Correlation Between NETGEAR and BJs Restaurants
Can any of the company-specific risk be diversified away by investing in both NETGEAR and BJs Restaurants 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 NETGEAR and BJs Restaurants into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NETGEAR and BJs Restaurants, you can compare the effects of market volatilities on NETGEAR and BJs Restaurants 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 NETGEAR with a short position of BJs Restaurants. Check out your portfolio center. Please also check ongoing floating volatility patterns of NETGEAR and BJs Restaurants.
Diversification Opportunities for NETGEAR and BJs Restaurants
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between NETGEAR and BJs is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding NETGEAR and BJs Restaurants in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BJs Restaurants and NETGEAR 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 NETGEAR are associated (or correlated) with BJs Restaurants. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BJs Restaurants has no effect on the direction of NETGEAR i.e., NETGEAR and BJs Restaurants go up and down completely randomly.
Pair Corralation between NETGEAR and BJs Restaurants
Given the investment horizon of 90 days NETGEAR is expected to generate 1.61 times less return on investment than BJs Restaurants. But when comparing it to its historical volatility, NETGEAR is 1.37 times less risky than BJs Restaurants. It trades about 0.21 of its potential returns per unit of risk. BJs Restaurants is currently generating about 0.25 of returns per unit of risk over similar time horizon. If you would invest 3,399 in BJs Restaurants on September 2, 2024 and sell it today you would earn a total of 445.00 from holding BJs Restaurants or generate 13.09% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
NETGEAR vs. BJs Restaurants
Performance |
| Timeline |
| NETGEAR |
| BJs Restaurants |
NETGEAR and BJs Restaurants Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with NETGEAR and BJs Restaurants
The main advantage of trading using opposite NETGEAR and BJs Restaurants positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NETGEAR position performs unexpectedly, BJs Restaurants 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 BJs Restaurants will offset losses from the drop in BJs Restaurants' long position.| NETGEAR vs. Comtech Telecommunications Corp | NETGEAR vs. KVH Industries | NETGEAR vs. Silicom | NETGEAR vs. Knowles Cor |
| BJs Restaurants vs. Dine Brands Global | BJs Restaurants vs. Brinker International | BJs Restaurants vs. Bloomin Brands | BJs Restaurants vs. The Cheesecake Factory |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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