Correlation Between Summit Materials and Supercom
Can any of the company-specific risk be diversified away by investing in both Summit Materials and Supercom 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 Summit Materials and Supercom into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Summit Materials and Supercom, you can compare the effects of market volatilities on Summit Materials and Supercom 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 Summit Materials with a short position of Supercom. Check out your portfolio center. Please also check ongoing floating volatility patterns of Summit Materials and Supercom.
Diversification Opportunities for Summit Materials and Supercom
0.23 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Summit and Supercom is 0.23. Overlapping area represents the amount of risk that can be diversified away by holding Summit Materials and Supercom in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Supercom and Summit Materials 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 Summit Materials are associated (or correlated) with Supercom. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Supercom has no effect on the direction of Summit Materials i.e., Summit Materials and Supercom go up and down completely randomly.
Pair Corralation between Summit Materials and Supercom
Considering the 90-day investment horizon Summit Materials is expected to generate 2.02 times less return on investment than Supercom. But when comparing it to its historical volatility, Summit Materials is 1.83 times less risky than Supercom. It trades about 0.16 of its potential returns per unit of risk. Supercom is currently generating about 0.17 of returns per unit of risk over similar time horizon. If you would invest 319.00 in Supercom on September 1, 2024 and sell it today you would earn a total of 47.00 from holding Supercom or generate 14.73% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Summit Materials vs. Supercom
Performance |
| Timeline |
| Summit Materials |
| Supercom |
Summit Materials and Supercom Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Summit Materials and Supercom
The main advantage of trading using opposite Summit Materials and Supercom positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Summit Materials position performs unexpectedly, Supercom 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 Supercom will offset losses from the drop in Supercom's long position.| Summit Materials vs. Martin Marietta Materials | Summit Materials vs. Vulcan Materials | Summit Materials vs. James Hardie Industries | Summit Materials vs. Eagle Materials |
| Supercom vs. Desktop Metal | Supercom vs. Fabrinet | Supercom vs. Knowles Cor | Supercom vs. Ubiquiti Networks |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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