Correlation Between Rush Street and Afi Properties
Can any of the company-specific risk be diversified away by investing in both Rush Street and Afi Properties 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 Rush Street and Afi Properties into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Rush Street Interactive and Afi Properties, you can compare the effects of market volatilities on Rush Street and Afi Properties 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 Rush Street with a short position of Afi Properties. Check out your portfolio center. Please also check ongoing floating volatility patterns of Rush Street and Afi Properties.
Diversification Opportunities for Rush Street and Afi Properties
0.34 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Rush and Afi is 0.34. Overlapping area represents the amount of risk that can be diversified away by holding Rush Street Interactive and Afi Properties in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Afi Properties and Rush Street 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 Rush Street Interactive are associated (or correlated) with Afi Properties. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Afi Properties has no effect on the direction of Rush Street i.e., Rush Street and Afi Properties go up and down completely randomly.
Pair Corralation between Rush Street and Afi Properties
Considering the 90-day investment horizon Rush Street Interactive is expected to generate 1.6 times more return on investment than Afi Properties. However, Rush Street is 1.6 times more volatile than Afi Properties. It trades about 0.09 of its potential returns per unit of risk. Afi Properties is currently generating about 0.08 per unit of risk. If you would invest 419.00 in Rush Street Interactive on November 19, 2024 and sell it today you would earn a total of 1,251 from holding Rush Street Interactive or generate 298.57% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 77.62% |
| Values | Daily Returns |
Rush Street Interactive vs. Afi Properties
Performance |
| Timeline |
| Rush Street Interactive |
| Afi Properties |
Rush Street and Afi Properties Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Rush Street and Afi Properties
The main advantage of trading using opposite Rush Street and Afi Properties positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Rush Street position performs unexpectedly, Afi Properties 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 Afi Properties will offset losses from the drop in Afi Properties' long position.| Rush Street vs. Genius Sports | Rush Street vs. Gan | Rush Street vs. Ballys Corp | Rush Street vs. Hims Hers Health |
| Afi Properties vs. Alony Hetz Properties | Afi Properties vs. Clal Insurance Enterprises | Afi Properties vs. Electra | Afi Properties vs. Harel Insurance Investments |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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