Correlation Between Check Point and SENECA FOODS
Can any of the company-specific risk be diversified away by investing in both Check Point and SENECA 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 Check Point and SENECA FOODS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Check Point Software and SENECA FOODS A, you can compare the effects of market volatilities on Check Point and SENECA 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 Check Point with a short position of SENECA FOODS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Check Point and SENECA FOODS.
Diversification Opportunities for Check Point and SENECA FOODS
-0.1 | Correlation Coefficient |
Good diversification
The 3 months correlation between Check and SENECA is -0.1. Overlapping area represents the amount of risk that can be diversified away by holding Check Point Software and SENECA FOODS A in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SENECA FOODS A and Check Point 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 Check Point Software are associated (or correlated) with SENECA FOODS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SENECA FOODS A has no effect on the direction of Check Point i.e., Check Point and SENECA FOODS go up and down completely randomly.
Pair Corralation between Check Point and SENECA FOODS
Assuming the 90 days trading horizon Check Point is expected to generate 6.92 times less return on investment than SENECA FOODS. But when comparing it to its historical volatility, Check Point Software is 1.3 times less risky than SENECA FOODS. It trades about 0.03 of its potential returns per unit of risk. SENECA FOODS A is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest 5,250 in SENECA FOODS A on September 13, 2024 and sell it today you would earn a total of 1,500 from holding SENECA FOODS A or generate 28.57% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Check Point Software vs. SENECA FOODS A
Performance |
Timeline |
Check Point Software |
SENECA FOODS A |
Check Point and SENECA FOODS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Check Point and SENECA FOODS
The main advantage of trading using opposite Check Point and SENECA FOODS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Check Point position performs unexpectedly, SENECA 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 SENECA FOODS will offset losses from the drop in SENECA FOODS's long position.Check Point vs. Apple Inc | Check Point vs. Apple Inc | Check Point vs. Apple Inc | Check Point vs. Apple Inc |
SENECA FOODS vs. Check Point Software | SENECA FOODS vs. Consolidated Communications Holdings | SENECA FOODS vs. MAROC TELECOM | SENECA FOODS vs. Vishay Intertechnology |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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