Correlation Between NYSE Composite and Floating Rate

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

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

Diversification Opportunities for NYSE Composite and Floating Rate

0.73

Correlation Coefficient

NYSE Composite  Floating Rate

Poor diversification

The 3 months correlation between NYSE and Floating is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Floating Rate Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Floating Rate 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 Floating Rate. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Floating Rate Income has no effect on the direction of NYSE Composite i.e., NYSE Composite and Floating Rate go up and down completely randomly.

Pair Corralation between NYSE Composite and Floating Rate

Assuming the 90 days trading horizon NYSE Composite is expected to generate 5.42 times less return on investment than Floating Rate. In addition to that, NYSE Composite is 8.91 times more volatile than Floating Rate Income. It trades about 0.01 of its total potential returns per unit of risk. Floating Rate Income is currently generating about 0.41 per unit of volatility. If you would invest  767.00  in Floating Rate Income on September 17, 2024 and sell it today you would earn a total of  3.00  from holding Floating Rate Income or generate 0.39% return on investment over 90 days.

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

NYSE Composite  vs.  Floating Rate Income

Pair Trading with NYSE Composite and Floating Rate

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

The idea behind NYSE Composite and Floating Rate Income 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.