Correlation Between Empire State and Global Net
Can any of the company-specific risk be diversified away by investing in both Empire State and Global Net 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 Empire State and Global Net into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Empire State Realty and Global Net Lease,, you can compare the effects of market volatilities on Empire State and Global Net 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 Empire State with a short position of Global Net. Check out your portfolio center. Please also check ongoing floating volatility patterns of Empire State and Global Net.
Diversification Opportunities for Empire State and Global Net
0.04 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Empire and Global is 0.04. Overlapping area represents the amount of risk that can be diversified away by holding Empire State Realty and Global Net Lease, in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Global Net Lease, and Empire State 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 Empire State Realty are associated (or correlated) with Global Net. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Global Net Lease, has no effect on the direction of Empire State i.e., Empire State and Global Net go up and down completely randomly.
Pair Corralation between Empire State and Global Net
Given the investment horizon of 90 days Empire State Realty is expected to generate 0.77 times more return on investment than Global Net. However, Empire State Realty is 1.3 times less risky than Global Net. It trades about 0.15 of its potential returns per unit of risk. Global Net Lease, is currently generating about -0.14 per unit of risk. If you would invest 1,082 in Empire State Realty on August 29, 2024 and sell it today you would earn a total of 43.00 from holding Empire State Realty or generate 3.97% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Empire State Realty vs. Global Net Lease,
Performance |
| Timeline |
| Empire State Realty |
| Global Net Lease, |
Empire State and Global Net Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Empire State and Global Net
The main advantage of trading using opposite Empire State and Global Net positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Empire State position performs unexpectedly, Global Net 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 Net will offset losses from the drop in Global Net's long position.| Empire State vs. Paramount Group | Empire State vs. Hudson Pacific Properties | Empire State vs. Equity Commonwealth | Empire State vs. Douglas Emmett |
| Global Net vs. VICI Properties | Global Net vs. Essential Properties Realty | Global Net vs. Empire State Realty | Global Net vs. American Assets Trust |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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