Correlation Between Evolv Technologies and Lands End
Can any of the company-specific risk be diversified away by investing in both Evolv Technologies and Lands End 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 Evolv Technologies and Lands End into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Evolv Technologies Holdings and Lands End, you can compare the effects of market volatilities on Evolv Technologies and Lands End 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 Evolv Technologies with a short position of Lands End. Check out your portfolio center. Please also check ongoing floating volatility patterns of Evolv Technologies and Lands End.
Diversification Opportunities for Evolv Technologies and Lands End
0.16 | Correlation Coefficient |
Average diversification
The 3 months correlation between Evolv and Lands is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding Evolv Technologies Holdings and Lands End in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lands End and Evolv Technologies 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 Evolv Technologies Holdings are associated (or correlated) with Lands End. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lands End has no effect on the direction of Evolv Technologies i.e., Evolv Technologies and Lands End go up and down completely randomly.
Pair Corralation between Evolv Technologies and Lands End
Given the investment horizon of 90 days Evolv Technologies is expected to generate 1.47 times less return on investment than Lands End. In addition to that, Evolv Technologies is 1.11 times more volatile than Lands End. It trades about 0.04 of its total potential returns per unit of risk. Lands End is currently generating about 0.07 per unit of volatility. If you would invest 768.00 in Lands End on January 19, 2024 and sell it today you would earn a total of 520.00 from holding Lands End or generate 67.71% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Evolv Technologies Holdings vs. Lands End
Performance |
| Timeline |
| Evolv Technologies |
| Lands End |
Evolv Technologies and Lands End Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Evolv Technologies and Lands End
The main advantage of trading using opposite Evolv Technologies and Lands End positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Evolv Technologies position performs unexpectedly, Lands End 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 Lands End will offset losses from the drop in Lands End's long position.| Evolv Technologies vs. Knightscope | Evolv Technologies vs. LogicMark | Evolv Technologies vs. Guardforce AI Co | Evolv Technologies vs. Bridger Aerospace Group |
| Lands End vs. Tillys Inc | Lands End vs. Zumiez Inc | Lands End vs. Citi Trends | Lands End vs. Cato Corporation |
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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