Correlation Between Stack Capital and Dividend
Can any of the company-specific risk be diversified away by investing in both Stack Capital and Dividend 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 Stack Capital and Dividend into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Stack Capital Group and Dividend 15 Split, you can compare the effects of market volatilities on Stack Capital and Dividend 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 Stack Capital with a short position of Dividend. Check out your portfolio center. Please also check ongoing floating volatility patterns of Stack Capital and Dividend.
Diversification Opportunities for Stack Capital and Dividend
-0.22 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Stack and Dividend is -0.22. Overlapping area represents the amount of risk that can be diversified away by holding Stack Capital Group and Dividend 15 Split in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dividend 15 Split and Stack Capital 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 Stack Capital Group are associated (or correlated) with Dividend. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dividend 15 Split has no effect on the direction of Stack Capital i.e., Stack Capital and Dividend go up and down completely randomly.
Pair Corralation between Stack Capital and Dividend
Assuming the 90 days trading horizon Stack Capital Group is expected to under-perform the Dividend. In addition to that, Stack Capital is 3.04 times more volatile than Dividend 15 Split. It trades about -0.05 of its total potential returns per unit of risk. Dividend 15 Split is currently generating about 0.36 per unit of volatility. If you would invest 608.00 in Dividend 15 Split on August 10, 2025 and sell it today you would earn a total of 84.00 from holding Dividend 15 Split or generate 13.82% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Stack Capital Group vs. Dividend 15 Split
Performance |
| Timeline |
| Stack Capital Group |
| Dividend 15 Split |
Stack Capital and Dividend Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Stack Capital and Dividend
The main advantage of trading using opposite Stack Capital and Dividend positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Stack Capital position performs unexpectedly, Dividend 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 Dividend will offset losses from the drop in Dividend's long position.| Stack Capital vs. Global Dividend Growth | Stack Capital vs. Dividend 15 Split | Stack Capital vs. Premium Income | Stack Capital vs. Canadian Life Companies |
| Dividend vs. Premium Income | Dividend vs. Stack Capital Group | Dividend vs. Global Dividend Growth | Dividend vs. Canadian Life Companies |
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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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