Correlation Between Smurfit Kappa and CCL Industries
Can any of the company-specific risk be diversified away by investing in both Smurfit Kappa and CCL Industries 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 Smurfit Kappa and CCL Industries into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Smurfit Kappa Group and CCL Industries, you can compare the effects of market volatilities on Smurfit Kappa and CCL Industries 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 Smurfit Kappa with a short position of CCL Industries. Check out your portfolio center. Please also check ongoing floating volatility patterns of Smurfit Kappa and CCL Industries.
Diversification Opportunities for Smurfit Kappa and CCL Industries
-0.31 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Smurfit and CCL is -0.31. Overlapping area represents the amount of risk that can be diversified away by holding Smurfit Kappa Group and CCL Industries in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CCL Industries and Smurfit Kappa 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 Smurfit Kappa Group are associated (or correlated) with CCL Industries. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CCL Industries has no effect on the direction of Smurfit Kappa i.e., Smurfit Kappa and CCL Industries go up and down completely randomly.
Pair Corralation between Smurfit Kappa and CCL Industries
Assuming the 90 days horizon Smurfit Kappa Group is expected to generate 1.65 times more return on investment than CCL Industries. However, Smurfit Kappa is 1.65 times more volatile than CCL Industries. It trades about 0.15 of its potential returns per unit of risk. CCL Industries is currently generating about -0.08 per unit of risk. If you would invest 4,740 in Smurfit Kappa Group on September 3, 2024 and sell it today you would earn a total of 330.00 from holding Smurfit Kappa Group or generate 6.96% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.24% |
| Values | Daily Returns |
Smurfit Kappa Group vs. CCL Industries
Performance |
| Timeline |
| Smurfit Kappa Group |
| CCL Industries |
Smurfit Kappa and CCL Industries Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Smurfit Kappa and CCL Industries
The main advantage of trading using opposite Smurfit Kappa and CCL Industries positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Smurfit Kappa position performs unexpectedly, CCL Industries 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 CCL Industries will offset losses from the drop in CCL Industries' long position.| Smurfit Kappa vs. AptarGroup | Smurfit Kappa vs. Superior Plus Corp | Smurfit Kappa vs. NMI Holdings | Smurfit Kappa vs. Origin Agritech |
| CCL Industries vs. AptarGroup | CCL Industries vs. Superior Plus Corp | CCL Industries vs. NMI Holdings | CCL Industries vs. Origin Agritech |
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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