Correlation Between Getty Realty and Terreno Realty
Can any of the company-specific risk be diversified away by investing in both Getty Realty and Terreno Realty 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 Terreno Realty into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Getty Realty and Terreno Realty, you can compare the effects of market volatilities on Getty Realty and Terreno Realty 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 Terreno Realty. Check out your portfolio center. Please also check ongoing floating volatility patterns of Getty Realty and Terreno Realty.
Diversification Opportunities for Getty Realty and Terreno Realty
-0.39 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Getty and Terreno is -0.39. Overlapping area represents the amount of risk that can be diversified away by holding Getty Realty and Terreno Realty in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Terreno Realty 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 Terreno Realty. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Terreno Realty has no effect on the direction of Getty Realty i.e., Getty Realty and Terreno Realty go up and down completely randomly.
Pair Corralation between Getty Realty and Terreno Realty
Considering the 90-day investment horizon Getty Realty is expected to generate 0.8 times more return on investment than Terreno Realty. However, Getty Realty is 1.25 times less risky than Terreno Realty. It trades about 0.12 of its potential returns per unit of risk. Terreno Realty is currently generating about -0.01 per unit of risk. If you would invest 2,511 in Getty Realty on August 27, 2024 and sell it today you would earn a total of 744.00 from holding Getty Realty or generate 29.63% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Getty Realty vs. Terreno Realty
Performance |
| Timeline |
| Getty Realty |
| Terreno Realty |
Getty Realty and Terreno Realty Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Getty Realty and Terreno Realty
The main advantage of trading using opposite Getty Realty and Terreno Realty positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Getty Realty position performs unexpectedly, Terreno Realty 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 Terreno Realty will offset losses from the drop in Terreno Realty'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 |
| Terreno Realty vs. Plymouth Industrial REIT | Terreno Realty vs. EastGroup Properties | Terreno Realty vs. LXP Industrial Trust | Terreno Realty vs. First Industrial 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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