Correlation Between Realty Income and Global Self
Can any of the company-specific risk be diversified away by investing in both Realty Income and Global Self 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 Realty Income and Global Self into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Realty Income and Global Self Storage, you can compare the effects of market volatilities on Realty Income and Global Self 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 Realty Income with a short position of Global Self. Check out your portfolio center. Please also check ongoing floating volatility patterns of Realty Income and Global Self.
Diversification Opportunities for Realty Income and Global Self
0.02 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Realty and Global is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding Realty Income and Global Self Storage in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Global Self Storage and Realty Income 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 Realty Income are associated (or correlated) with Global Self. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Global Self Storage has no effect on the direction of Realty Income i.e., Realty Income and Global Self go up and down completely randomly.
Pair Corralation between Realty Income and Global Self
Taking into account the 90-day investment horizon Realty Income is expected to generate 1.17 times more return on investment than Global Self. However, Realty Income is 1.17 times more volatile than Global Self Storage. It trades about 0.11 of its potential returns per unit of risk. Global Self Storage is currently generating about -0.05 per unit of risk. If you would invest 5,190 in Realty Income on December 27, 2024 and sell it today you would earn a total of 426.00 from holding Realty Income or generate 8.21% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Realty Income vs. Global Self Storage
Performance |
Timeline |
Realty Income |
Global Self Storage |
Realty Income and Global Self Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Realty Income and Global Self
The main advantage of trading using opposite Realty Income and Global Self positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Realty Income position performs unexpectedly, Global Self 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 Global Self will offset losses from the drop in Global Self's long position.Realty Income vs. Federal Realty Investment | Realty Income vs. Macerich Company | Realty Income vs. National Retail Properties | Realty Income vs. Kimco Realty |
Global Self vs. LXP Industrial Trust | Global Self vs. First Industrial Realty | Global Self vs. Plymouth Industrial REIT | Global Self vs. Terreno Realty |
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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