Correlation Between NYSE Composite and Voya Target

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

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

Diversification Opportunities for NYSE Composite and Voya Target

0.96

Correlation Coefficient

NYSE Composite  Voya Target

Almost no diversification

The 3 months correlation between NYSE and Voya is 0.96. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Voya Target Retirement in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Voya Target Retirement 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 Voya Target. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Voya Target Retirement has no effect on the direction of NYSE Composite i.e., NYSE Composite and Voya Target go up and down completely randomly.

Pair Corralation between NYSE Composite and Voya Target

Assuming the 90 days trading horizon NYSE Composite is expected to generate 1.24 times more return on investment than Voya Target. However, NYSE Composite is 1.24 times more volatile than Voya Target Retirement. It trades about 0.05 of its potential returns per unit of risk. Voya Target Retirement is currently generating about 0.01 per unit of risk. If you would invest  1,907,793  in NYSE Composite on December 28, 2024 and sell it today you would earn a total of  45,679  from holding NYSE Composite or generate 2.39% return on investment over 90 days.

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

NYSE Composite  vs.  Voya Target Retirement

Pair Trading with NYSE Composite and Voya Target

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

The idea behind NYSE Composite and Voya Target Retirement 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.