Correlation Between Microsoft and Ballard Power
Can any of the company-specific risk be diversified away by investing in both Microsoft and Ballard Power 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 Ballard Power into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Microsoft and Ballard Power Systems, you can compare the effects of market volatilities on Microsoft and Ballard Power 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 Ballard Power. Check out your portfolio center. Please also check ongoing floating volatility patterns of Microsoft and Ballard Power.
Diversification Opportunities for Microsoft and Ballard Power
-0.63 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Microsoft and Ballard is -0.63. Overlapping area represents the amount of risk that can be diversified away by holding Microsoft and Ballard Power Systems in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ballard Power Systems 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 Ballard Power. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ballard Power Systems has no effect on the direction of Microsoft i.e., Microsoft and Ballard Power go up and down completely randomly.
Pair Corralation between Microsoft and Ballard Power
Assuming the 90 days trading horizon Microsoft is expected to generate 0.37 times more return on investment than Ballard Power. However, Microsoft is 2.74 times less risky than Ballard Power. It trades about 0.08 of its potential returns per unit of risk. Ballard Power Systems is currently generating about -0.05 per unit of risk. If you would invest 27,625 in Microsoft on August 29, 2024 and sell it today you would earn a total of 13,020 from holding Microsoft or generate 47.13% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Microsoft vs. Ballard Power Systems
Performance |
| Timeline |
| Microsoft |
| Ballard Power Systems |
Microsoft and Ballard Power Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Microsoft and Ballard Power
The main advantage of trading using opposite Microsoft and Ballard Power positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Microsoft position performs unexpectedly, Ballard Power 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 Ballard Power will offset losses from the drop in Ballard Power's long position.| Microsoft vs. Daido Steel Co | Microsoft vs. Safety Insurance Group | Microsoft vs. BLUESCOPE STEEL | Microsoft vs. Reinsurance Group of |
| Ballard Power vs. Superior Plus Corp | Ballard Power vs. NMI Holdings | Ballard Power vs. Origin Agritech | Ballard Power vs. SIVERS SEMICONDUCTORS AB |
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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