Skip to main content

Relationship between Exchange Rates, Palm Oil Prices, and Crude Oil Prices: A Vine Copula Based GARCH Approach

  • Conference paper
Modeling Dependence in Econometrics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 251))

Abstract

The dollar is the leading international currency, and it is used widely in the majority of international financial transactions. The various food products that comprise agricultural commodities, as also crude oil, have been using the dollar exchange rate for international trade. Over the past several years, the changes in the dollar exchange rate have shown more volatility in addition to a depreciation trend, which has had an influence on the prices of those commodities. We analyzed the relationship between the dollar exchange rates and the prices of two commodities, palm oil and crude oil, by using the GARCH(1,1) model to examine the volatility of the exchange rates and the future prices 1-Pos. of the prices of both the commodities. The vine copula model is used to analyze the dependence structure between their marginal distributions. The data analyses were based on the daily observations from June 2007 to March 2013. The empirical results of GARCH(1,1) show that the exchange rates, palm oil prices, and crude oil prices have a long-run persistence in volatility. The C-vine copula model reveals that there exists a weak negative dependence for each pair-copula, that is, Exchange rate-Palm oil (E,P) and Exchange rate-Crude oil (E,C) in tree 1. Also, a conditional pair-copula of Palm oil-Crude oil given Exchange rate (P,C|E) in tree 2 offers a weak positive dependence. Moreover, the findings of this study provide evidence that the exchange rate (E) is an important variable that governs the interactions in the dependence structure between palm oil price (P) and crude oil price (C).

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 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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. 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)

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

    Article  Google Scholar 

  3. Abbott, P.C., et al.: What’s Driving Food Prices? Farm Foundation Issue Report (July 2008)

    Google Scholar 

  4. Harri, A., et al.: The relationship between oil, exchange rates, and commodity prices. Journal of Agricultural and Applied Economics 41, 501–510 (2009)

    Google Scholar 

  5. Harri, A., Hudson, D.: Mean and variance dynamics between agricultural commodity prices and crude oil prices. Paper presented at the Economics of Alternative Energy Sources and Globalization, The Road Ahead Meeting, Orlando, FL, November 15-17 (2009)

    Google Scholar 

  6. Kwon, D., Koo, W.W.: Price transmission channels of energy and exchange rate on food sector: a disaggregated approach based on stage of process. Selected Paper prepared for presentation at the Agricultural & Applied Economics Association 2009 AAEA & ACCI Joint Annual Meeting, Milwaukee, Wisconsin, July 26-29 (2009)

    Google Scholar 

  7. Akram, Q.F.: Commodity Prices, Interest Rates and the Dollar. Energy Economics 31, 838–851 (2009)

    Article  Google Scholar 

  8. Cooke, B., Robles, M.: Recent Food Prices Movements. A Time Series Analysis. International Food Policy Research Institute (IFPRI) Discussion Paper No. 00942. IFPRI, Washington DC (2009)

    Google Scholar 

  9. Gilbert, C.L.: How to understand high food prices. Journal of Agricultural Economics 61(2), 398–425 (2010)

    Article  Google Scholar 

  10. 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 

  11. 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 

  12. Anzuini, et al.: The impact of monetary policy shocks on commodity prices. Working paper No. 851, Bank of Italy (2012)

    Google Scholar 

  13. ASEAN Secretariat. Regional and Country Reports of the ASEAN Assessment on the Social Impact of the Global Financial Crisis. The ASEAN Secretariat (2010), http://www.asean.org/archive/publications/ARCR/ASEANRegional&CountryReport.pdf (accessed May 20, 2013)

  14. FAO. Declaration of the world summit on food security. World Summit on Food Security, Rome, November 16-18 (2009), ftp://ftp.fao.org/docrep/fao/Meeting/018/k6050e.pdf (accessed May 20, 2013)

  15. United Nations. World Energy Assessment: Overview 2004 Update. United Nations Development Programme (2004), http://www.undp.org/content/dam/aplaws/publication/en/

  16. ASEAN Secretariat. ASEAN Community in a Global Community of Nations.Co-Chairs’ statement of the 4th ASEAN-UN summit Bali, Indonesia (November 19, 2011), http://www.mofa.go.jp/region/asia-paci/eas/pdfs/declaration_1111_2.pdf (accessed May 20, 2013)

  17. Abbott, P.C., et al.: What’s Driving Food Prices in 2011? Farm Foundation Issue Report (July 2011)

    Google Scholar 

  18. 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 

  19. Speed, P.A.: ASEAN. The 45 Year Evolution of a Regional Institution. POLINARES working paper n. 61, University of Westminster (2012), http://www.polinares.eu/docs/d4-1/polinares_wp4_chapter11.pdf (accessed May 27, 2003)

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

    Article  Google Scholar 

  21. 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 

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

    Article  MathSciNet  MATH  Google Scholar 

  23. Brechmann, E.C., Schepsmeier, U.: Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine. Journal of Statistical Software 52(3), 1–27 (2013), http://www.jstatsoft.org/v52/i03/ (accessed February 20, 2013)

    Google Scholar 

  24. Wuertz, D., Chalabi, Y.: Rmetrics-Autoregressive Conditional Heteroskedastic Modelling (2013), http://cran.r-project.org/web/packages/fGarch/index.html (accessed May 10, 2013)

  25. Sklar, A.: Fonctions de répartition á n dimensions etleursmarges. Publications de l’Institut de Statistique de L’Université de Paris 8, 229–231 (1959)

    MathSciNet  Google Scholar 

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

    Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  28. Fisher, M.: Tailoring copula-based multivariate generalized hyperbolic secant distributions to financial return data: An empirical investigation. Discussion papers, University of Erlangen-Nüremberg, Germany (2003), http://www.statistik.wiso.uni-erlangen.de/forschung/d0047.pdf (accessed January 25, 2013)

  29. Joe, H.: Families of m-Variate Distributions with Given Margins and m(m1)/2 Bivariate Dependence Parameters. In: Rüschendorf, L., Schweizer, B., Taylor, M.D. (eds.) Distributions with Fixed Marginals and Related Topics, vol. 28, pp. 120–141 (1996)

    Google Scholar 

  30. Bedford, T., Cooke, R.M.: Probability Density Decomposition for Conditionally Dependent Random Variables Modeled by Vines. Annals of Mathematics and Artificial Intelligence 32, 245–268 (2001)

    Google Scholar 

  31. Bedford, T., Cooke, R.M.: Vines- A New Graphical Model for Dependent Random Variables. Annals of Statistics 30, 1031–1068 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  32. Aas, K., et al.: Pair-copula constructions of multiple dependence. Insurance: Mathematics and Economics 44, 182–198 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  33. Koyama, K.: A Though on Crude Oil Pricing in Asia. The institute of energy economics, Japan (2011), https://eneken.ieej.or.jp/data/3711.pdf (accessed May 27, 2013)

  34. Patton, A.J.: Modelling Asymmetric Exchange Rate Dependence. International Economic Review 47(2), 527–556 (2006)

    Article  MathSciNet  Google Scholar 

  35. Manthos, V.: Dynamic Copula Toolbox 3.0 (2010), http://www.mathworks.com/matlabcentral/fileexchange/29303-dynamic-copula-toolbox-3-0 (accessed December 15, 2012)

  36. Lim, S., Teong, L.K.: Recent trends, opportunities and challenges of biodiesel in Malaysia: An overview. Renewable and Sustainable Energy Reviews 14, 938–954 (2010)

    Article  Google Scholar 

  37. Gasparatos, A., et al.: Sustainability impacts of first-generation biofuels. Animal Frontiers 3(2), 1–15 (2013), doi:10.2527/af.2013-0011

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Teera Kiatmanaroch .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Kiatmanaroch, T., Sriboonchitta, S. (2014). Relationship between Exchange Rates, Palm Oil Prices, and Crude Oil Prices: A Vine Copula Based GARCH Approach. In: Huynh, VN., Kreinovich, V., Sriboonchitta, S. (eds) Modeling Dependence in Econometrics. Advances in Intelligent Systems and Computing, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-319-03395-2_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-03395-2_25

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03394-5

  • Online ISBN: 978-3-319-03395-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics