Correlation Between Seneca Foods and Kellanova
Can any of the company-specific risk be diversified away by investing in both Seneca Foods and Kellanova 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 Seneca Foods and Kellanova into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Seneca Foods Corp and Kellanova, you can compare the effects of market volatilities on Seneca Foods and Kellanova 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 Seneca Foods with a short position of Kellanova. Check out your portfolio center. Please also check ongoing floating volatility patterns of Seneca Foods and Kellanova.
Diversification Opportunities for Seneca Foods and Kellanova
0.58 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Seneca and Kellanova is 0.58. Overlapping area represents the amount of risk that can be diversified away by holding Seneca Foods Corp and Kellanova in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kellanova and Seneca Foods 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 Seneca Foods Corp are associated (or correlated) with Kellanova. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kellanova has no effect on the direction of Seneca Foods i.e., Seneca Foods and Kellanova go up and down completely randomly.
Pair Corralation between Seneca Foods and Kellanova
Assuming the 90 days horizon Seneca Foods is expected to generate 1.09 times less return on investment than Kellanova. But when comparing it to its historical volatility, Seneca Foods Corp is 1.0 times less risky than Kellanova. It trades about 0.12 of its potential returns per unit of risk. Kellanova is currently generating about 0.13 of returns per unit of risk over similar time horizon. If you would invest 5,425 in Kellanova on August 27, 2024 and sell it today you would earn a total of 2,692 from holding Kellanova or generate 49.62% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Seneca Foods Corp vs. Kellanova
Performance |
| Timeline |
| Seneca Foods Corp |
| Kellanova |
Seneca Foods and Kellanova Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Seneca Foods and Kellanova
The main advantage of trading using opposite Seneca Foods and Kellanova positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Seneca Foods position performs unexpectedly, Kellanova 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 Kellanova will offset losses from the drop in Kellanova's long position.| Seneca Foods vs. Central Garden Pet | Seneca Foods vs. Central Garden Pet | Seneca Foods vs. Natures Sunshine Products | Seneca Foods vs. Associated British Foods |
| Kellanova vs. Campbell Soup | Kellanova vs. ConAgra Foods | Kellanova vs. Hormel Foods | Kellanova vs. Kraft Heinz Co |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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