The below analysis compares continuous front month future settlement prices of various grain -> energy and metal commodities. The following steps take place for each:
1. graph each product on a standardized basis for comparison.
2. conducting a correlation test using pearson correlation coefficient.
3. Calculate the point-estimate probability that both markets will concurrently close above and below their respective 5-day rolling average on the same trading day.

FRONT MONTH SOYBEANS VS. COPPER

## 
##  Pearson's product-moment correlation
## 
## data:  plotss$P1norm and plotss$P2norm
## t = 167.53, df = 14245, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.8088509 0.8199095
## sample estimates:
##       cor 
## 0.8144541

Copper and Soybeans concurrently settle above their respective 5-day rolling averages 0.569 of the time, and concurrently below their respective 5-day averages 0.483 of the time

FRONT MONTH SOYBEANS VS. CRUDE OIL

## 
##  Pearson's product-moment correlation
## 
## data:  plotss$P1norm and plotss$P2norm
## t = 136.86, df = 8338, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.8251103 0.8383370
## sample estimates:
##       cor 
## 0.8318417

S and CL concurrently settle above their respective 5-day rolling averages 0.568 of the time, and concurrently below their respective 5-day averages 0.474 of the time

FRONT MONTH SOYBEANS VS. RBOB

## 
##  Pearson's product-moment correlation
## 
## data:  plotss$P1norm and plotss$P2norm
## t = 58.442, df = 2685, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.7311168 0.7644294
## sample estimates:
##       cor 
## 0.7482444

S and RB concurrently settle above their respective 5-day rolling averages 0.595 of the time, and concurrently below their respective 5-day averages 0.477 of the time

FRONT MONTH SOYBEANS VS. ETHANOL

## 
##  Pearson's product-moment correlation
## 
## data:  plotss$P1norm and plotss$P2norm
## t = 53.809, df = 1181, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.8254373 0.8585385
## sample estimates:
##       cor 
## 0.8427829

S and EH concurrently settle above their respective 5-day rolling averages 0.638 of the time, and concurrently below their respective 5-day averages 0.541 of the time

FRONT MONTH SOYBEANS VS. NG

## 
##  Pearson's product-moment correlation
## 
## data:  plotss$P1norm and plotss$P2norm
## t = 14.292, df = 6562, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.1501920 0.1971168
## sample estimates:
##      cor 
## 0.173753

S and NG concurrently settle above their respective 5-day rolling averages 0.522 of the time, and concurrently below their respective 5-day averages 0.499 of the time

FRONT MONTH CORN VS. COPPER

## 
##  Pearson's product-moment correlation
## 
## data:  plotss$P1norm and plotss$P2norm
## t = 163.9, df = 14247, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.8025919 0.8139745
## sample estimates:
##       cor 
## 0.8083588

C and HG concurrently settle above their respective 5-day rolling averages 0.556 of the time, and concurrently below their respective 5-day averages 0.51 of the time

FRONT MONTH CORN VS. CRUDE OIL

## 
##  Pearson's product-moment correlation
## 
## data:  plotss$P1norm and plotss$P2norm
## t = 113.94, df = 8331, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.7719287 0.7887187
## sample estimates:
##       cor 
## 0.7804644

C and CL concurrently settle above their respective 5-day rolling averages 0.561 of the time, and concurrently below their respective 5-day averages 0.504 of the time

FRONT MONTH CORN VS. RBOB

## 
##  Pearson's product-moment correlation
## 
## data:  plotss$P1norm and plotss$P2norm
## t = 52.192, df = 2685, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.6903660 0.7279338
## sample estimates:
##      cor 
## 0.709654

C and RB concurrently settle above their respective 5-day rolling averages 0.584 of the time, and concurrently below their respective 5-day averages 0.498 of the time

FRONT MONTH CORN VS. ETHANOL

## 
##  Pearson's product-moment correlation
## 
## data:  plotss$P1norm and plotss$P2norm
## t = 47.692, df = 1181, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.7908924 0.8299338
## sample estimates:
##       cor 
## 0.8113158

C and EH concurrently settle above their respective 5-day rolling averages 0.716 of the time, and concurrently below their respective 5-day averages 0.652 of the time

FRONT MONTH CORN VS. NG

## 
##  Pearson's product-moment correlation
## 
## data:  plotss$P1norm and plotss$P2norm
## t = 9.5631, df = 6562, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.09331182 0.14103189
## sample estimates:
##       cor 
## 0.1172395

C and NG concurrently settle above their respective 5-day rolling averages 0.519 of the time, and concurrently below their respective 5-day averages 0.538 of the time