends in Econometrics 1(1), 1–111 (2005)

    Article  MATH  Google Scholar 

  25. Genest, C., Rivest, L.P.: Statistical Inference Procedures for Bivariate Archimedean Copulas. Journal of the American Statistical Association 88(423), 1034–1043 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  26. Genest, C., et al.: A Semiparametric Estimation Procedure of Dependence Parameters in Multivariate Families of Distributions. Biometrika 82, 543–552 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  27. Embrechts, P., Lindskog, F., McNeil, A.J.: Modelling dependence with copulas and application to risk management. In: Rachev, S.T. (ed.) Handbook of heavy tailed distribution in finance. Elsevier, Amsterdam (2003)

    Google Scholar 

  28. Cherubini, U., Luciano, E., Vecchiato, W.: Copula methods in finance. Wiley, London (2004)

    Book  MATH  Google Scholar 

  29. Artzner, P., et al.: Coherent measures of risk. Mathematical Finance 9(3), 203–228 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  30. Sheppard, K.: Financial Econometrics Notes. University of Oxford (2013)

    Google Scholar 

  31. Sriboonchitta, S., Liu, J., Kreinovich, V., Nguyen, H.T.: A vine copula approach for analyzing financial risk and co-movement of the Indonesian, Philippine and Thailand stock markets. In: Huynh, V.-N., Kreinovich, V., Sriboonchitta, S. (eds.) Modeling Dependence in Econometrics. AISC, vol. 251, pp. 245–257. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  32. Ouyang, Z., Liao, H., Yang, X.: Modeling dependence based on mixture copulas and its application in risk management. Appl. Math. J. Chinese Univ. 24(4), 393–401 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  33. Autchariyapanitkul, K. et al.: Portfolio optimization of stock returns in high-dimensions: A copula-based approach. Thai Journal of Mathematics. Special Issue on: Copula Mathematics and Econometrics 11–23 (2014)

    Google Scholar 

  34. Serra, T., Zilberman, D.: Biofuel-related price transmission literature: A review. Energy Economics 37, 141–151 (2013)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Songsak Sriboonchitta .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Kiatmanaroch, T., Puarattanaarunkorn, O., Autchariyapanitkul, K., Sriboonchitta, S. (2015). Volatility Linkages Between Price Returns of Crude Oil and Crude Palm Oil in the ASEAN Region: A Copula Based GARCH Approach. In: Huynh, VN., Inuiguchi, M., Demoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2015. Lecture Notes in Computer Science(), vol 9376. Springer, Cham. https://doi.org/10.1007/978-3-319-25135-6_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-25135-6_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25134-9

  • Online ISBN: 978-3-319-25135-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics