RESEARCH ON NON-RANDOM ELEMENTS OF THE COMMODITY FUTURES MARKETS

The research questions of this study were: (1) Can non-randomness
be identified in the movement of commodity futures prices which would indicate
that the random walk theory is not fully applicable? (2) What model or models demonstrate this non-randomness? and (3) Are characteristics
of non-randomness uniformly present in different commodity types?
A data base of commodity futures price history was assembled
covering wheat, corn, oats, and soybeans. Considering the four commodity
types and the various delivery months for each commodity, a total of 215
years of price history was available. The historical data was used to test two methods of technical
analysis: (1) a moving average model and (2) a seasonal model. The models
simulate on a digital computer various decision rules in trading commodity
futures using the price history data as input. The models were evaluated
by comparing the resulting net profits from trading against the net profit
from a simple buy-and-hold policy.
Moving average and seasonal strategies were found which would
produce more profitable results than the buy-and-hold strategy. The moving
average model produced best results with wheat and corn. Oats showed the
poorest results and soybeans was in an intermediate position. Oats,
however, was the only commodity of the four tested which exhibited consistently better results using the seasonal model compared to the moving
average model.
Recommendations were made on areas of possible further study based
on the research results.