Pair Correlation Between All Ords and IPC

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

Pair Volatility

Assuming 30 trading days horizon, All Ords is expected to generate 0.45 times more return on investment than IPC. However, All Ords is 2.2 times less risky than IPC. It trades about 0.18 of its potential returns per unit of risk. IPC is currently generating about -0.16 per unit of risk. If you would invest  595,670  in All Ords on October 23, 2017 and sell it today you would earn a total of  8,750  from holding All Ords or generate 1.47% return on investment over 30 days.

Correlation Coefficient

Pair Corralation between All Ords and IPC
-0.49

Parameters

Time Period1 Month [change]
DirectionNegative 
StrengthVery Weak
Accuracy91.3%
ValuesDaily Returns

Diversification

Very good diversification

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

Comparative Volatility

 Predicted Return Density 
      Returns