Correlation Between EN Shoham and Global Knafaim
Can any of the company-specific risk be diversified away by investing in both EN Shoham and Global Knafaim 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 EN Shoham and Global Knafaim into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between EN Shoham Business and Global Knafaim Leasing, you can compare the effects of market volatilities on EN Shoham and Global Knafaim 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 EN Shoham with a short position of Global Knafaim. Check out your portfolio center. Please also check ongoing floating volatility patterns of EN Shoham and Global Knafaim.
Diversification Opportunities for EN Shoham and Global Knafaim
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between SHOM and Global is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding EN Shoham Business and Global Knafaim Leasing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Global Knafaim Leasing and EN Shoham 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 EN Shoham Business are associated (or correlated) with Global Knafaim. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Global Knafaim Leasing has no effect on the direction of EN Shoham i.e., EN Shoham and Global Knafaim go up and down completely randomly.
Pair Corralation between EN Shoham and Global Knafaim
Assuming the 90 days trading horizon EN Shoham Business is expected to generate 1.01 times more return on investment than Global Knafaim. However, EN Shoham is 1.01 times more volatile than Global Knafaim Leasing. It trades about 0.05 of its potential returns per unit of risk. Global Knafaim Leasing is currently generating about 0.02 per unit of risk. If you would invest 78,270 in EN Shoham Business on December 21, 2024 and sell it today you would earn a total of 2,840 from holding EN Shoham Business or generate 3.63% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
EN Shoham Business vs. Global Knafaim Leasing
Performance |
Timeline |
EN Shoham Business |
Global Knafaim Leasing |
EN Shoham and Global Knafaim Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with EN Shoham and Global Knafaim
The main advantage of trading using opposite EN Shoham and Global Knafaim positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if EN Shoham position performs unexpectedly, Global Knafaim 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 Global Knafaim will offset losses from the drop in Global Knafaim's long position.EN Shoham vs. Menif Financial Services | EN Shoham vs. Accel Solutions Group | EN Shoham vs. Rani Zim Shopping | EN Shoham vs. Mivtach Shamir |
Global Knafaim vs. Knafaim | Global Knafaim vs. El Al Israel | Global Knafaim vs. Orbit Technologies | Global Knafaim vs. Ashot Ashkelon Industries |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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