Correlation Between Getty Realty and ANZ Group
Can any of the company-specific risk be diversified away by investing in both Getty Realty and ANZ Group at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Getty Realty and ANZ Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Getty Realty and ANZ Group Holdings, you can compare the effects of market volatilities on Getty Realty and ANZ Group 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 Getty Realty with a short position of ANZ Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Getty Realty and ANZ Group.
Diversification Opportunities for Getty Realty and ANZ Group
-0.22 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Getty and ANZ is -0.22. Overlapping area represents the amount of risk that can be diversified away by holding Getty Realty and ANZ Group Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ANZ Group Holdings and Getty Realty 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 Getty Realty are associated (or correlated) with ANZ Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ANZ Group Holdings has no effect on the direction of Getty Realty i.e., Getty Realty and ANZ Group go up and down completely randomly.
Pair Corralation between Getty Realty and ANZ Group
Considering the 90-day investment horizon Getty Realty is expected to generate 14.93 times less return on investment than ANZ Group. But when comparing it to its historical volatility, Getty Realty is 2.95 times less risky than ANZ Group. It trades about 0.01 of its potential returns per unit of risk. ANZ Group Holdings is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 1,536 in ANZ Group Holdings on September 12, 2024 and sell it today you would earn a total of 102.00 from holding ANZ Group Holdings or generate 6.64% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 7.27% |
Values | Daily Returns |
Getty Realty vs. ANZ Group Holdings
Performance |
Timeline |
Getty Realty |
ANZ Group Holdings |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Getty Realty and ANZ Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Getty Realty and ANZ Group
The main advantage of trading using opposite Getty Realty and ANZ Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Getty Realty position performs unexpectedly, ANZ Group can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in ANZ Group will offset losses from the drop in ANZ Group's long position.Getty Realty vs. Regency Centers | Getty Realty vs. Site Centers Corp | Getty Realty vs. Brixmor Property | Getty Realty vs. Tanger Factory Outlet |
ANZ Group vs. Getty Realty | ANZ Group vs. Simon Property Group | ANZ Group vs. Modine Manufacturing | ANZ Group vs. Olympic Steel |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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