Correlation Between Elbit Systems and Verisk Analytics
Can any of the company-specific risk be diversified away by investing in both Elbit Systems and Verisk Analytics 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 Elbit Systems and Verisk Analytics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Elbit Systems and Verisk Analytics, you can compare the effects of market volatilities on Elbit Systems and Verisk Analytics 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 Elbit Systems with a short position of Verisk Analytics. Check out your portfolio center. Please also check ongoing floating volatility patterns of Elbit Systems and Verisk Analytics.
Diversification Opportunities for Elbit Systems and Verisk Analytics
0.24 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Elbit and Verisk is 0.24. Overlapping area represents the amount of risk that can be diversified away by holding Elbit Systems and Verisk Analytics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Verisk Analytics and Elbit Systems 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 Elbit Systems are associated (or correlated) with Verisk Analytics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Verisk Analytics has no effect on the direction of Elbit Systems i.e., Elbit Systems and Verisk Analytics go up and down completely randomly.
Pair Corralation between Elbit Systems and Verisk Analytics
Given the investment horizon of 90 days Elbit Systems is expected to generate 1.09 times more return on investment than Verisk Analytics. However, Elbit Systems is 1.09 times more volatile than Verisk Analytics. It trades about 0.03 of its potential returns per unit of risk. Verisk Analytics is currently generating about -0.13 per unit of risk. If you would invest 45,803 in Elbit Systems on August 25, 2025 and sell it today you would earn a total of 1,568 from holding Elbit Systems or generate 3.42% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Elbit Systems vs. Verisk Analytics
Performance |
| Timeline |
| Elbit Systems |
| Verisk Analytics |
Elbit Systems and Verisk Analytics Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Elbit Systems and Verisk Analytics
The main advantage of trading using opposite Elbit Systems and Verisk Analytics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Elbit Systems position performs unexpectedly, Verisk Analytics 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 Verisk Analytics will offset losses from the drop in Verisk Analytics' long position.| Elbit Systems vs. Curtiss Wright | Elbit Systems vs. BWX Technologies | Elbit Systems vs. Woodward | Elbit Systems vs. AerCap Holdings NV |
| Verisk Analytics vs. Equifax | Verisk Analytics vs. EMCOR Group | Verisk Analytics vs. Old Dominion Freight | Verisk Analytics vs. Ingersoll Rand |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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