Correlation Between Microsoft and Lowes Companies
Can any of the company-specific risk be diversified away by investing in both Microsoft and Lowes Companies 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 Lowes Companies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Microsoft and Lowes Companies, you can compare the effects of market volatilities on Microsoft and Lowes Companies 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 Lowes Companies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Microsoft and Lowes Companies.
Diversification Opportunities for Microsoft and Lowes Companies
0.18 | Correlation Coefficient |
Average diversification
The 3 months correlation between Microsoft and Lowes is 0.18. Overlapping area represents the amount of risk that can be diversified away by holding Microsoft and Lowes Companies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lowes Companies 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 Lowes Companies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lowes Companies has no effect on the direction of Microsoft i.e., Microsoft and Lowes Companies go up and down completely randomly.
Pair Corralation between Microsoft and Lowes Companies
Given the investment horizon of 90 days Microsoft is expected to generate 1.05 times less return on investment than Lowes Companies. But when comparing it to its historical volatility, Microsoft is 1.07 times less risky than Lowes Companies. It trades about 0.06 of its potential returns per unit of risk. Lowes Companies is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 20,436 in Lowes Companies on August 31, 2024 and sell it today you would earn a total of 6,807 from holding Lowes Companies or generate 33.31% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Microsoft vs. Lowes Companies
Performance |
| Timeline |
| Microsoft |
| Lowes Companies |
Microsoft and Lowes Companies Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Microsoft and Lowes Companies
The main advantage of trading using opposite Microsoft and Lowes Companies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Microsoft position performs unexpectedly, Lowes Companies 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 Lowes Companies will offset losses from the drop in Lowes Companies' long position.| Microsoft vs. Palo Alto Networks | Microsoft vs. Uipath Inc | Microsoft vs. Block Inc | Microsoft vs. Adobe Systems Incorporated |
| Lowes Companies vs. RLJ Lodging Trust | Lowes Companies vs. Aquagold International | Lowes Companies vs. Stepstone Group | Lowes Companies vs. Morningstar Unconstrained Allocation |
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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