Correlation Between Arbor Realty and New York
Can any of the company-specific risk be diversified away by investing in both Arbor Realty and New York 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 Arbor Realty and New York into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Arbor Realty Trust and New York Mortgage, you can compare the effects of market volatilities on Arbor Realty and New York 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 Arbor Realty with a short position of New York. Check out your portfolio center. Please also check ongoing floating volatility patterns of Arbor Realty and New York.
Diversification Opportunities for Arbor Realty and New York
0.55 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Arbor and New is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Arbor Realty Trust and New York Mortgage in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on New York Mortgage and Arbor 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 Arbor Realty Trust are associated (or correlated) with New York. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of New York Mortgage has no effect on the direction of Arbor Realty i.e., Arbor Realty and New York go up and down completely randomly.
Pair Corralation between Arbor Realty and New York
Assuming the 90 days trading horizon Arbor Realty is expected to generate 1.25 times less return on investment than New York. In addition to that, Arbor Realty is 1.45 times more volatile than New York Mortgage. It trades about 0.05 of its total potential returns per unit of risk. New York Mortgage is currently generating about 0.09 per unit of volatility. If you would invest 1,506 in New York Mortgage on August 30, 2024 and sell it today you would earn a total of 776.00 from holding New York Mortgage or generate 51.53% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Arbor Realty Trust vs. New York Mortgage
Performance |
Timeline |
Arbor Realty Trust |
New York Mortgage |
Arbor Realty and New York Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Arbor Realty and New York
The main advantage of trading using opposite Arbor Realty and New York positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Arbor Realty position performs unexpectedly, New York 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 New York will offset losses from the drop in New York's long position.Arbor Realty vs. ACRES Commercial Realty | Arbor Realty vs. Dynex Capital | Arbor Realty vs. PennyMac Mortgage Investment | Arbor Realty vs. AG Mortgage Investment |
New York vs. AG Mortgage Investment | New York vs. AG Mortgage Investment | New York vs. Invesco Mortgage Capital | New York vs. Invesco Mortgage Capital |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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