Correlation Between Hormel Foods and United Rentals
Can any of the company-specific risk be diversified away by investing in both Hormel Foods and United Rentals 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 Hormel Foods and United Rentals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hormel Foods and United Rentals, you can compare the effects of market volatilities on Hormel Foods and United Rentals 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 Hormel Foods with a short position of United Rentals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hormel Foods and United Rentals.
Diversification Opportunities for Hormel Foods and United Rentals
-0.19 | Correlation Coefficient |
Good diversification
The 3 months correlation between Hormel and United is -0.19. Overlapping area represents the amount of risk that can be diversified away by holding Hormel Foods and United Rentals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on United Rentals and Hormel 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 Hormel Foods are associated (or correlated) with United Rentals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of United Rentals has no effect on the direction of Hormel Foods i.e., Hormel Foods and United Rentals go up and down completely randomly.
Pair Corralation between Hormel Foods and United Rentals
Assuming the 90 days trading horizon Hormel Foods is expected to generate 0.29 times more return on investment than United Rentals. However, Hormel Foods is 3.43 times less risky than United Rentals. It trades about -0.37 of its potential returns per unit of risk. United Rentals is currently generating about -0.17 per unit of risk. If you would invest 19,773 in Hormel Foods on October 25, 2024 and sell it today you would lose (1,701) from holding Hormel Foods or give up 8.6% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Hormel Foods vs. United Rentals
Performance |
| Timeline |
| Hormel Foods |
| United Rentals |
Hormel Foods and United Rentals Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hormel Foods and United Rentals
The main advantage of trading using opposite Hormel Foods and United Rentals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hormel Foods position performs unexpectedly, United Rentals 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 United Rentals will offset losses from the drop in United Rentals' long position.| Hormel Foods vs. Verizon Communications | Hormel Foods vs. Check Point Software | Hormel Foods vs. Charter Communications | Hormel Foods vs. Unity Software |
| United Rentals vs. Localiza Rent a | United Rentals vs. Vamos Locao de | United Rentals vs. Movida Participaes SA | United Rentals vs. Datadog, |
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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