Correlation Between BJs Restaurants and Custom Truck
Can any of the company-specific risk be diversified away by investing in both BJs Restaurants and Custom Truck 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 Custom Truck into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BJs Restaurants and Custom Truck One, you can compare the effects of market volatilities on BJs Restaurants and Custom Truck 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 Custom Truck. Check out your portfolio center. Please also check ongoing floating volatility patterns of BJs Restaurants and Custom Truck.
Diversification Opportunities for BJs Restaurants and Custom Truck
0.3 | Correlation Coefficient |
Weak diversification
The 3 months correlation between BJs and Custom is 0.3. Overlapping area represents the amount of risk that can be diversified away by holding BJs Restaurants and Custom Truck One in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Custom Truck One 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 Custom Truck. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Custom Truck One has no effect on the direction of BJs Restaurants i.e., BJs Restaurants and Custom Truck go up and down completely randomly.
Pair Corralation between BJs Restaurants and Custom Truck
Given the investment horizon of 90 days BJs Restaurants is expected to generate 0.89 times more return on investment than Custom Truck. However, BJs Restaurants is 1.13 times less risky than Custom Truck. It trades about 0.03 of its potential returns per unit of risk. Custom Truck One is currently generating about 0.0 per unit of risk. If you would invest 3,024 in BJs Restaurants on August 26, 2024 and sell it today you would earn a total of 510.00 from holding BJs Restaurants or generate 16.87% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
BJs Restaurants vs. Custom Truck One
Performance |
| Timeline |
| BJs Restaurants |
| Custom Truck One |
BJs Restaurants and Custom Truck Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BJs Restaurants and Custom Truck
The main advantage of trading using opposite BJs Restaurants and Custom Truck positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BJs Restaurants position performs unexpectedly, Custom Truck 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 Custom Truck will offset losses from the drop in Custom Truck's long position.| BJs Restaurants vs. Dine Brands Global | BJs Restaurants vs. Brinker International | BJs Restaurants vs. Bloomin Brands | BJs Restaurants vs. The Cheesecake Factory |
| Custom Truck vs. PROG Holdings | Custom Truck vs. McGrath RentCorp | Custom Truck vs. Mega Matrix Corp | Custom Truck vs. FTAI Aviation Ltd |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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