Correlation Between Applied Materials, and Ulta Beauty
Can any of the company-specific risk be diversified away by investing in both Applied Materials, and Ulta Beauty 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 Applied Materials, and Ulta Beauty into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Applied Materials, and Ulta Beauty, you can compare the effects of market volatilities on Applied Materials, and Ulta Beauty 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 Applied Materials, with a short position of Ulta Beauty. Check out your portfolio center. Please also check ongoing floating volatility patterns of Applied Materials, and Ulta Beauty.
Diversification Opportunities for Applied Materials, and Ulta Beauty
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Applied and Ulta is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding Applied Materials, and Ulta Beauty in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ulta Beauty and Applied Materials, 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 Applied Materials, are associated (or correlated) with Ulta Beauty. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ulta Beauty has no effect on the direction of Applied Materials, i.e., Applied Materials, and Ulta Beauty go up and down completely randomly.
Pair Corralation between Applied Materials, and Ulta Beauty
Assuming the 90 days trading horizon Applied Materials, is expected to generate 1.01 times more return on investment than Ulta Beauty. However, Applied Materials, is 1.01 times more volatile than Ulta Beauty. It trades about -0.1 of its potential returns per unit of risk. Ulta Beauty is currently generating about -0.18 per unit of risk. If you would invest 10,382 in Applied Materials, on December 24, 2024 and sell it today you would lose (1,742) from holding Applied Materials, or give up 16.78% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Applied Materials, vs. Ulta Beauty
Performance |
Timeline |
Applied Materials, |
Ulta Beauty |
Applied Materials, and Ulta Beauty Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Applied Materials, and Ulta Beauty
The main advantage of trading using opposite Applied Materials, and Ulta Beauty positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Applied Materials, position performs unexpectedly, Ulta Beauty 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 Ulta Beauty will offset losses from the drop in Ulta Beauty's long position.Applied Materials, vs. Autohome | Applied Materials, vs. Live Nation Entertainment, | Applied Materials, vs. Pure Storage, | Applied Materials, vs. Hormel Foods |
Ulta Beauty vs. Cognizant Technology Solutions | Ulta Beauty vs. Livetech da Bahia | Ulta Beauty vs. Lumen Technologies, | Ulta Beauty vs. Vulcan Materials |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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