Correlation Between Microsoft and Commercial Metals
Can any of the company-specific risk be diversified away by investing in both Microsoft and Commercial Metals 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 Microsoft and Commercial Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Microsoft and Commercial Metals, you can compare the effects of market volatilities on Microsoft and Commercial Metals 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 Microsoft with a short position of Commercial Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Microsoft and Commercial Metals.
Diversification Opportunities for Microsoft and Commercial Metals
0.06 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Microsoft and Commercial is 0.06. Overlapping area represents the amount of risk that can be diversified away by holding Microsoft and Commercial Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Commercial Metals and Microsoft 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 Microsoft are associated (or correlated) with Commercial Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Commercial Metals has no effect on the direction of Microsoft i.e., Microsoft and Commercial Metals go up and down completely randomly.
Pair Corralation between Microsoft and Commercial Metals
Given the investment horizon of 90 days Microsoft is expected to generate 5.96 times less return on investment than Commercial Metals. But when comparing it to its historical volatility, Microsoft is 1.59 times less risky than Commercial Metals. It trades about 0.01 of its potential returns per unit of risk. Commercial Metals is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 5,348 in Commercial Metals on August 27, 2024 and sell it today you would earn a total of 774.00 from holding Commercial Metals or generate 14.47% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Microsoft vs. Commercial Metals
Performance |
| Timeline |
| Microsoft |
| Commercial Metals |
Microsoft and Commercial Metals Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Microsoft and Commercial Metals
The main advantage of trading using opposite Microsoft and Commercial Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Microsoft position performs unexpectedly, Commercial Metals 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 Commercial Metals will offset losses from the drop in Commercial Metals' long position.| Microsoft vs. GigaCloud Technology Class | Microsoft vs. Arqit Quantum | Microsoft vs. Cemtrex | Microsoft vs. Rapid7 Inc |
| Commercial Metals vs. Olympic Steel | Commercial Metals vs. Steel Dynamics | Commercial Metals vs. Nucor Corp | Commercial Metals vs. Universal Stainless Alloy |
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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