Correlation Between Afi Properties and Big Shopping
Can any of the company-specific risk be diversified away by investing in both Afi Properties and Big Shopping 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 Afi Properties and Big Shopping into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Afi Properties and Big Shopping Centers, you can compare the effects of market volatilities on Afi Properties and Big Shopping 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 Afi Properties with a short position of Big Shopping. Check out your portfolio center. Please also check ongoing floating volatility patterns of Afi Properties and Big Shopping.
Diversification Opportunities for Afi Properties and Big Shopping
-0.1 | Correlation Coefficient |
Good diversification
The 3 months correlation between Afi and Big is -0.1. Overlapping area represents the amount of risk that can be diversified away by holding Afi Properties and Big Shopping Centers in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Big Shopping Centers and Afi Properties 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 Afi Properties are associated (or correlated) with Big Shopping. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Big Shopping Centers has no effect on the direction of Afi Properties i.e., Afi Properties and Big Shopping go up and down completely randomly.
Pair Corralation between Afi Properties and Big Shopping
Assuming the 90 days trading horizon Afi Properties is expected to generate 1.17 times more return on investment than Big Shopping. However, Afi Properties is 1.17 times more volatile than Big Shopping Centers. It trades about 0.08 of its potential returns per unit of risk. Big Shopping Centers is currently generating about 0.07 per unit of risk. If you would invest 1,046,000 in Afi Properties on September 2, 2024 and sell it today you would earn a total of 659,000 from holding Afi Properties or generate 63.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Afi Properties vs. Big Shopping Centers
Performance |
| Timeline |
| Afi Properties |
| Big Shopping Centers |
Afi Properties and Big Shopping Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Afi Properties and Big Shopping
The main advantage of trading using opposite Afi Properties and Big Shopping positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Afi Properties position performs unexpectedly, Big Shopping 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 Big Shopping will offset losses from the drop in Big Shopping's long position.| Afi Properties vs. Alony Hetz Properties | Afi Properties vs. Clal Insurance Enterprises | Afi Properties vs. Electra | Afi Properties vs. Harel Insurance Investments |
| Big Shopping vs. Azrieli Group | Big Shopping vs. Melisron | Big Shopping vs. Amot Investments | Big Shopping vs. Alony Hetz 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 Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.
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