Investigating Nonlinear Speculation in Cattle, Corn and Hog Futures Markets Using Logistic Smooth Transition Regression Models
AbstractThis 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.
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Bibliographic InfoPaper provided by Quantitative Finance Research Centre, University of Technology, Sydney in its series Research Paper Series with number 172.
Date of creation: 01 Feb 2006
Date of revision:
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futures marktes; speculation; nonlinear dynamics; smooth transition regression model;
Other versions of this item:
- Röthig, Andreas & Chiarella, Carl, 2006. "Investigating nonlinear speculation in cattle, corn, and hog futures markets using logistic smooth transition regression models," Darmstadt Discussion Papers in Economics 36774, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute of Economics (VWL).
- 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 &bull Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-AGR-2006-03-11 (Agricultural Economics)
- NEP-ALL-2006-03-11 (All new papers)
- NEP-FIN-2006-03-11 (Finance)
- NEP-FMK-2006-03-11 (Financial Markets)
- NEP-RMG-2006-03-11 (Risk Management)
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