Correlation Between Dine Brands and Ming Shing
Can any of the company-specific risk be diversified away by investing in both Dine Brands and Ming Shing 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 Dine Brands and Ming Shing into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dine Brands Global and Ming Shing Group, you can compare the effects of market volatilities on Dine Brands and Ming Shing 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 Dine Brands with a short position of Ming Shing. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dine Brands and Ming Shing.
Diversification Opportunities for Dine Brands and Ming Shing
0.36 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Dine and Ming is 0.36. Overlapping area represents the amount of risk that can be diversified away by holding Dine Brands Global and Ming Shing Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ming Shing Group and Dine Brands 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 Dine Brands Global are associated (or correlated) with Ming Shing. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ming Shing Group has no effect on the direction of Dine Brands i.e., Dine Brands and Ming Shing go up and down completely randomly.
Pair Corralation between Dine Brands and Ming Shing
Considering the 90-day investment horizon Dine Brands Global is expected to under-perform the Ming Shing. But the stock apears to be less risky and, when comparing its historical volatility, Dine Brands Global is 2.97 times less risky than Ming Shing. The stock trades about 0.0 of its potential returns per unit of risk. The Ming Shing Group is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 559.00 in Ming Shing Group on September 26, 2024 and sell it today you would earn a total of 14.00 from holding Ming Shing Group or generate 2.5% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 53.66% |
Values | Daily Returns |
Dine Brands Global vs. Ming Shing Group
Performance |
Timeline |
Dine Brands Global |
Ming Shing Group |
Dine Brands and Ming Shing Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Dine Brands and Ming Shing
The main advantage of trading using opposite Dine Brands and Ming Shing positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dine Brands position performs unexpectedly, Ming Shing 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 Ming Shing will offset losses from the drop in Ming Shing's long position.Dine Brands vs. Bloomin Brands | Dine Brands vs. BJs Restaurants | Dine Brands vs. The Cheesecake Factory | Dine Brands vs. Brinker International |
Ming Shing vs. Summit Materials | Ming Shing vs. Boyd Gaming | Ming Shing vs. Dine Brands Global | Ming Shing vs. Barrick Gold 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 Sign In To Macroaxis module to sign in to explore Macroaxis' wealth optimization platform and fintech modules.
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