Correlation Between Microsoft and Federated Mid
Can any of the company-specific risk be diversified away by investing in both Microsoft and Federated Mid 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 Federated Mid into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Microsoft and Federated Mid Cap Index, you can compare the effects of market volatilities on Microsoft and Federated Mid 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 Federated Mid. Check out your portfolio center. Please also check ongoing floating volatility patterns of Microsoft and Federated Mid.
Diversification Opportunities for Microsoft and Federated Mid
0.18 | Correlation Coefficient |
Average diversification
The 3 months correlation between Microsoft and Federated is 0.18. Overlapping area represents the amount of risk that can be diversified away by holding Microsoft and Federated Mid Cap Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Federated Mid Cap 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 Federated Mid. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Federated Mid Cap has no effect on the direction of Microsoft i.e., Microsoft and Federated Mid go up and down completely randomly.
Pair Corralation between Microsoft and Federated Mid
Given the investment horizon of 90 days Microsoft is expected to generate 2.8 times less return on investment than Federated Mid. In addition to that, Microsoft is 1.39 times more volatile than Federated Mid Cap Index. It trades about 0.05 of its total potential returns per unit of risk. Federated Mid Cap Index is currently generating about 0.19 per unit of volatility. If you would invest 1,692 in Federated Mid Cap Index on September 2, 2024 and sell it today you would earn a total of 200.00 from holding Federated Mid Cap Index or generate 11.82% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Microsoft vs. Federated Mid Cap Index
Performance |
Timeline |
Microsoft |
Federated Mid Cap |
Microsoft and Federated Mid Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Microsoft and Federated Mid
The main advantage of trading using opposite Microsoft and Federated Mid positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Microsoft position performs unexpectedly, Federated Mid 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 Federated Mid will offset losses from the drop in Federated Mid's long position.Microsoft vs. Palo Alto Networks | Microsoft vs. Uipath Inc | Microsoft vs. Block Inc | Microsoft vs. Adobe Systems Incorporated |
Federated Mid vs. Federated Mdt Large | Federated Mid vs. Federated Global Allocation | Federated Mid vs. Federated Max Cap Index | Federated Mid vs. Federated Total Return |
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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