Correlation Between Campbell Soup and Hormel Foods
Can any of the company-specific risk be diversified away by investing in both Campbell Soup and Hormel 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 Hormel 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 Hormel Foods, you can compare the effects of market volatilities on Campbell Soup and Hormel 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 Hormel Foods. Check out your portfolio center. Please also check ongoing floating volatility patterns of Campbell Soup and Hormel Foods.
Diversification Opportunities for Campbell Soup and Hormel Foods
0.16 | Correlation Coefficient |
Average diversification
The 3 months correlation between Campbell and Hormel is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding Campbell Soup and Hormel Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hormel 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 Hormel Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hormel Foods has no effect on the direction of Campbell Soup i.e., Campbell Soup and Hormel Foods go up and down completely randomly.
Pair Corralation between Campbell Soup and Hormel Foods
Considering the 90-day investment horizon Campbell Soup is expected to generate 4.1 times less return on investment than Hormel Foods. But when comparing it to its historical volatility, Campbell Soup is 1.67 times less risky than Hormel Foods. It trades about 0.04 of its potential returns per unit of risk. Hormel Foods is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 3,010 in Hormel Foods on January 21, 2024 and sell it today you would earn a total of 464.00 from holding Hormel Foods or generate 15.42% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 96.92% |
| Values | Daily Returns |
Campbell Soup vs. Hormel Foods
Performance |
| Timeline |
| Campbell Soup |
| Hormel Foods |
Campbell Soup and Hormel Foods Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Campbell Soup and Hormel Foods
The main advantage of trading using opposite Campbell Soup and Hormel Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Campbell Soup position performs unexpectedly, Hormel 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 Hormel Foods will offset losses from the drop in Hormel Foods' long position.| Campbell Soup vs. General Mills | Campbell Soup vs. Hormel Foods | Campbell Soup vs. Kellanova | Campbell Soup vs. Lamb Weston Holdings |
| Hormel Foods vs. Campbell Soup | Hormel Foods vs. General Mills | Hormel Foods vs. Kellanova | Hormel Foods vs. Lamb Weston Holdings |
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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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