Correlation Between Sphere Entertainment and Dine Brands
Can any of the company-specific risk be diversified away by investing in both Sphere Entertainment and Dine 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 Sphere Entertainment and Dine Brands into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sphere Entertainment Co and Dine Brands Global, you can compare the effects of market volatilities on Sphere Entertainment and Dine 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 Sphere Entertainment with a short position of Dine Brands. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sphere Entertainment and Dine Brands.
Diversification Opportunities for Sphere Entertainment and Dine Brands
-0.45 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Sphere and Dine is -0.45. Overlapping area represents the amount of risk that can be diversified away by holding Sphere Entertainment Co and Dine Brands Global in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dine Brands Global and Sphere Entertainment 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 Sphere Entertainment Co are associated (or correlated) with Dine Brands. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dine Brands Global has no effect on the direction of Sphere Entertainment i.e., Sphere Entertainment and Dine Brands go up and down completely randomly.
Pair Corralation between Sphere Entertainment and Dine Brands
Given the investment horizon of 90 days Sphere Entertainment Co is expected to generate 0.79 times more return on investment than Dine Brands. However, Sphere Entertainment Co is 1.27 times less risky than Dine Brands. It trades about 0.07 of its potential returns per unit of risk. Dine Brands Global is currently generating about -0.14 per unit of risk. If you would invest 4,151 in Sphere Entertainment Co on December 2, 2024 and sell it today you would earn a total of 212.00 from holding Sphere Entertainment Co or generate 5.11% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Sphere Entertainment Co vs. Dine Brands Global
Performance |
Timeline |
Sphere Entertainment |
Dine Brands Global |
Sphere Entertainment and Dine Brands Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sphere Entertainment and Dine Brands
The main advantage of trading using opposite Sphere Entertainment and Dine Brands positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sphere Entertainment position performs unexpectedly, Dine 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 Dine Brands will offset losses from the drop in Dine Brands' long position.Sphere Entertainment vs. Compania Cervecerias Unidas | Sphere Entertainment vs. Willamette Valley Vineyards | Sphere Entertainment vs. United Microelectronics | Sphere Entertainment vs. Teradyne |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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