Correlation Between CF Industries and Grocery Outlet
Can any of the company-specific risk be diversified away by investing in both CF Industries and Grocery Outlet 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 CF Industries and Grocery Outlet into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CF Industries Holdings and Grocery Outlet Holding, you can compare the effects of market volatilities on CF Industries and Grocery Outlet 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 CF Industries with a short position of Grocery Outlet. Check out your portfolio center. Please also check ongoing floating volatility patterns of CF Industries and Grocery Outlet.
Diversification Opportunities for CF Industries and Grocery Outlet
-0.01 | Correlation Coefficient |
Good diversification
The 3 months correlation between CF Industries and Grocery is -0.01. Overlapping area represents the amount of risk that can be diversified away by holding CF Industries Holdings and Grocery Outlet Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Grocery Outlet Holding and CF Industries 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 CF Industries Holdings are associated (or correlated) with Grocery Outlet. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Grocery Outlet Holding has no effect on the direction of CF Industries i.e., CF Industries and Grocery Outlet go up and down completely randomly.
Pair Corralation between CF Industries and Grocery Outlet
Allowing for the 90-day total investment horizon CF Industries is expected to generate 2.25 times less return on investment than Grocery Outlet. But when comparing it to its historical volatility, CF Industries Holdings is 3.23 times less risky than Grocery Outlet. It trades about 0.21 of its potential returns per unit of risk. Grocery Outlet Holding is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest 1,672 in Grocery Outlet Holding on August 24, 2024 and sell it today you would earn a total of 262.50 from holding Grocery Outlet Holding or generate 15.7% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.65% |
| Values | Daily Returns |
CF Industries Holdings vs. Grocery Outlet Holding
Performance |
| Timeline |
| CF Industries Holdings |
| Grocery Outlet Holding |
CF Industries and Grocery Outlet Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with CF Industries and Grocery Outlet
The main advantage of trading using opposite CF Industries and Grocery Outlet positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CF Industries position performs unexpectedly, Grocery Outlet 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 Grocery Outlet will offset losses from the drop in Grocery Outlet's long position.| CF Industries vs. Nutrien | CF Industries vs. Intrepid Potash | CF Industries vs. Corteva | CF Industries vs. ICL Israel Chemicals |
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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 Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.
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