Correlation Between Ulta Beauty and Advance Auto
Can any of the company-specific risk be diversified away by investing in both Ulta Beauty and Advance Auto 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 Ulta Beauty and Advance Auto into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ulta Beauty and Advance Auto Parts, you can compare the effects of market volatilities on Ulta Beauty and Advance Auto 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 Ulta Beauty with a short position of Advance Auto. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ulta Beauty and Advance Auto.
Diversification Opportunities for Ulta Beauty and Advance Auto
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Ulta and Advance is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Ulta Beauty and Advance Auto Parts in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Advance Auto Parts and Ulta Beauty 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 Ulta Beauty are associated (or correlated) with Advance Auto. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Advance Auto Parts has no effect on the direction of Ulta Beauty i.e., Ulta Beauty and Advance Auto go up and down completely randomly.
Pair Corralation between Ulta Beauty and Advance Auto
Assuming the 90 days trading horizon Ulta Beauty is expected to generate 1.05 times less return on investment than Advance Auto. But when comparing it to its historical volatility, Ulta Beauty is 1.19 times less risky than Advance Auto. It trades about 0.12 of its potential returns per unit of risk. Advance Auto Parts is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 1,430 in Advance Auto Parts on September 18, 2024 and sell it today you would earn a total of 264.00 from holding Advance Auto Parts or generate 18.46% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Ulta Beauty vs. Advance Auto Parts
Performance |
Timeline |
Ulta Beauty |
Advance Auto Parts |
Ulta Beauty and Advance Auto Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ulta Beauty and Advance Auto
The main advantage of trading using opposite Ulta Beauty and Advance Auto positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ulta Beauty position performs unexpectedly, Advance Auto 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 Advance Auto will offset losses from the drop in Advance Auto's long position.Ulta Beauty vs. Unity Software | Ulta Beauty vs. Mitsubishi UFJ Financial | Ulta Beauty vs. The Trade Desk | Ulta Beauty vs. Sumitomo Mitsui Financial |
Advance Auto vs. Ross Stores | Advance Auto vs. New Oriental Education | Advance Auto vs. Delta Air Lines | Advance Auto vs. TAL Education Group |
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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