IDEAS home Printed from https://ideas.repec.org/p/qld/uq2004/334.html
   My bibliography  Save this paper

Interactions of Source State and Market Price Trends for Cattle of Korean, Japanese and USA Market Specifications

Author

Abstract

This study analyses the trends in the real prices of steers destined for the Japanese and Korean market, and cows destined for the USA market when sold in Queensland (QLD) or New South Wales (NSW). The aim of this paper is to explore how these prices have influenced each other when faced with the same overall economic and climatic conditions. A Vector Autoregressive model is first estimated to find linkages across six price series defined by source and destination. A Seemingly Unrelated Regressions Model for the real price series is then estimated including lagged prices of linked markets and indicators of macroeconomic and climatic conditions. From our empirical analysis, we find strong evidence of mean-reverting real prices, indicating they can be predicted by their historical mean. Further, the historical mean prices paid in QLD are higher than those paid in NSW for the Korean and US market cattle specifications. The price of cattle of Japanese market specification sold in NSW is solely determined by world conditions and historical values, and it influences directly or indirectly all other markets. The price trends for cattle of US market specifications do not seem to predict movements in the Japanese or Korean markets. This is expected as the Japanese market is a premium market while the US market accepts cattle from a wider range of specifications. This study does not find a systematic relationship between these prices and movements, the Southern Oscillation Index, the Asian financial crises, or the Australian Business Cycle.

Suggested Citation

  • Dr Alicia Rambaldi & Bortolussi, 2004. "Interactions of Source State and Market Price Trends for Cattle of Korean, Japanese and USA Market Specifications," Discussion Papers Series 334, School of Economics, University of Queensland, Australia.
    • Handle: RePEc:qld:uq2004:334
    as

    Download full text from publisher

    File URL: https://economics.uq.edu.au//files/44372/334.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Layton, Allan P, 1997. "Do Leading Indicators Really Predict Australian Business Cycle Turning Points?," The Economic Record, The Economic Society of Australia, vol. 73(222), pages 258-269, September.
    2. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    3. 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.
    4. Rosen, Sherwin & Murphy, Kevin M & Scheinkman, Jose A, 1994. "Cattle Cycles," Journal of Political Economy, University of Chicago Press, vol. 102(3), pages 468-492, June.
    5. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    6. Philip M. Bodman & Mark Crosby, 2002. "The Australian Business Cycle: Joe Palooka or Dead Cat Bounce?," Australian Economic Papers, Wiley Blackwell, vol. 41(2), pages 191-207, June.
    7. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    8. Allan P. Layton, 1997. "Do Leading Indicators Really Predict Australian Business Cycle Turning Points?," The Economic Record, The Economic Society of Australia, vol. 73(222), pages 258-269, September.
    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. Postali, Fernando A.S. & Picchetti, Paulo, 2006. "Geometric Brownian Motion and structural breaks in oil prices: A quantitative analysis," Energy Economics, Elsevier, vol. 28(4), pages 506-522, July.
    2. Prilly Oktoviany & Robert Knobloch & Ralf Korn, 2021. "A machine learning-based price state prediction model for agricultural commodities using external factors," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1063-1085, December.
    3. Guedes, José & Santos, Pedro, 2016. "Valuing an offshore oil exploration and production project through real options analysis," Energy Economics, Elsevier, vol. 60(C), pages 377-386.
    4. Jilong Chen & Christian Ewald & Ruolan Ouyang & Sjur Westgaard & Xiaoxia Xiao, 2022. "Pricing commodity futures and determining risk premia in a three factor model with stochastic volatility: the case of Brent crude oil," Annals of Operations Research, Springer, vol. 313(1), pages 29-46, June.
    5. Fiuza de Bragança, Gabriel Godofredo & Daglish, Toby, 2016. "Can market power in the electricity spot market translate into market power in the hedge market?," Energy Economics, Elsevier, vol. 58(C), pages 11-26.
    6. Bai, Yizhou & Xue, Cheng, 2021. "An empirical study on the regulated Chinese agricultural commodity futures market based on skew Ornstein-Uhlenbeck model," Research in International Business and Finance, Elsevier, vol. 57(C).
    7. Moreno, Manuel & Novales, Alfonso & Platania, Federico, 2019. "Long-term swings and seasonality in energy markets," European Journal of Operational Research, Elsevier, vol. 279(3), pages 1011-1023.
    8. Nguyen, Duc Binh Benno & Prokopczuk, Marcel, 2019. "Jumps in commodity markets," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 55-70.
    9. Ames, Matthew & Bagnarosa, Guillaume & Matsui, Tomoko & Peters, Gareth W. & Shevchenko, Pavel V., 2020. "Which risk factors drive oil futures price curves?," Energy Economics, Elsevier, vol. 87(C).
    10. Marcelo G. Figueroa, 2006. "Pricing Multiple Interruptible-Swing Contracts," Birkbeck Working Papers in Economics and Finance 0606, Birkbeck, Department of Economics, Mathematics & Statistics.
    11. Abdullah Almansour and Margaret Insley, 2016. "The Impact of Stochastic Extraction Cost on the Value of an Exhaustible Resource: An Application to the Alberta Oil Sands," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    12. Chen, Shan & Insley, Margaret, 2012. "Regime switching in stochastic models of commodity prices: An application to an optimal tree harvesting problem," Journal of Economic Dynamics and Control, Elsevier, vol. 36(2), pages 201-219.
    13. Back, Janis & Prokopczuk, Marcel & Rudolf, Markus, 2013. "Seasonality and the valuation of commodity options," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 273-290.
    14. Björn Lutz, 2010. "Pricing of Derivatives on Mean-Reverting Assets," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-02909-7, October.
    15. Julien Chevallier & Benoît Sévi, 2014. "On the Stochastic Properties of Carbon Futures Prices," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 58(1), pages 127-153, May.
    16. Alvaro Cartea & Marcelo Figueroa, 2005. "Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(4), pages 313-335.
    17. Luis M. Abadie & José M. Chamorro, 2009. "Monte Carlo valuation of natural gas investments," Review of Financial Economics, John Wiley & Sons, vol. 18(1), pages 10-22, January.
    18. Issler, João Victor & Notini, Hilton Hostalácio & Rodrigues, Claudia Oliveira da Fontoura, 2009. "Um indicador coincidente e antecedente da atividade econômica brasileira," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 695, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    19. Villaplana Conde, Pablo, 2003. "Pricing power derivatives: a two-factor jump-diffusion approach," DEE - Working Papers. Business Economics. WB wb031805, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    20. Aur'elien Alfonsi & Nerea Vadillo, 2023. "Risk valuation of quanto derivatives on temperature and electricity," Papers 2310.07692, arXiv.org.

    More about this item

    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:qld:uq2004:334. 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: SOE IT (email available below). General contact details of provider: https://edirc.repec.org/data/decuqau.html .

    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.