Asset risk and return are not enough for investors in collections of assets. Portfolio performance includes the extent of correlation or independence, the diversification, of the collected components.
The table below shows the correlations of the continuously compounded daily returns among the fifteen commodities in the VistaCTA basket for the three year period January 1, 2010 to December 31, 2012. Correlation coefficients may range from 0.00 (red) to 1.00 (blue) with 0.00 interpreted as “independent” or no correlation and 1.00 interpreted as 100% correlation or prices moving in lockstep. The correlation of a commodity to itself, of course, is 1.00. The correlation coefficient may be more meaningful over the long-term and that's why I selected a standard three year period. Low correlations, below .50, are shown in red. High correlations are in blue.
For example, the correlation coefficient of continuously compounded daily returns from Jan 1, 2010 to Dec 31, 2012 for coffee to copper is a low 0.28 indicating they have significantly different risks and returns. Copper and coffee are in totally different industries and would be expected to have little relation to each other as evidenced by their low correlation. Commodities within the same industry are usually expected to have high correlations.
VistaCTA Component Correlations 2010 - 2012
Commodity sectors are shown in each box. The energy sector, as expected, shows high internal correlation. Heating oil and gasoline have a .91 correlation coefficient to crude oil and .95 to each other. Notably, natural gas trades in its own world with very low correlation in the teens to the other energies.
Crude | 1.00 | ||||||||||||||
HeatOil | 0.91 | 1.00 | |||||||||||||
NatGas | 0.15 | 0.15 | 1.00 | ||||||||||||
Gasoline | 0.91 | 0.95 | 0.14 | 1.00 | |||||||||||
Gold | 0.29 | 0.27 | 0.14 | 0.29 | 1.00 | ||||||||||
Silver | 0.29 | 0.28 | 0.12 | 0.28 | 0.73 | 1.00 | |||||||||
Copper | 0.38 | 0.37 | 0.10 | 0.35 | 0.66 | 0.63 | 1.00 | ||||||||
Corn | 0.35 | 0.34 | 0.04 | 0.34 | 0.18 | 0.19 | 0.25 | 1.00 | |||||||
Wheat | 0.47 | 0.44 | 0.08 | 0.45 | 0.20 | 0.21 | 0.30 | 0.77 | 1.00 | ||||||
Soybeans | 0.52 | 0.46 | 0.05 | 0.46 | 0.25 | 0.25 | 0.35 | 0.40 | 0.50 | 1.00 | |||||
Coffee | 0.30 | 0.27 | 0.10 | 0.27 | 0.26 | 0.24 | 0.28 | 0.22 | 0.28 | 0.31 | 1.00 | ||||
Sugar | 0.26 | 0.24 | 0.09 | 0.24 | 0.32 | 0.25 | 0.31 | 0.12 | 0.17 | 0.26 | 0.29 | 1.00 | |||
Cocoa | 0.30 | 0.28 | 0.11 | 0.26 | 0.14 | 0.15 | 0.22 | 0.17 | 0.22 | 0.27 | 0.24 | 0.13 | 1.00 | ||
Cotton | 0.27 | 0.26 | 0.00 | 0.25 | 0.29 | 0.29 | 0.33 | 0.16 | 0.22 | 0.23 | 0.19 | 0.24 | 0.18 | 1.00 | |
OJ | 0.16 | 0.13 | 0.05 | 0.13 | 0.09 | 0.09 | 0.17 | 0.07 | 0.13 | 0.11 | 0.05 | 0.07 | 0.07 | 0.07 | 1.00 |
Crude | HeatOil | NatGas | Gasoline | Gold | Silver | Copper | Corn | Wheat | Soybeans | Coffee | Sugar | Cocoa | Cotton | OJ |
Commodity sectors are shown in each box. The energy sector, as expected, shows high internal correlation. Heating oil and gasoline have a .91 correlation coefficient to crude oil and .95 to each other. Notably, natural gas trades in its own world with very low correlation in the teens to the other energies.
Metals, surprisingly, have lower correlation over this period. Gold to silver is .73, and seems lower than expected. Copper, an industrial metal, is .66. The grains and soybeans also have lower than expected correlations. Wheat and corn do trade together (.77), adding soybeans to the mix reduces the coefficient to .50 and below. The softs may be misnamed as a sector evidenced by their low intermarket correlations, all red.
The two most non-correlated commodities in the VistaCTA basket are natural gas and frozen concentrated orange juice with multiple very low single digit correlations to the other commodities in the Vista basket.
Overall we see a picture with lots of low correlations contributing to the high diversification effects of owning a commodity basket. The reduced risk of the VistaCTA basket may be a strong reason for investors to own commodity baskets versus taking their chances picking and choosing winners and losers in the market.