Correlation Between Delek Automotive and Shufersal
Can any of the company-specific risk be diversified away by investing in both Delek Automotive and Shufersal 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 Delek Automotive and Shufersal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Delek Automotive Systems and Shufersal, you can compare the effects of market volatilities on Delek Automotive and Shufersal 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 Delek Automotive with a short position of Shufersal. Check out your portfolio center. Please also check ongoing floating volatility patterns of Delek Automotive and Shufersal.
Diversification Opportunities for Delek Automotive and Shufersal
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Delek and Shufersal is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Delek Automotive Systems and Shufersal in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shufersal and Delek Automotive 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 Delek Automotive Systems are associated (or correlated) with Shufersal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shufersal has no effect on the direction of Delek Automotive i.e., Delek Automotive and Shufersal go up and down completely randomly.
Pair Corralation between Delek Automotive and Shufersal
Assuming the 90 days trading horizon Delek Automotive Systems is expected to generate 1.67 times more return on investment than Shufersal. However, Delek Automotive is 1.67 times more volatile than Shufersal. It trades about 0.27 of its potential returns per unit of risk. Shufersal is currently generating about 0.31 per unit of risk. If you would invest 211,500 in Delek Automotive Systems on September 13, 2024 and sell it today you would earn a total of 68,000 from holding Delek Automotive Systems or generate 32.15% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Delek Automotive Systems vs. Shufersal
Performance |
Timeline |
Delek Automotive Systems |
Shufersal |
Delek Automotive and Shufersal Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Delek Automotive and Shufersal
The main advantage of trading using opposite Delek Automotive and Shufersal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Delek Automotive position performs unexpectedly, Shufersal 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 Shufersal will offset losses from the drop in Shufersal's long position.Delek Automotive vs. Alony Hetz Properties | Delek Automotive vs. Harel Insurance Investments | Delek Automotive vs. Delek Group | Delek Automotive vs. Migdal Insurance |
Shufersal vs. Rami Levi | Shufersal vs. Neto ME Holdings | Shufersal vs. Strauss Group | Shufersal vs. Al Bad Massuot Yitzhak |
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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