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Determining the Relationship Between Energy and Agricultural Commodities with the ARDL Model

Year 2022, Volume: 24 Issue: 2, 147 - 160, 30.12.2022

Abstract

The daily volatility in the prices of energy and agricultural commodities is one of the most important factors that push investors to trade in these markets. For those who invest in energy and agricultural commodities while creating a portfolio, the relationship between these commodities should be determined correctly. If the position taken is actually wrong, it is inevitable to encounter an unexpected loss. Therefore, taking positions by knowing the relationship between both long-term and short-term will help investors increase their returns or close positions with the least loss.
This study was carried out in order to determine the long-term relationship between energy and agricultural commodities. WTI oil, diesel and natural gas were selected as energy commodities, wheat, cocoa and cotton were selected as agricultural commodities, and analyzes were made with the ARDL model. As a result of the analysis, it has been determined that there is a long-term relationship between WTI oil taken as a dependent variable, and other commodities taken as an independent variable. This result indicates that energy and agricultural commodities move together in the long run and it is necessary to be careful while creating a portfolio based on them.

References

  • Baffes, & Dennis (2015). Long-Term Drivers of Food Prices. Trade Policy and Food Security Improving Access to Food in Developing Countries in the Wake of High World Prices (Ian Gillson & Amir Fouad, ed.), World Bank Group, 13-36.
  • Byrne, J. P., Fazio, G. & Fiess, N. (2013). Primary Commodity Prices: Co-Movements, Common Factors And Fundamentals. Journal of Development Economics, 101, 16-26.
  • Chen, S-T., Kuo, H-I. & Chen, C-C (2010). Modeling The Relationship Between The Oil Price And Global Food Prices. Applied Energy, 87 (8), 2517-2525.
  • Coronado, S., Rojas, O. Romero-Meza, R. Serletis, A. & Chiu, L. V. (2018). Crude Oil and Biofuel Agricultural Commodity Prices. Uncertainty, Expectations and Asset Price Dynamics (Fredj Jawadi ed.), 107-123.
  • De Nicola, F., De Pace, P. & Hernandez, M. A. (2016). Co-Movement Of Major Energy, Agricultural, And Food Commodity Price Returns: A Time-Series Assessment, Energy Economics, 57 (C), 28-41.
  • Du, X., Yu, C. L. & Hayes, D. J. (2011). Speculation And Volatility Spillover In The Crude Oil And Agricultural Commodity Markets: A Bayesian Analysis. Energy Economics, 33 (3), 497-503.
  • Engle, R. F. & Granger, W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55 (2), 251-276.
  • Fowowe, B. (2016). Do Oil Prices Drive Agricultural Commodity Prices? Evidence From South Africa. Energy, 104, 149-157.
  • Gülerce, M. & Ünal, G. (2017). Forecasting Of Oil And Agricultural Commodity Prices: Varma Versus Arma. Annals of Financial Economics, 12 (3), 1-30.
  • Ibrahim, M. H. (2015). Oil And Food Prices In Malaysia: A Nonlinear ARDL Analysis. Ibrahim Agricultural and Food Economics, 3 (1), 1-14.
  • Jadidzadeh, A. & Serletis, A. (2018). The Global Crude Oil Market And Biofuel Agricultural Commodity Prices. The Journal of Economic Asymmetries, 18, 1-9.
  • Johansen, S. & Juselius, K. (1990). Maximum Likelihood Estimation And Inference On Cointegration —With Applications To The Demand For Money. OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 52 (2), 169-210.
  • Karakotsios, A., Katrakilidis, C. & Kroupis, N. (2021). The Dynamic Linkages Between Food Prices And Oil Prices. Does Asymmetry Matter?. The Journal of Economic Asymmetries, 23, 1-10.
  • Kumar, S., Choudhary, S., Singh, G. & Singha, S. (2021). Crude Oil, Gold, Natural Gas, Exchange Rate And Indian Stock Market: Evidence From The Asymmetric Nonlinear ARDL Model. Resources Policy, 73, 1-7.
  • Lucotte, Y. (2016). Co-movements Between Crude Oil And Food Prices: A Post-Commodity Boom Perspective. Economics Letters, 147, 142-147.
  • Nazlıoğlu, Ş. (2011). World Oil And Agricultural Commodity Prices: Evidence From Nonlinear Causality. Energy Policy, 39 (5), 2935-2943.
  • Nazlıoğlu, Ş. & Soytaş, U. (2012). Oil Price, Agricultural Commodity Prices, And The Dollar: A Panel Cointegration And Causality Analysis. Energy Economics, 34 (4), 1098-1104.
  • Nkoro, E. & Uko, A. K. (2016). Autoregressive Distributed Lag (ARDL) Cointegration Technique: Application And Interpretation, Journal of Statistical and Econometric Methods, 5 (4), 63-91.
  • Pesaran, M. H., Shin, Y. & Smith, R. J. (2001). Bounds Testing Approaches To The Analysis Of Level Relationships. Journal Of APPLIED ECONOMETRICS, 16 (3), 289-326.
  • Reboredo, J. C. (2012). Do Food And Oil Prices Co-Move?. Energy Policy, 49, 456-467.
  • Roman, M., Gorecka, A. & Domagala, J. (2020). The Linkages between Crude Oil and Food Prices. Energies, 13 (24), 1-18.
  • Serra, T., Zilberman, D. Gil, J. M. & Goodwin, B. K. (2011). Nonlinearities In The U.S. Corn-Ethanol-Oil-Gasoline Price System. Agricultural Economics, 42 (1), 35-45.
  • Tiwari, A. K., Khalfaoui, R., Solarin, S. A. & Shahbaz, M. (2018). Analyzing The Time-Frequency Lead–Lag Relationship Between Oil And Agricultural Commodities. Energy Economics, 76, 470-494.
  • Tursoy, T. & Faisal, F. (2018). The İmpact Of Gold And Crude Oil Prices On Stock Market In Turkey: Empirical Evidences From ARDL Bounds Test And Combined Cointegration. Resources Policy, 55, 49-54.
  • Wang, Y., Wu, C. & Yang, L. (2014). Oil Price Shocks And Agricultural Commodity Prices. Energy Economics, 44 (C), 22-35.
  • Zafeiriou, E., Arabatzis, G., Karanikola, P., Tampakis, S. & Tsiantikoudis, S. (2018). Agricultural Commodities and Crude Oil Prices: An Empirical Investigation of Their Relationship. Sustainability, 10 (4), 1-11.
  • Zhang, Z., Lohr, L., Escalante, C. & Wetzstein, M. (2010). Food Versus Fuel: What Do Prices Tell Us?. Energy Policy, 38 (1), 445-451.

Enerji ve Tarım Emtiaları Arasındaki İlişkinin ARDL Modeli İle Belirlenmesi

Year 2022, Volume: 24 Issue: 2, 147 - 160, 30.12.2022

Abstract

Enerji ve tarım emtiaları fiyatlarında yaşanan günlük hareketlilik, yatırımcıları bu piyasalarda işlem yapmaya iten en önemli faktörlerden biridir. Portföy oluştururken enerji ve tarımsal emtialara yönelik yatırımda bulunanlar açısından bu emtialar arasındaki ilişkinin doğru şekilde tespit edilmesi gerekmektedir. Eğer alınan pozisyon aslında yanlışsa beklenmedik bir zararla karşılaşılması kaçınılmazdır. Bu yüzden hem uzun dönemli hem de kısa dönemli aralarında oluşan ilişkinin bilinerek pozisyon alınması, yatırımcıların getirilerini artırabilmelerine ya da en az kayıpla pozisyon kapatmalarına destek olabilecektir.
Bu çalışma enerji ve tarım emtiaları arasındaki uzun dönemli ilişkinin tespit edilebilmesi amacıyla yapılmıştır. Enerji emtiaları olarak WTI petrol, motorin ve doğalgaz, tarım emtiaları olarak buğday, kakao ve pamuk seçilmiş ve ARDL modeli ile analizler yapılmıştır. Analiz sonucunda bağımlı değişken olarak alınan WTI petrol ile bağımsız değişken olarak alınan diğer emtialar arasında uzun dönemli ilişki olduğu tespit edilmiştir. Bu sonuç uzun dönemde enerji ve tarım emtialarının birlikte hareket ettiğini ve bunlara dayalı portföy oluştururken dikkatli davranılması gerekliliğini ifade etmektedir.

References

  • Baffes, & Dennis (2015). Long-Term Drivers of Food Prices. Trade Policy and Food Security Improving Access to Food in Developing Countries in the Wake of High World Prices (Ian Gillson & Amir Fouad, ed.), World Bank Group, 13-36.
  • Byrne, J. P., Fazio, G. & Fiess, N. (2013). Primary Commodity Prices: Co-Movements, Common Factors And Fundamentals. Journal of Development Economics, 101, 16-26.
  • Chen, S-T., Kuo, H-I. & Chen, C-C (2010). Modeling The Relationship Between The Oil Price And Global Food Prices. Applied Energy, 87 (8), 2517-2525.
  • Coronado, S., Rojas, O. Romero-Meza, R. Serletis, A. & Chiu, L. V. (2018). Crude Oil and Biofuel Agricultural Commodity Prices. Uncertainty, Expectations and Asset Price Dynamics (Fredj Jawadi ed.), 107-123.
  • De Nicola, F., De Pace, P. & Hernandez, M. A. (2016). Co-Movement Of Major Energy, Agricultural, And Food Commodity Price Returns: A Time-Series Assessment, Energy Economics, 57 (C), 28-41.
  • Du, X., Yu, C. L. & Hayes, D. J. (2011). Speculation And Volatility Spillover In The Crude Oil And Agricultural Commodity Markets: A Bayesian Analysis. Energy Economics, 33 (3), 497-503.
  • Engle, R. F. & Granger, W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55 (2), 251-276.
  • Fowowe, B. (2016). Do Oil Prices Drive Agricultural Commodity Prices? Evidence From South Africa. Energy, 104, 149-157.
  • Gülerce, M. & Ünal, G. (2017). Forecasting Of Oil And Agricultural Commodity Prices: Varma Versus Arma. Annals of Financial Economics, 12 (3), 1-30.
  • Ibrahim, M. H. (2015). Oil And Food Prices In Malaysia: A Nonlinear ARDL Analysis. Ibrahim Agricultural and Food Economics, 3 (1), 1-14.
  • Jadidzadeh, A. & Serletis, A. (2018). The Global Crude Oil Market And Biofuel Agricultural Commodity Prices. The Journal of Economic Asymmetries, 18, 1-9.
  • Johansen, S. & Juselius, K. (1990). Maximum Likelihood Estimation And Inference On Cointegration —With Applications To The Demand For Money. OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 52 (2), 169-210.
  • Karakotsios, A., Katrakilidis, C. & Kroupis, N. (2021). The Dynamic Linkages Between Food Prices And Oil Prices. Does Asymmetry Matter?. The Journal of Economic Asymmetries, 23, 1-10.
  • Kumar, S., Choudhary, S., Singh, G. & Singha, S. (2021). Crude Oil, Gold, Natural Gas, Exchange Rate And Indian Stock Market: Evidence From The Asymmetric Nonlinear ARDL Model. Resources Policy, 73, 1-7.
  • Lucotte, Y. (2016). Co-movements Between Crude Oil And Food Prices: A Post-Commodity Boom Perspective. Economics Letters, 147, 142-147.
  • Nazlıoğlu, Ş. (2011). World Oil And Agricultural Commodity Prices: Evidence From Nonlinear Causality. Energy Policy, 39 (5), 2935-2943.
  • Nazlıoğlu, Ş. & Soytaş, U. (2012). Oil Price, Agricultural Commodity Prices, And The Dollar: A Panel Cointegration And Causality Analysis. Energy Economics, 34 (4), 1098-1104.
  • Nkoro, E. & Uko, A. K. (2016). Autoregressive Distributed Lag (ARDL) Cointegration Technique: Application And Interpretation, Journal of Statistical and Econometric Methods, 5 (4), 63-91.
  • Pesaran, M. H., Shin, Y. & Smith, R. J. (2001). Bounds Testing Approaches To The Analysis Of Level Relationships. Journal Of APPLIED ECONOMETRICS, 16 (3), 289-326.
  • Reboredo, J. C. (2012). Do Food And Oil Prices Co-Move?. Energy Policy, 49, 456-467.
  • Roman, M., Gorecka, A. & Domagala, J. (2020). The Linkages between Crude Oil and Food Prices. Energies, 13 (24), 1-18.
  • Serra, T., Zilberman, D. Gil, J. M. & Goodwin, B. K. (2011). Nonlinearities In The U.S. Corn-Ethanol-Oil-Gasoline Price System. Agricultural Economics, 42 (1), 35-45.
  • Tiwari, A. K., Khalfaoui, R., Solarin, S. A. & Shahbaz, M. (2018). Analyzing The Time-Frequency Lead–Lag Relationship Between Oil And Agricultural Commodities. Energy Economics, 76, 470-494.
  • Tursoy, T. & Faisal, F. (2018). The İmpact Of Gold And Crude Oil Prices On Stock Market In Turkey: Empirical Evidences From ARDL Bounds Test And Combined Cointegration. Resources Policy, 55, 49-54.
  • Wang, Y., Wu, C. & Yang, L. (2014). Oil Price Shocks And Agricultural Commodity Prices. Energy Economics, 44 (C), 22-35.
  • Zafeiriou, E., Arabatzis, G., Karanikola, P., Tampakis, S. & Tsiantikoudis, S. (2018). Agricultural Commodities and Crude Oil Prices: An Empirical Investigation of Their Relationship. Sustainability, 10 (4), 1-11.
  • Zhang, Z., Lohr, L., Escalante, C. & Wetzstein, M. (2010). Food Versus Fuel: What Do Prices Tell Us?. Energy Policy, 38 (1), 445-451.
There are 27 citations in total.

Details

Primary Language Turkish
Journal Section Issue
Authors

Hidayet Güneş 0000-0002-9826-9862

Publication Date December 30, 2022
Submission Date April 13, 2022
Published in Issue Year 2022 Volume: 24 Issue: 2

Cite

APA Güneş, H. (2022). Enerji ve Tarım Emtiaları Arasındaki İlişkinin ARDL Modeli İle Belirlenmesi. Kastamonu Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 24(2), 147-160. https://doi.org/10.21180/iibfdkastamonu.1103192