Correlation Between Ermenegildo Zegna and Under Armour
Can any of the company-specific risk be diversified away by investing in both Ermenegildo Zegna and Under Armour 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 Ermenegildo Zegna and Under Armour into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ermenegildo Zegna NV and Under Armour C, you can compare the effects of market volatilities on Ermenegildo Zegna and Under Armour 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 Ermenegildo Zegna with a short position of Under Armour. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ermenegildo Zegna and Under Armour.
Diversification Opportunities for Ermenegildo Zegna and Under Armour
-0.1 | Correlation Coefficient |
Good diversification
The 3 months correlation between Ermenegildo and Under is -0.1. Overlapping area represents the amount of risk that can be diversified away by holding Ermenegildo Zegna NV and Under Armour C in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Under Armour C and Ermenegildo Zegna 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 Ermenegildo Zegna NV are associated (or correlated) with Under Armour. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Under Armour C has no effect on the direction of Ermenegildo Zegna i.e., Ermenegildo Zegna and Under Armour go up and down completely randomly.
Pair Corralation between Ermenegildo Zegna and Under Armour
Considering the 90-day investment horizon Ermenegildo Zegna NV is expected to generate 0.57 times more return on investment than Under Armour. However, Ermenegildo Zegna NV is 1.76 times less risky than Under Armour. It trades about 0.04 of its potential returns per unit of risk. Under Armour C is currently generating about -0.01 per unit of risk. If you would invest 804.00 in Ermenegildo Zegna NV on October 23, 2024 and sell it today you would earn a total of 27.00 from holding Ermenegildo Zegna NV or generate 3.36% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Ermenegildo Zegna NV vs. Under Armour C
Performance |
Timeline |
Ermenegildo Zegna |
Under Armour C |
Ermenegildo Zegna and Under Armour Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ermenegildo Zegna and Under Armour
The main advantage of trading using opposite Ermenegildo Zegna and Under Armour positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ermenegildo Zegna position performs unexpectedly, Under Armour 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 Under Armour will offset losses from the drop in Under Armour's long position.Ermenegildo Zegna vs. Oxford Industries | Ermenegildo Zegna vs. G III Apparel Group | Ermenegildo Zegna vs. Kontoor Brands | Ermenegildo Zegna vs. Columbia Sportswear |
Under Armour vs. Levi Strauss Co | Under Armour vs. Columbia Sportswear | Under Armour vs. Hanesbrands | Under Armour vs. PVH Corp |
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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