Pair Correlation Between DOW and MetLife

This module allows you to analyze existing cross correlation between DOW and MetLife Inc. You can compare the effects of market volatilities on DOW and MetLife 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 MetLife. See also your portfolio center. Please also check ongoing floating volatility patterns of DOW and MetLife.
 Time Horizon     30 Days    Login   to change
Symbolsvs
 DOW  vs   MetLife Inc
 Performance (%) 
      Timeline 

Pair Volatility

Given the investment horizon of 30 days, DOW is expected to generate 0.69 times more return on investment than MetLife. However, DOW is 1.45 times less risky than MetLife. It trades about -0.1 of its potential returns per unit of risk. MetLife Inc is currently generating about -0.26 per unit of risk. If you would invest  2,621,460  in DOW on January 20, 2018 and sell it today you would lose (99,522)  from holding DOW or give up 3.8% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between DOW and MetLife
0.89

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthStrong
Accuracy100.0%
ValuesDaily Returns

Diversification

Very poor diversification

Overlapping area represents the amount of risk that can be diversified away by holding DOW and MetLife Inc in the same portfolio assuming nothing else is changed. The correlation between historical prices or returns on MetLife Inc 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 MetLife. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MetLife Inc has no effect on the direction of DOW i.e. DOW and MetLife go up and down completely randomly.
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Comparative Volatility

 Predicted Return Density 
      Returns