Correlation Between NYSE Composite and Calvert Income

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

By analyzing existing cross correlation between NYSE Composite and Calvert Income Fund, you can compare the effects of market volatilities on NYSE Composite and Calvert Income 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 NYSE Composite with a short position of Calvert Income. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Calvert Income.

Diversification Opportunities for NYSE Composite and Calvert Income

0.8

Correlation Coefficient

NYSE Composite  Calvert Income

Very poor diversification

The 3 months correlation between NYSE and Calvert is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Calvert Income Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Calvert Income and NYSE Composite 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 NYSE Composite are associated (or correlated) with Calvert Income. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Calvert Income has no effect on the direction of NYSE Composite i.e., NYSE Composite and Calvert Income go up and down completely randomly.

Pair Corralation between NYSE Composite and Calvert Income

Assuming the 90 days trading horizon NYSE Composite is expected to under-perform the Calvert Income. In addition to that, NYSE Composite is 2.61 times more volatile than Calvert Income Fund. It trades about -0.02 of its total potential returns per unit of risk. Calvert Income Fund is currently generating about 0.06 per unit of volatility. If you would invest  1,502  in Calvert Income Fund on December 2, 2024 and sell it today you would earn a total of  15.00  from holding Calvert Income Fund or generate 1.0% return on investment over 90 days.

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

NYSE Composite  vs.  Calvert Income Fund

Pair Trading with NYSE Composite and Calvert Income

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

The idea behind NYSE Composite and Calvert Income Fund 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 Fundamental Analysis module to view fundamental data based on most recent published financial statements.