Correlation Between AG Mortgage and Power REIT
Can any of the company-specific risk be diversified away by investing in both AG Mortgage and Power REIT 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 AG Mortgage and Power REIT into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AG Mortgage Investment and Power REIT PFD, you can compare the effects of market volatilities on AG Mortgage and Power REIT 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 AG Mortgage with a short position of Power REIT. Check out your portfolio center. Please also check ongoing floating volatility patterns of AG Mortgage and Power REIT.
Diversification Opportunities for AG Mortgage and Power REIT
-0.31 | Correlation Coefficient |
Very good diversification
The 3 months correlation between MITT-PA and Power is -0.31. Overlapping area represents the amount of risk that can be diversified away by holding AG Mortgage Investment and Power REIT PFD in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Power REIT PFD and AG Mortgage 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 AG Mortgage Investment are associated (or correlated) with Power REIT. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Power REIT PFD has no effect on the direction of AG Mortgage i.e., AG Mortgage and Power REIT go up and down completely randomly.
Pair Corralation between AG Mortgage and Power REIT
Assuming the 90 days trading horizon AG Mortgage Investment is expected to generate 0.18 times more return on investment than Power REIT. However, AG Mortgage Investment is 5.71 times less risky than Power REIT. It trades about 0.08 of its potential returns per unit of risk. Power REIT PFD is currently generating about -0.03 per unit of risk. If you would invest 1,371 in AG Mortgage Investment on August 24, 2024 and sell it today you would earn a total of 856.00 from holding AG Mortgage Investment or generate 62.44% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 64.72% |
| Values | Daily Returns |
AG Mortgage Investment vs. Power REIT PFD
Performance |
| Timeline |
| AG Mortgage Investment |
| Power REIT PFD |
AG Mortgage and Power REIT Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with AG Mortgage and Power REIT
The main advantage of trading using opposite AG Mortgage and Power REIT positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AG Mortgage position performs unexpectedly, Power REIT 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 Power REIT will offset losses from the drop in Power REIT's long position.| AG Mortgage vs. New York Mortgage | AG Mortgage vs. New York Mortgage | AG Mortgage vs. Two Harbors Investment | AG Mortgage vs. Two Harbors Investment |
| Power REIT vs. Safe Bulkers | Power REIT vs. AG Mortgage Investment | Power REIT vs. Safe Bulkers | Power REIT vs. Aquagold International |
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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