Correlation Between SL Green and Vornado Realty
Can any of the company-specific risk be diversified away by investing in both SL Green and Vornado 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 SL Green and Vornado Realty into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SL Green Realty and Vornado Realty Trust, you can compare the effects of market volatilities on SL Green and Vornado 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 SL Green with a short position of Vornado Realty. Check out your portfolio center. Please also check ongoing floating volatility patterns of SL Green and Vornado Realty.
Diversification Opportunities for SL Green and Vornado Realty
0.91 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between SLG and Vornado is 0.91. Overlapping area represents the amount of risk that can be diversified away by holding SL Green Realty and Vornado Realty Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Vornado Realty Trust and SL Green 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 SL Green Realty are associated (or correlated) with Vornado Realty. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Vornado Realty Trust has no effect on the direction of SL Green i.e., SL Green and Vornado Realty go up and down completely randomly.
Pair Corralation between SL Green and Vornado Realty
Considering the 90-day investment horizon SL Green Realty is expected to generate 1.06 times more return on investment than Vornado Realty. However, SL Green is 1.06 times more volatile than Vornado Realty Trust. It trades about 0.07 of its potential returns per unit of risk. Vornado Realty Trust is currently generating about 0.06 per unit of risk. If you would invest 3,535 in SL Green Realty on August 27, 2024 and sell it today you would earn a total of 4,428 from holding SL Green Realty or generate 125.26% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
SL Green Realty vs. Vornado Realty Trust
Performance |
| Timeline |
| SL Green Realty |
| Vornado Realty Trust |
SL Green and Vornado Realty Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SL Green and Vornado Realty
The main advantage of trading using opposite SL Green and Vornado Realty positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SL Green position performs unexpectedly, Vornado 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 Vornado Realty will offset losses from the drop in Vornado Realty's long position.| SL Green vs. Boston Properties | SL Green vs. Douglas Emmett | SL Green vs. Kilroy Realty Corp | SL Green vs. Alexandria Real Estate |
| Vornado Realty vs. Boston Properties | Vornado Realty vs. Alexandria Real Estate | Vornado Realty vs. Brandywine Realty Trust | Vornado Realty vs. Hudson Pacific Properties |
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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