Correlation Between Electrovaya Common and Air Lease
Can any of the company-specific risk be diversified away by investing in both Electrovaya Common and Air Lease 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 Electrovaya Common and Air Lease into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Electrovaya Common Shares and Air Lease, you can compare the effects of market volatilities on Electrovaya Common and Air Lease 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 Electrovaya Common with a short position of Air Lease. Check out your portfolio center. Please also check ongoing floating volatility patterns of Electrovaya Common and Air Lease.
Diversification Opportunities for Electrovaya Common and Air Lease
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Electrovaya and Air is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Electrovaya Common Shares and Air Lease in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Air Lease and Electrovaya Common 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 Electrovaya Common Shares are associated (or correlated) with Air Lease. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Air Lease has no effect on the direction of Electrovaya Common i.e., Electrovaya Common and Air Lease go up and down completely randomly.
Pair Corralation between Electrovaya Common and Air Lease
Given the investment horizon of 90 days Electrovaya Common Shares is expected to under-perform the Air Lease. In addition to that, Electrovaya Common is 2.04 times more volatile than Air Lease. It trades about 0.0 of its total potential returns per unit of risk. Air Lease is currently generating about 0.08 per unit of volatility. If you would invest 3,331 in Air Lease on September 24, 2024 and sell it today you would earn a total of 1,526 from holding Air Lease or generate 45.81% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Electrovaya Common Shares vs. Air Lease
Performance |
Timeline |
Electrovaya Common Shares |
Air Lease |
Electrovaya Common and Air Lease Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Electrovaya Common and Air Lease
The main advantage of trading using opposite Electrovaya Common and Air Lease positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Electrovaya Common position performs unexpectedly, Air Lease 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 Air Lease will offset losses from the drop in Air Lease's long position.Electrovaya Common vs. Pioneer Power Solutions | Electrovaya Common vs. Ocean Power Technologies | Electrovaya Common vs. Ideal Power | Electrovaya Common vs. Expion360 |
Air Lease vs. PROG Holdings | Air Lease vs. McGrath RentCorp | Air Lease vs. HE Equipment Services | Air Lease vs. GATX 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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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