Featured Post

How to Invest

  How to Invest An investment guide for everyone.   Investments are a form of spending but spending on SAVINGS. Savings for yourself, ...

Tuesday, February 26, 2013

Commodity Correlations


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

 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. 


Saturday, February 23, 2013

2012 Commodity Risk Versus Reward

A standard method to evaluate asset performance is to plot the return of an investment against its standard deviation.  This is commonly called the risk-reward chart. While used for stocks the risk-reward chart below is shown for the fifteen commodities included in the Vista CTA basket. 

On the face of it, 2012 was a poor year for commodities. VistaCTA's benchmark, the Dow Jones-UBS Commodity Total Return Index, was down -1.05% in 2012.  The VistaCTA basket rose +1.48%.
 
Risk-Reward Chart
 
The vertical axis shows the continuously compounded price return of the commodities in the VistaCTA basket. The horizontal axis shows the standard deviation of daily returns for the 2012 calendar year.  The VistaCTA data point is shown in red.  For comparison purposes, the S&P 500 data point is in black.
 
Year 2012 Commodity Risk-Reward Chart
 

 The chart data set is shown below.
 
 
While a down year for commodities, 2012 highlighted the diversification value of holding a well constructed basket. The basket +1.47% annual return was 366 basis points higher than the average -2.19% return of the 15 basket components. At 0.009, the basket standard deviation of 2012 daily returns was the lowest of all the basket components and 1.49 below the 1.58 component average.  The Vista basket, while only slightly higher on the year, had risk comparable to that of the S&P 500 which had a banner recovery year.


Even in 2012, the VistaCTA basket added value for commodity investors with significantly improved risk while showing a small gain in a generally down year.