Correlation Between Campbell Soup and Flowers Foods
Can any of the company-specific risk be diversified away by investing in both Campbell Soup and Flowers Foods 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 Campbell Soup and Flowers Foods into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Campbell Soup and Flowers Foods, you can compare the effects of market volatilities on Campbell Soup and Flowers Foods 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 Campbell Soup with a short position of Flowers Foods. Check out your portfolio center. Please also check ongoing floating volatility patterns of Campbell Soup and Flowers Foods.
Diversification Opportunities for Campbell Soup and Flowers Foods
0.91 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Campbell and Flowers is 0.91. Overlapping area represents the amount of risk that can be diversified away by holding Campbell Soup and Flowers Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Flowers Foods and Campbell Soup 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 Campbell Soup are associated (or correlated) with Flowers Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Flowers Foods has no effect on the direction of Campbell Soup i.e., Campbell Soup and Flowers Foods go up and down completely randomly.
Pair Corralation between Campbell Soup and Flowers Foods
Considering the 90-day investment horizon Campbell Soup is expected to generate 1.07 times more return on investment than Flowers Foods. However, Campbell Soup is 1.07 times more volatile than Flowers Foods. It trades about -0.03 of its potential returns per unit of risk. Flowers Foods is currently generating about -0.04 per unit of risk. If you would invest 4,933 in Campbell Soup on November 2, 2024 and sell it today you would lose (1,054) from holding Campbell Soup or give up 21.37% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 99.8% |
| Values | Daily Returns |
Campbell Soup vs. Flowers Foods
Performance |
| Timeline |
| Campbell Soup |
| Flowers Foods |
Campbell Soup and Flowers Foods Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Campbell Soup and Flowers Foods
The main advantage of trading using opposite Campbell Soup and Flowers Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Campbell Soup position performs unexpectedly, Flowers Foods 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 Flowers Foods will offset losses from the drop in Flowers Foods' long position.| Campbell Soup vs. General Mills | Campbell Soup vs. Hormel Foods | Campbell Soup vs. Kellanova | Campbell Soup vs. Lamb Weston Holdings |
| Flowers Foods vs. ConAgra Foods | Flowers Foods vs. McCormick Company Incorporated | Flowers Foods vs. Campbell Soup | Flowers Foods vs. Kellanova |
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 Bollinger Bands module to use Bollinger Bands indicator to analyze target price for a given investing horizon.
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