Correlation Between Microsoft and Arthur J
Can any of the company-specific risk be diversified away by investing in both Microsoft and Arthur J 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 Arthur J into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Microsoft and Arthur J Gallagher, you can compare the effects of market volatilities on Microsoft and Arthur J 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 Arthur J. Check out your portfolio center. Please also check ongoing floating volatility patterns of Microsoft and Arthur J.
Diversification Opportunities for Microsoft and Arthur J
Weak diversification
The 3 months correlation between Microsoft and Arthur is 0.39. Overlapping area represents the amount of risk that can be diversified away by holding Microsoft and Arthur J Gallagher in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Arthur J Gallagher 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 Arthur J. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Arthur J Gallagher has no effect on the direction of Microsoft i.e., Microsoft and Arthur J go up and down completely randomly.
Pair Corralation between Microsoft and Arthur J
Given the investment horizon of 90 days Microsoft is expected to generate 1.16 times more return on investment than Arthur J. However, Microsoft is 1.16 times more volatile than Arthur J Gallagher. It trades about -0.22 of its potential returns per unit of risk. Arthur J Gallagher is currently generating about -0.25 per unit of risk. If you would invest 42,143 in Microsoft on January 27, 2024 and sell it today you would lose (2,239) from holding Microsoft or give up 5.31% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 95.65% |
| Values | Daily Returns |
Microsoft vs. Arthur J Gallagher
Performance |
| Timeline |
| Microsoft |
| Arthur J Gallagher |
Microsoft and Arthur J Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Microsoft and Arthur J
The main advantage of trading using opposite Microsoft and Arthur J positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Microsoft position performs unexpectedly, Arthur J 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 Arthur J will offset losses from the drop in Arthur J's long position.The idea behind Microsoft and Arthur J Gallagher pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| Arthur J vs. Aon PLC | Arthur J vs. Brown Brown | Arthur J vs. Willis Towers Watson | Arthur J vs. Erie Indemnity |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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