Correlation Between Microsoft and Acadia Realty
Can any of the company-specific risk be diversified away by investing in both Microsoft and Acadia Realty 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 Acadia Realty into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Microsoft and Acadia Realty Trust, you can compare the effects of market volatilities on Microsoft and Acadia Realty 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 Acadia Realty. Check out your portfolio center. Please also check ongoing floating volatility patterns of Microsoft and Acadia Realty.
Diversification Opportunities for Microsoft and Acadia Realty
0.3 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Microsoft and Acadia is 0.3. Overlapping area represents the amount of risk that can be diversified away by holding Microsoft and Acadia Realty Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Acadia Realty Trust 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 Acadia Realty. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Acadia Realty Trust has no effect on the direction of Microsoft i.e., Microsoft and Acadia Realty go up and down completely randomly.
Pair Corralation between Microsoft and Acadia Realty
Given the investment horizon of 90 days Microsoft is expected to generate 1.06 times less return on investment than Acadia Realty. But when comparing it to its historical volatility, Microsoft is 1.27 times less risky than Acadia Realty. It trades about 0.09 of its potential returns per unit of risk. Acadia Realty Trust is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 1,211 in Acadia Realty Trust on September 22, 2024 and sell it today you would earn a total of 1,089 from holding Acadia Realty Trust or generate 89.93% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 97.83% |
Values | Daily Returns |
Microsoft vs. Acadia Realty Trust
Performance |
Timeline |
Microsoft |
Acadia Realty Trust |
Microsoft and Acadia Realty Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Microsoft and Acadia Realty
The main advantage of trading using opposite Microsoft and Acadia Realty positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Microsoft position performs unexpectedly, Acadia Realty 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 Acadia Realty will offset losses from the drop in Acadia Realty's long position.Microsoft vs. Global Blue Group | Microsoft vs. Aurora Mobile | Microsoft vs. Marqeta | Microsoft vs. Nextnav Acquisition Corp |
Acadia Realty vs. Simon Property Group | Acadia Realty vs. Realty Income | Acadia Realty vs. Link Real Estate | Acadia Realty vs. Kimco Realty |
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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