Correlation Between Summit Materials and Infosys
Can any of the company-specific risk be diversified away by investing in both Summit Materials and Infosys 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 Infosys into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Summit Materials and Infosys Ltd ADR, you can compare the effects of market volatilities on Summit Materials and Infosys 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 Infosys. Check out your portfolio center. Please also check ongoing floating volatility patterns of Summit Materials and Infosys.
Diversification Opportunities for Summit Materials and Infosys
-0.51 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Summit and Infosys is -0.51. Overlapping area represents the amount of risk that can be diversified away by holding Summit Materials and Infosys Ltd ADR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Infosys Ltd ADR 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 Infosys. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Infosys Ltd ADR has no effect on the direction of Summit Materials i.e., Summit Materials and Infosys go up and down completely randomly.
Pair Corralation between Summit Materials and Infosys
Considering the 90-day investment horizon Summit Materials is expected to generate 1.51 times more return on investment than Infosys. However, Summit Materials is 1.51 times more volatile than Infosys Ltd ADR. It trades about 0.2 of its potential returns per unit of risk. Infosys Ltd ADR is currently generating about 0.21 per unit of risk. If you would invest 4,670 in Summit Materials on September 3, 2024 and sell it today you would earn a total of 424.00 from holding Summit Materials or generate 9.08% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Summit Materials vs. Infosys Ltd ADR
Performance |
| Timeline |
| Summit Materials |
| Infosys Ltd ADR |
Summit Materials and Infosys Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Summit Materials and Infosys
The main advantage of trading using opposite Summit Materials and Infosys positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Summit Materials position performs unexpectedly, Infosys 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 Infosys will offset losses from the drop in Infosys' long position.| Summit Materials vs. Martin Marietta Materials | Summit Materials vs. Vulcan Materials | Summit Materials vs. United States Lime | Summit Materials vs. James Hardie Industries |
| Infosys vs. Accenture plc | Infosys vs. International Business Machines | Infosys vs. ASGN Inc | Infosys vs. ExlService Holdings |
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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