Correlation Between Microsoft and Highland Copper
Can any of the company-specific risk be diversified away by investing in both Microsoft and Highland Copper 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 Highland Copper into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Microsoft and Highland Copper, you can compare the effects of market volatilities on Microsoft and Highland Copper 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 Highland Copper. Check out your portfolio center. Please also check ongoing floating volatility patterns of Microsoft and Highland Copper.
Diversification Opportunities for Microsoft and Highland Copper
0.03 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Microsoft and Highland is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding Microsoft and Highland Copper in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Highland Copper 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 Highland Copper. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Highland Copper has no effect on the direction of Microsoft i.e., Microsoft and Highland Copper go up and down completely randomly.
Pair Corralation between Microsoft and Highland Copper
Given the investment horizon of 90 days Microsoft is expected to generate 2.1 times less return on investment than Highland Copper. But when comparing it to its historical volatility, Microsoft is 2.62 times less risky than Highland Copper. It trades about 0.17 of its potential returns per unit of risk. Highland Copper is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest 6.50 in Highland Copper on September 3, 2024 and sell it today you would earn a total of 0.50 from holding Highland Copper or generate 7.69% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Microsoft vs. Highland Copper
Performance |
| Timeline |
| Microsoft |
| Highland Copper |
Microsoft and Highland Copper Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Microsoft and Highland Copper
The main advantage of trading using opposite Microsoft and Highland Copper positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Microsoft position performs unexpectedly, Highland Copper 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 Highland Copper will offset losses from the drop in Highland Copper's long position.| Microsoft vs. Palo Alto Networks | Microsoft vs. Uipath Inc | Microsoft vs. Block Inc | Microsoft vs. Adobe Systems Incorporated |
| Highland Copper vs. Bell Copper | Highland Copper vs. CopperCorp Resources | Highland Copper vs. Dor Copper Mining | Highland Copper vs. Copper Fox Metals |
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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