Invesco DB Commodity Index Tracking Fund x Commodity Correlations
Historical price and correlation data
Seasonality
This multi-factor forecast for Paypal Holdings (PYPL) is based on a weighted average of five factor-dervied forecasts.
Backtest PYPLLeft-hand side y-axis coordinates represent the 1 to 180-day look back periods for Pearson correlation values.
Right-hand side y=axis coordinates measure the price level of DBC.
Commodity Pearson Correlations
| Correlation Interval |
Previous Year |
Previous Month |
Last Value |
| 20-day |
0.27827 |
0.16728 |
0.37393 |
| 40-day |
0.24867 |
0.31853 |
0.21634 |
| 60-day |
0.18151 |
0.26273 |
0.27614 |
| 80-day |
0.21582 |
0.26286 |
0.24906 |
| 100-day |
0.22858 |
0.26722 |
0.25743 |
| 120-day |
0.22349 |
0.24876 |
0.24154 |
| 140-day |
0.25731 |
0.24066 |
0.23975 |
| 160-day |
0.30102 |
0.24326 |
0.23219 |
| 180-day |
0.30774 |
0.23136 |
0.23523 |
| Correlation Interval |
Last Value |
| 20-day |
0.37393 |
| 40-day |
0.21634 |
| 60-day |
0.27614 |
| 80-day |
0.24906 |
| 100-day |
0.25743 |
| 120-day |
0.24154 |
| 140-day |
0.23975 |
| 160-day |
0.23219 |
| 180-day |
0.23523 |
About Heat Map Colors
This average correlation heat map uses a color scheme to represent how strongly the DBA, DBE, DBP and DBB components exhibit a positive (red), somewhat positive (white), or low / inverse average correlation (green). Different shades of these three colors represent the strength or weakness of the average correlation as shown on the heatmap colorbar legend, to the right of the heatmap itself.
The X-axis displays trading days by date, and the Y-axis contains different n-day average correlation look back periods. For example, The 180-day average of Pearson correlation value calculated on a specific date appears on the heat map at the intersection of Y-coordinate "180" and X-coordinate of the specific date.
A price chart of Invesco DB Commodity Index Tracking Fund is overlaid on top of the heat map so you can observe the impact that different average correlation regimes may be having on the price of the asset.
As a general observation, high correlation regimes are accompanied by high volatility in price movements, and vice-versa.
Note that traders who need a perform a more comprehensive analysis can
backtest the impact of each of these n-day average correlations using the
Tradewell platform.
The
Pearson correlation coefficient is a measure of linear strength between two sets of data. In financial markets is used to determine whether the variability of returns between a group of assets is linearly related.
In the example of this heat map analysis of Invesco DB Commodity Index Tracking Fund, we are measuring the average correlations between the components over various look-back periods, spanning 10 days to 180 days.
In the example of this
heat map analysis of Invesco DB Commodity Index Tracking Fund, we are measuring the average correlations between the components over various look-back periods, spanning 10 days to 180 days.
A coefficient value of -1 represents a maximally inverse relationship between the variables, whereas a value of 1 represents a maximally positive relationship. A value of 0 indicates no linear relationship between the variables.
For example, a 20-day average correlation value of 1 would indicate that variability of the index components returns has been perfectly linearly related over the previous 20 days.
DBC seeks to track changes in the level of DBIQ Optimum Yield's Commodity Index. The fund's portfolio includes: exchange-traded futures on Light Sweet Crude Oil (WTI), Heating Oil, RBOB Gasoline Natural Gas Brent Crude Oil; Gold , Silver, Aluminum, Zinc, Copper (Grade A), Corn, Wheat, Soybeans and Sugar.
