IDEAS home Printed from https://ideas.repec.org/p/uts/rpaper/172.html
   My bibliography  Save this paper

Investigating Nonlinear Speculation in Cattle, Corn and Hog Futures Markets Using Logistic Smooth Transition Regression Models

Author

Listed:

Abstract

This article explores nonlinearities in the response of speculators’ trading activity to price changes in live cattle, corn, and lean hog futures markets. Analyzing weekly data from March 4, 1997 to December 27, 2005, we reject linearity in all of these markets. Using smooth transition regression models, we find a similar structure of nonlinearities with regard to the number of different regimes, the choice of the transition variable, and the value at which the transition occurs.

Suggested Citation

  • Andreas Röthig & Carl Chiarella, 2006. "Investigating Nonlinear Speculation in Cattle, Corn and Hog Futures Markets Using Logistic Smooth Transition Regression Models," Research Paper Series 172, Quantitative Finance Research Centre, University of Technology, Sydney.
  • Handle: RePEc:uts:rpaper:172
    as

    Download full text from publisher

    File URL: https://www.uts.edu.au/sites/default/files/qfr-archive-02/QFR-rp172.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    2. Changyun Wang, 2003. "The behavior and performance of major types of futures traders," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(1), pages 1-31, January.
    3. Skalin, Joakim & Terasvirta, Timo, 1999. "Another Look at Swedish Business Cycles, 1861-1988," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(4), pages 359-378, July-Aug..
    4. Dijk, Dick van & Franses, Philip Hans, 1999. "Modeling Multiple Regimes in the Business Cycle," Macroeconomic Dynamics, Cambridge University Press, vol. 3(03), pages 311-340, September.
    5. Pablo Mejia-Reyes & Denise Osborn & Marianne Sensier, 2010. "Modelling real exchange rate effects on output performance in Latin America," Applied Economics, Taylor & Francis Journals, vol. 42(19), pages 2491-2503.
    6. Hall, Anthony D. & Skalin, Joakim & Teräsvirta, Timo, 1998. "A nonlinear time series model of El Niño," SSE/EFI Working Paper Series in Economics and Finance 263, Stockholm School of Economics.
    7. Sarno, Lucio, 1999. "Adjustment Costs and Nonlinear Dynamics in the Demand for Money: Italy, 1861-1991," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 4(2), pages 155-177, April.
    8. Qingfeng “Wilson” Liu, 2005. "Price relations among hog, corn, and soybean meal futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 25(5), pages 491-514, May.
    9. Lutkepohl, Helmut & Terasvirta, Timo & Wolters, Jurgen, 1999. "Investigating Stability and Linearity of a German M1 Money Demand Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 511-525, Sept.-Oct.
    10. John R. Nofsinger & Richard W. Sias, 1999. "Herding and Feedback Trading by Institutional and Individual Investors," Journal of Finance, American Finance Association, vol. 54(6), pages 2263-2295, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Adam Clements & Neda Todorova, 2014. "The impact of information flow and trading activity on gold and oil futures volatility," NCER Working Paper Series 102, National Centre for Econometric Research.
    2. Yu-Lun Chen & Yin-Feng Gau & Wen-Ju Liao, 2016. "Trading activities and price discovery in foreign currency futures markets," Review of Quantitative Finance and Accounting, Springer, vol. 46(4), pages 793-818, May.
    3. Melike Bildirici & Özgür Ömer Ersin, 2014. "Nonlinearity, Volatility and Fractional Integration in Daily Oil Prices: Smooth Transition Autoregressive ST-FI(AP)GARCH Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 108-135, October.
    4. Wang, Yudong & Liu, Li & Diao, Xundi & Wu, Chongfeng, 2015. "Forecasting the real prices of crude oil under economic and statistical constraints," Energy Economics, Elsevier, vol. 51(C), pages 599-608.
    5. Andreas Röthig, 2011. "On speculators and hedgers in currency futures markets: who leads whom?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 16(1), pages 63-69, January.
    6. Georg Lehecka, 2015. "Do hedging and speculative pressures drive commodity prices, or the other way round?," Empirical Economics, Springer, vol. 49(2), pages 575-603, September.
    7. Chang, Ya-Kai & Chen, Yu-Lun & Chou, Robin K. & Gau, Yin-Feng, 2013. "The effectiveness of position limits: Evidence from the foreign exchange futures markets," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4501-4509.
    8. Liu, Li & Wang, Yudong & Wu, Chongfeng & Wu, Wenfeng, 2016. "Disentangling the determinants of real oil prices," Energy Economics, Elsevier, vol. 56(C), pages 363-373.
    9. Sigl-Grüb, C. & Schiereck, D., 2010. "Speculation and Nonlinear Price Dynamics in Commodity Futures Markets," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56603, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    10. Mingue SUn, "undated". "A Branch-and-Bound Algorithm for Representative Integer Efficient Solutions in Multiple Objective Network Programming Problems," Working Papers 0007, College of Business, University of Texas at San Antonio.
    11. Yuanlong Ge & Holly H. Wang & Sung K. Ahn, 2010. "Cotton market integration and the impact of China's new exchange rate regime," Agricultural Economics, International Association of Agricultural Economists, vol. 41(5), pages 443-451, September.
    12. Röthig, Andreas, 2008. "The impact of backwardation on hedgers' demand for currency futures contracts: theory versus empirical evidence," Darmstadt Discussion Papers in Economics 190, Darmstadt University of Technology, Department of Law and Economics.
    13. Mutafoglu, Takvor H. & Tokat, Ekin & Tokat, Hakki A., 2012. "Forecasting precious metal price movements using trader positions," Resources Policy, Elsevier, vol. 37(3), pages 273-280.
    14. Yiuman Tse & Michael R. Williams, 2013. "Does Index Speculation Impact Commodity Prices? An Intraday Analysis," The Financial Review, Eastern Finance Association, vol. 48(3), pages 365-383, August.
    15. Sanders, Dwight R. & Irwin, Scott H. & Merrin, Robert P., 2009. "Smart Money: The Forecasting Ability of CFTC Large Traders in Agricultural Futures Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(2), August.
    16. Andreas Röthig, 2012. "Cross‐Speculation In Currency Futures Markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 17(3), pages 272-278, July.

    More about this item

    Keywords

    futures marktes; speculation; nonlinear dynamics; smooth transition regression model;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:uts:rpaper:172. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Duncan Ford). General contact details of provider: http://edirc.repec.org/data/qfutsau.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.