Pair Correlation Between ATX and Stockholm

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

Pair Volatility

Given the investment horizon of 30 days, ATX is expected to generate 1.27 times more return on investment than Stockholm. However, ATX is 1.27 times more volatile than Stockholm. It trades about -0.15 of its potential returns per unit of risk. Stockholm is currently generating about -0.24 per unit of risk. If you would invest  338,315  in ATX on October 20, 2017 and sell it today you would lose (6,845)  from holding ATX or give up 2.02% of portfolio value over 30 days.

Correlation Coefficient

Pair Corralation between ATX and Stockholm
0.74

Parameters

Time Period1 Month [change]
DirectionPositive 
StrengthSignificant
Accuracy95.45%
ValuesDaily Returns

Diversification

Poor diversification

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

 Predicted Return Density 
      Returns