Component structures of agricultural commodity futures traded on the Tokyo Grain Exchange
- 94 Downloads
In this paper, we propose a discrete version of the short-term and long-term component model of the agricultural futures prices. The maximum likelihood estimate of each parameter is obtained using an adaptive filtering algorithm. The diagnostics statistically support the specification of the model. The short-term components exhibit no causal relationship with economic fundamentals such as inflation rate and economic growth rate. These components, therefore, seem to be driven mainly by fads rather than market fundamentals. On the other hand, the long-term components show conitegrating relationship with only one cointegrating vector among the three futures contracts examined.
KeywordsAgricultural futures Kalman filter Fads
JEL classification numberG12
Unable to display preview. Download preview PDF.
- Bhar, R., & Hamori, S. (2005). Empirical techniques in finance. Heidelberg: SpringerGoogle Scholar
- Blanchard, O., & Watson, M. (1982). Bubbles, rational expectations and financial markets. In Wachtel P. (Ed.), Crises in the economic and financial structure. Lexington, Mass: Lexington BooksGoogle Scholar
- Booth, G. G., Brockman, P., & Tse, Y. (1998). The relationship between US and Canadian wheat futures. Applied Economics Letters, 8, 73–80Google Scholar
- Harvey, A. C. (1990). The econometric analysis of time series (2nd ed.). Cambridge, Massachusetts: The MIT PressGoogle Scholar
- Reinhart, C., & Wickham, P. (1994). Commodity prices: cyclical weakness or secular decline? IMF Staff Papers, 41, 175–213Google Scholar
- Stevens, S. C. (1991). Evidence for a weather persistence effect on the corn, wheat, and soybean growing season price dynamics. Journal of Futures Markets, 11, 81–88Google Scholar