Correlation Between Meta Platforms and Under Armour
Can any of the company-specific risk be diversified away by investing in both Meta Platforms 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 Meta Platforms and Under Armour into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Meta Platforms and Under Armour C, you can compare the effects of market volatilities on Meta Platforms 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 Meta Platforms with a short position of Under Armour. Check out your portfolio center. Please also check ongoing floating volatility patterns of Meta Platforms and Under Armour.
Diversification Opportunities for Meta Platforms and Under Armour
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Meta and Under is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding Meta Platforms 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 Meta Platforms 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 Meta Platforms 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 Meta Platforms i.e., Meta Platforms and Under Armour go up and down completely randomly.
Pair Corralation between Meta Platforms and Under Armour
Allowing for the 90-day total investment horizon Meta Platforms is expected to under-perform the Under Armour. In addition to that, Meta Platforms is 1.19 times more volatile than Under Armour C. It trades about -0.13 of its total potential returns per unit of risk. Under Armour C is currently generating about -0.01 per unit of volatility. If you would invest 985.00 in Under Armour C on January 26, 2024 and sell it today you would lose (324.00) from holding Under Armour C or give up 32.89% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 7.29% |
| Values | Daily Returns |
Meta Platforms vs. Under Armour C
Performance |
| Timeline |
| Meta Platforms |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
| Under Armour C |
Meta Platforms and Under Armour Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Meta Platforms and Under Armour
The main advantage of trading using opposite Meta Platforms and Under Armour positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Meta Platforms 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.| Meta Platforms vs. Meta Platforms | Meta Platforms vs. Alphabet Inc Class A | Meta Platforms vs. Twilio Inc | Meta Platforms vs. Snap Inc |
| 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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