Correlation Between Delek Automotive and Willy Food
Can any of the company-specific risk be diversified away by investing in both Delek Automotive and Willy Food 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 Willy Food 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 Willy Food, you can compare the effects of market volatilities on Delek Automotive and Willy Food 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 Willy Food. Check out your portfolio center. Please also check ongoing floating volatility patterns of Delek Automotive and Willy Food.
Diversification Opportunities for Delek Automotive and Willy Food
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Delek and Willy is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Delek Automotive Systems and Willy Food in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Willy Food 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 Willy Food. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Willy Food has no effect on the direction of Delek Automotive i.e., Delek Automotive and Willy Food go up and down completely randomly.
Pair Corralation between Delek Automotive and Willy Food
Assuming the 90 days trading horizon Delek Automotive is expected to generate 1.34 times less return on investment than Willy Food. In addition to that, Delek Automotive is 1.1 times more volatile than Willy Food. It trades about 0.26 of its total potential returns per unit of risk. Willy Food is currently generating about 0.39 per unit of volatility. If you would invest 249,800 in Willy Food on September 27, 2024 and sell it today you would earn a total of 39,000 from holding Willy Food or generate 15.61% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Delek Automotive Systems vs. Willy Food
Performance |
Timeline |
Delek Automotive Systems |
Willy Food |
Delek Automotive and Willy Food Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Delek Automotive and Willy Food
The main advantage of trading using opposite Delek Automotive and Willy Food positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Delek Automotive position performs unexpectedly, Willy Food 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 Willy Food will offset losses from the drop in Willy Food's long position.Delek Automotive vs. Bank Leumi Le Israel | Delek Automotive vs. Mizrahi Tefahot | Delek Automotive vs. Norstar | Delek Automotive vs. Gazit Globe |
Willy Food vs. Aryt Industries | Willy Food vs. Kerur Holdings | Willy Food vs. Scope Metals Group | Willy Food vs. Delek Automotive Systems |
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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