Pair Correlation Between DOW and Home Depot

This module allows you to analyze existing cross correlation between DOW and The Home Depot Inc. You can compare the effects of market volatilities on DOW and Home Depot and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in DOW with a short position of Home Depot. See also your portfolio center. Please also check ongoing floating volatility patterns of DOW and Home Depot.
 Time Horizon     30 Days    Login   to change
 DOW  vs   The Home Depot Inc
 Performance (%) 

Pair Volatility

Given the investment horizon of 30 days, DOW is expected to generate 0.78 times more return on investment than Home Depot. However, DOW is 1.29 times less risky than Home Depot. It trades about -0.08 of its potential returns per unit of risk. The Home Depot Inc is currently generating about -0.15 per unit of risk. If you would invest  2,607,172  in DOW on January 19, 2018 and sell it today you would lose (85,234)  from holding DOW or give up 3.27% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between DOW and Home Depot


Time Period1 Month [change]
StrengthVery Strong
ValuesDaily Returns


Almost no diversification

Overlapping area represents the amount of risk that can be diversified away by holding DOW and The Home Depot Inc in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on The Home Depot and DOW is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on DOW are associated (or correlated) with Home Depot. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of The Home Depot has no effect on the direction of DOW i.e. DOW and Home Depot go up and down completely randomly.

Comparative Volatility

 Predicted Return Density