Correlation Between Microsoft and ARCA Institutional

Can any of the company-specific risk be diversified away by investing in both Microsoft and ARCA Institutional 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 ARCA Institutional into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Microsoft and ARCA Institutional, you can compare the effects of market volatilities on Microsoft and ARCA Institutional 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 ARCA Institutional. Check out your portfolio center. Please also check ongoing floating volatility patterns of Microsoft and ARCA Institutional.

Diversification Opportunities for Microsoft and ARCA Institutional

0.71

Correlation Coefficient

Microsoft  ARCA Institutional

Poor diversification

The 3 months correlation between Microsoft and ARCA is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Microsoft and ARCA Institutional in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ARCA Institutional 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 ARCA Institutional. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ARCA Institutional has no effect on the direction of Microsoft i.e., Microsoft and ARCA Institutional go up and down completely randomly.

Pair Corralation between Microsoft and ARCA Institutional

Given the investment horizon of 90 days Microsoft is expected to generate 1.33 times more return on investment than ARCA Institutional. However, Microsoft is 1.33 times more volatile than ARCA Institutional. It trades about 0.19 of its potential returns per unit of risk. ARCA Institutional is currently generating about 0.21 per unit of risk. If you would invest  41,879  in Microsoft on September 26, 2024 and sell it today you would earn a total of  2,054  from holding Microsoft or generate 4.9% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Significant
Accuracy	100.0%
Values	Daily Returns

Microsoft  vs.  ARCA Institutional

Pair Trading with Microsoft and ARCA Institutional

The main advantage of trading using opposite Microsoft and ARCA Institutional positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Microsoft position performs unexpectedly, ARCA Institutional 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 ARCA Institutional will offset losses from the drop in ARCA Institutional's long position.

The idea behind Microsoft and ARCA Institutional 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.

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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.