Correlation Between Dollarama and Restaurant Brands
Can any of the company-specific risk be diversified away by investing in both Dollarama 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 Dollarama and Restaurant Brands into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dollarama and Restaurant Brands International, you can compare the effects of market volatilities on Dollarama 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 Dollarama with a short position of Restaurant Brands. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dollarama and Restaurant Brands.
Diversification Opportunities for Dollarama and Restaurant Brands
0.59 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Dollarama and Restaurant is 0.59. Overlapping area represents the amount of risk that can be diversified away by holding Dollarama and Restaurant Brands Internationa in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Restaurant Brands and Dollarama 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 Dollarama 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 Dollarama i.e., Dollarama and Restaurant Brands go up and down completely randomly.
Pair Corralation between Dollarama and Restaurant Brands
Assuming the 90 days trading horizon Dollarama is expected to generate 1.26 times more return on investment than Restaurant Brands. However, Dollarama is 1.26 times more volatile than Restaurant Brands International. It trades about 0.1 of its potential returns per unit of risk. Restaurant Brands International is currently generating about 0.08 per unit of risk. If you would invest 13,307 in Dollarama on August 31, 2024 and sell it today you would earn a total of 1,277 from holding Dollarama or generate 9.6% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Dollarama vs. Restaurant Brands Internationa
Performance |
Timeline |
Dollarama |
Restaurant Brands |
Dollarama and Restaurant Brands Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Dollarama and Restaurant Brands
The main advantage of trading using opposite Dollarama and Restaurant Brands positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dollarama 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.Dollarama vs. Berkshire Hathaway CDR | Dollarama vs. JPMorgan Chase Co | Dollarama vs. Bank of America | Dollarama vs. Alphabet Inc CDR |
Restaurant Brands vs. Canadian Tire | Restaurant Brands vs. Dollarama | Restaurant Brands vs. Nutrien | Restaurant Brands vs. Magna International |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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