Correlation Between BJs Restaurants and Aluminumof China
Can any of the company-specific risk be diversified away by investing in both BJs Restaurants and Aluminumof China 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 BJs Restaurants and Aluminumof China into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BJs Restaurants and Aluminum of, you can compare the effects of market volatilities on BJs Restaurants and Aluminumof China 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 BJs Restaurants with a short position of Aluminumof China. Check out your portfolio center. Please also check ongoing floating volatility patterns of BJs Restaurants and Aluminumof China.
Diversification Opportunities for BJs Restaurants and Aluminumof China
0.14 | Correlation Coefficient |
Average diversification
The 3 months correlation between BJs and Aluminumof is 0.14. Overlapping area represents the amount of risk that can be diversified away by holding BJs Restaurants and Aluminum of in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aluminumof China and BJs Restaurants 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 BJs Restaurants are associated (or correlated) with Aluminumof China. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aluminumof China has no effect on the direction of BJs Restaurants i.e., BJs Restaurants and Aluminumof China go up and down completely randomly.
Pair Corralation between BJs Restaurants and Aluminumof China
Given the investment horizon of 90 days BJs Restaurants is expected to generate 8.87 times less return on investment than Aluminumof China. But when comparing it to its historical volatility, BJs Restaurants is 1.94 times less risky than Aluminumof China. It trades about 0.01 of its potential returns per unit of risk. Aluminum of is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 43.00 in Aluminum of on November 8, 2024 and sell it today you would earn a total of 22.00 from holding Aluminum of or generate 51.16% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 88.26% |
Values | Daily Returns |
BJs Restaurants vs. Aluminum of
Performance |
Timeline |
BJs Restaurants |
Aluminumof China |
BJs Restaurants and Aluminumof China Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BJs Restaurants and Aluminumof China
The main advantage of trading using opposite BJs Restaurants and Aluminumof China positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BJs Restaurants position performs unexpectedly, Aluminumof China 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 Aluminumof China will offset losses from the drop in Aluminumof China's long position.BJs Restaurants vs. Dominos Pizza Common | BJs Restaurants vs. Yum Brands | BJs Restaurants vs. The Wendys Co | BJs Restaurants vs. Wingstop |
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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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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