Correlation Between Starbucks and Restaurant Brands
Can any of the company-specific risk be diversified away by investing in both Starbucks and Restaurant Brands 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 Starbucks and Restaurant Brands into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Starbucks and Restaurant Brands International, you can compare the effects of market volatilities on Starbucks and Restaurant Brands 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 Starbucks with a short position of Restaurant Brands. Check out your portfolio center. Please also check ongoing floating volatility patterns of Starbucks and Restaurant Brands.
Diversification Opportunities for Starbucks and Restaurant Brands
0.54 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Starbucks and Restaurant is 0.54. Overlapping area represents the amount of risk that can be diversified away by holding Starbucks and Restaurant Brands Internationa in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Restaurant Brands and Starbucks 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 Starbucks are associated (or correlated) with Restaurant Brands. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Restaurant Brands has no effect on the direction of Starbucks i.e., Starbucks and Restaurant Brands go up and down completely randomly.
Pair Corralation between Starbucks and Restaurant Brands
Assuming the 90 days horizon Starbucks is expected to generate 7.64 times less return on investment than Restaurant Brands. In addition to that, Starbucks is 1.05 times more volatile than Restaurant Brands International. It trades about 0.0 of its total potential returns per unit of risk. Restaurant Brands International is currently generating about 0.01 per unit of volatility. If you would invest 6,272 in Restaurant Brands International on September 23, 2024 and sell it today you would earn a total of 10.00 from holding Restaurant Brands International or generate 0.16% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Starbucks vs. Restaurant Brands Internationa
Performance |
Timeline |
Starbucks |
Restaurant Brands |
Starbucks and Restaurant Brands Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Starbucks and Restaurant Brands
The main advantage of trading using opposite Starbucks and Restaurant Brands positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Starbucks position performs unexpectedly, Restaurant Brands 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 Restaurant Brands will offset losses from the drop in Restaurant Brands' long position.Starbucks vs. McDonalds | Starbucks vs. Starbucks | Starbucks vs. Compass Group PLC | Starbucks vs. Yum Brands |
Restaurant Brands vs. McDonalds | Restaurant Brands vs. Starbucks | Restaurant Brands vs. Starbucks | Restaurant Brands vs. Compass Group PLC |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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