Correlation Between Delek Automotive and Neto ME
Can any of the company-specific risk be diversified away by investing in both Delek Automotive and Neto ME 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 Neto ME 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 Neto ME Holdings, you can compare the effects of market volatilities on Delek Automotive and Neto ME 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 Neto ME. Check out your portfolio center. Please also check ongoing floating volatility patterns of Delek Automotive and Neto ME.
Diversification Opportunities for Delek Automotive and Neto ME
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Delek and Neto is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding Delek Automotive Systems and Neto ME Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Neto ME Holdings 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 Neto ME. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Neto ME Holdings has no effect on the direction of Delek Automotive i.e., Delek Automotive and Neto ME go up and down completely randomly.
Pair Corralation between Delek Automotive and Neto ME
Assuming the 90 days trading horizon Delek Automotive Systems is expected to generate 1.46 times more return on investment than Neto ME. However, Delek Automotive is 1.46 times more volatile than Neto ME Holdings. It trades about 0.41 of its potential returns per unit of risk. Neto ME Holdings is currently generating about 0.5 per unit of risk. If you would invest 219,700 in Delek Automotive Systems on August 25, 2024 and sell it today you would earn a total of 37,800 from holding Delek Automotive Systems or generate 17.21% 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. Neto ME Holdings
Performance |
| Timeline |
| Delek Automotive Systems |
| Neto ME Holdings |
Delek Automotive and Neto ME Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Delek Automotive and Neto ME
The main advantage of trading using opposite Delek Automotive and Neto ME positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Delek Automotive position performs unexpectedly, Neto ME 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 Neto ME will offset losses from the drop in Neto ME'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 |
| Neto ME vs. Delek Automotive Systems | Neto ME vs. Globrands Group | Neto ME vs. Kerur Holdings | Neto ME vs. Ram On Investments and |
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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