Correlation Between El Mor and Levinstein Eng
Can any of the company-specific risk be diversified away by investing in both El Mor and Levinstein Eng 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 El Mor and Levinstein Eng into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between El Mor Electric Installation and Levinstein Eng, you can compare the effects of market volatilities on El Mor and Levinstein Eng 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 El Mor with a short position of Levinstein Eng. Check out your portfolio center. Please also check ongoing floating volatility patterns of El Mor and Levinstein Eng.
Diversification Opportunities for El Mor and Levinstein Eng
0.74 | Correlation Coefficient |
Poor diversification
The 3 months correlation between ELMR and Levinstein is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding El-Mor Electric Installation and Levinstein Eng in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Levinstein Eng and El Mor 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 El Mor Electric Installation are associated (or correlated) with Levinstein Eng. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Levinstein Eng has no effect on the direction of El Mor i.e., El Mor and Levinstein Eng go up and down completely randomly.
Pair Corralation between El Mor and Levinstein Eng
Assuming the 90 days trading horizon El Mor is expected to generate 14.37 times less return on investment than Levinstein Eng. But when comparing it to its historical volatility, El Mor Electric Installation is 1.05 times less risky than Levinstein Eng. It trades about 0.0 of its potential returns per unit of risk. Levinstein Eng is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 3,119,000 in Levinstein Eng on December 29, 2023 and sell it today you would earn a total of 41,000 from holding Levinstein Eng or generate 1.31% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
El-Mor Electric Installation vs. Levinstein Eng
Performance |
Timeline |
El-Mor Electric Inst |
Levinstein Eng |
El Mor and Levinstein Eng Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with El Mor and Levinstein Eng
The main advantage of trading using opposite El Mor and Levinstein Eng positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if El Mor position performs unexpectedly, Levinstein Eng 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 Levinstein Eng will offset losses from the drop in Levinstein Eng's long position.El Mor vs. Nice | El Mor vs. Bank Leumi Le Israel | El Mor vs. ICL Israel Chemicals | El Mor vs. Mizrahi Tefahot |
Levinstein Eng vs. Nice | Levinstein Eng vs. Bank Leumi Le Israel | Levinstein Eng vs. ICL Israel Chemicals | Levinstein Eng vs. Mizrahi Tefahot |
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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