Correlation Between EZGO Technologies and Canada Goose
Can any of the company-specific risk be diversified away by investing in both EZGO Technologies and Canada Goose 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 EZGO Technologies and Canada Goose into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between EZGO Technologies and Canada Goose Holdings, you can compare the effects of market volatilities on EZGO Technologies and Canada Goose 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 EZGO Technologies with a short position of Canada Goose. Check out your portfolio center. Please also check ongoing floating volatility patterns of EZGO Technologies and Canada Goose.
Diversification Opportunities for EZGO Technologies and Canada Goose
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between EZGO and Canada is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding EZGO Technologies and Canada Goose Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Canada Goose Holdings and EZGO 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 EZGO Technologies are associated (or correlated) with Canada Goose. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Canada Goose Holdings has no effect on the direction of EZGO Technologies i.e., EZGO Technologies and Canada Goose go up and down completely randomly.
Pair Corralation between EZGO Technologies and Canada Goose
Given the investment horizon of 90 days EZGO Technologies is expected to under-perform the Canada Goose. In addition to that, EZGO Technologies is 2.7 times more volatile than Canada Goose Holdings. It trades about -0.01 of its total potential returns per unit of risk. Canada Goose Holdings is currently generating about -0.03 per unit of volatility. If you would invest 1,810 in Canada Goose Holdings on August 27, 2024 and sell it today you would lose (874.00) from holding Canada Goose Holdings or give up 48.29% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
EZGO Technologies vs. Canada Goose Holdings
Performance |
| Timeline |
| EZGO Technologies |
| Canada Goose Holdings |
EZGO Technologies and Canada Goose Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with EZGO Technologies and Canada Goose
The main advantage of trading using opposite EZGO Technologies and Canada Goose positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if EZGO Technologies position performs unexpectedly, Canada Goose 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 Canada Goose will offset losses from the drop in Canada Goose's long position.| EZGO Technologies vs. Vision Marine Technologies | EZGO Technologies vs. Marine Products | EZGO Technologies vs. Thor Industries | EZGO Technologies vs. BRP Inc |
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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 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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