Correlation Between SHIP HEALTHCARE and Microsoft
Can any of the company-specific risk be diversified away by investing in both SHIP HEALTHCARE and Microsoft 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 SHIP HEALTHCARE and Microsoft into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SHIP HEALTHCARE HLDGINC and Microsoft, you can compare the effects of market volatilities on SHIP HEALTHCARE and Microsoft 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 SHIP HEALTHCARE with a short position of Microsoft. Check out your portfolio center. Please also check ongoing floating volatility patterns of SHIP HEALTHCARE and Microsoft.
Diversification Opportunities for SHIP HEALTHCARE and Microsoft
-0.36 | Correlation Coefficient |
Very good diversification
The 3 months correlation between SHIP and Microsoft is -0.36. Overlapping area represents the amount of risk that can be diversified away by holding SHIP HEALTHCARE HLDGINC and Microsoft in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Microsoft and SHIP HEALTHCARE 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 SHIP HEALTHCARE HLDGINC are associated (or correlated) with Microsoft. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Microsoft has no effect on the direction of SHIP HEALTHCARE i.e., SHIP HEALTHCARE and Microsoft go up and down completely randomly.
Pair Corralation between SHIP HEALTHCARE and Microsoft
Assuming the 90 days horizon SHIP HEALTHCARE is expected to generate 1.96 times less return on investment than Microsoft. But when comparing it to its historical volatility, SHIP HEALTHCARE HLDGINC is 1.0 times less risky than Microsoft. It trades about 0.05 of its potential returns per unit of risk. Microsoft is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 39,362 in Microsoft on September 19, 2024 and sell it today you would earn a total of 3,878 from holding Microsoft or generate 9.85% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
SHIP HEALTHCARE HLDGINC vs. Microsoft
Performance |
Timeline |
SHIP HEALTHCARE HLDGINC |
Microsoft |
SHIP HEALTHCARE and Microsoft Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SHIP HEALTHCARE and Microsoft
The main advantage of trading using opposite SHIP HEALTHCARE and Microsoft positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SHIP HEALTHCARE position performs unexpectedly, Microsoft 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 Microsoft will offset losses from the drop in Microsoft's long position.SHIP HEALTHCARE vs. Superior Plus Corp | SHIP HEALTHCARE vs. NMI Holdings | SHIP HEALTHCARE vs. SIVERS SEMICONDUCTORS AB | SHIP HEALTHCARE vs. NorAm Drilling AS |
Microsoft vs. Bumrungrad Hospital Public | Microsoft vs. SHIP HEALTHCARE HLDGINC | Microsoft vs. National Health Investors | Microsoft vs. Sabra Health Care |
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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