Correlation Between Columbus McKinnon and GreenPower
Can any of the company-specific risk be diversified away by investing in both Columbus McKinnon and GreenPower 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 Columbus McKinnon and GreenPower into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Columbus McKinnon and GreenPower Motor, you can compare the effects of market volatilities on Columbus McKinnon and GreenPower 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 Columbus McKinnon with a short position of GreenPower. Check out your portfolio center. Please also check ongoing floating volatility patterns of Columbus McKinnon and GreenPower.
Diversification Opportunities for Columbus McKinnon and GreenPower
-0.49 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Columbus and GreenPower is -0.49. Overlapping area represents the amount of risk that can be diversified away by holding Columbus McKinnon and GreenPower Motor in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GreenPower Motor and Columbus McKinnon 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 Columbus McKinnon are associated (or correlated) with GreenPower. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GreenPower Motor has no effect on the direction of Columbus McKinnon i.e., Columbus McKinnon and GreenPower go up and down completely randomly.
Pair Corralation between Columbus McKinnon and GreenPower
Given the investment horizon of 90 days Columbus McKinnon is expected to under-perform the GreenPower. But the stock apears to be less risky and, when comparing its historical volatility, Columbus McKinnon is 4.98 times less risky than GreenPower. The stock trades about -0.04 of its potential returns per unit of risk. The GreenPower Motor is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 77.00 in GreenPower Motor on November 1, 2024 and sell it today you would earn a total of 2.00 from holding GreenPower Motor or generate 2.6% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Columbus McKinnon vs. GreenPower Motor
Performance |
Timeline |
Columbus McKinnon |
GreenPower Motor |
Columbus McKinnon and GreenPower Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Columbus McKinnon and GreenPower
The main advantage of trading using opposite Columbus McKinnon and GreenPower positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Columbus McKinnon position performs unexpectedly, GreenPower 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 GreenPower will offset losses from the drop in GreenPower's long position.Columbus McKinnon vs. CEA Industries | Columbus McKinnon vs. Thayer Ventures Acquisition | Columbus McKinnon vs. Iveda Solutions Warrant | Columbus McKinnon vs. Aquagold International |
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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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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