Correlation Between First Watch and Bausch Lomb
Can any of the company-specific risk be diversified away by investing in both First Watch and Bausch Lomb 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 First Watch and Bausch Lomb into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Watch Restaurant and Bausch Lomb Corp, you can compare the effects of market volatilities on First Watch and Bausch Lomb 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 First Watch with a short position of Bausch Lomb. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Watch and Bausch Lomb.
Diversification Opportunities for First Watch and Bausch Lomb
0.41 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between First and Bausch is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding First Watch Restaurant and Bausch Lomb Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bausch Lomb Corp and First Watch 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 First Watch Restaurant are associated (or correlated) with Bausch Lomb. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bausch Lomb Corp has no effect on the direction of First Watch i.e., First Watch and Bausch Lomb go up and down completely randomly.
Pair Corralation between First Watch and Bausch Lomb
Given the investment horizon of 90 days First Watch Restaurant is expected to generate 1.23 times more return on investment than Bausch Lomb. However, First Watch is 1.23 times more volatile than Bausch Lomb Corp. It trades about 0.15 of its potential returns per unit of risk. Bausch Lomb Corp is currently generating about 0.18 per unit of risk. If you would invest 1,500 in First Watch Restaurant on September 12, 2024 and sell it today you would earn a total of 463.00 from holding First Watch Restaurant or generate 30.87% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
First Watch Restaurant vs. Bausch Lomb Corp
Performance |
Timeline |
First Watch Restaurant |
Bausch Lomb Corp |
First Watch and Bausch Lomb Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with First Watch and Bausch Lomb
The main advantage of trading using opposite First Watch and Bausch Lomb positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Watch position performs unexpectedly, Bausch Lomb 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 Bausch Lomb will offset losses from the drop in Bausch Lomb's long position.First Watch vs. Noble Romans | First Watch vs. Good Times Restaurants | First Watch vs. Flanigans Enterprises | First Watch vs. FAT Brands |
Bausch Lomb vs. The Cooper Companies, | Bausch Lomb vs. ICU Medical | Bausch Lomb vs. Hologic | Bausch Lomb vs. Becton Dickinson and |
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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