Correlation Between Cal Maine and Churchill Downs
Can any of the company-specific risk be diversified away by investing in both Cal Maine and Churchill Downs 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 Cal Maine and Churchill Downs into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cal Maine Foods and Churchill Downs Incorporated, you can compare the effects of market volatilities on Cal Maine and Churchill Downs 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 Cal Maine with a short position of Churchill Downs. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cal Maine and Churchill Downs.
Diversification Opportunities for Cal Maine and Churchill Downs
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Cal and Churchill is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Cal Maine Foods and Churchill Downs Incorporated in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Churchill Downs and Cal Maine 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 Cal Maine Foods are associated (or correlated) with Churchill Downs. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Churchill Downs has no effect on the direction of Cal Maine i.e., Cal Maine and Churchill Downs go up and down completely randomly.
Pair Corralation between Cal Maine and Churchill Downs
Assuming the 90 days trading horizon Cal Maine Foods is expected to generate 1.23 times more return on investment than Churchill Downs. However, Cal Maine is 1.23 times more volatile than Churchill Downs Incorporated. It trades about 0.07 of its potential returns per unit of risk. Churchill Downs Incorporated is currently generating about 0.04 per unit of risk. If you would invest 5,277 in Cal Maine Foods on September 14, 2024 and sell it today you would earn a total of 4,783 from holding Cal Maine Foods or generate 90.64% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 99.8% |
| Values | Daily Returns |
Cal Maine Foods vs. Churchill Downs Incorporated
Performance |
| Timeline |
| Cal Maine Foods |
| Churchill Downs |
Cal Maine and Churchill Downs Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Cal Maine and Churchill Downs
The main advantage of trading using opposite Cal Maine and Churchill Downs positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cal Maine position performs unexpectedly, Churchill Downs 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 Churchill Downs will offset losses from the drop in Churchill Downs' long position.| Cal Maine vs. Zijin Mining Group | Cal Maine vs. Harmony Gold Mining | Cal Maine vs. Nufarm Limited | Cal Maine vs. HYDROFARM HLD GRP |
| Churchill Downs vs. Western Copper and | Churchill Downs vs. National Beverage Corp | Churchill Downs vs. Cal Maine Foods | Churchill Downs vs. COFCO Joycome Foods |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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