Correlation Between NYSE Composite and Invesco India

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

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

Diversification Opportunities for NYSE Composite and Invesco India

0.13

Correlation Coefficient

NYSE Composite  Invesco India

Average diversification

The 3 months correlation between NYSE and Invesco is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Invesco India ETF in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Invesco India ETF 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 Invesco India. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Invesco India ETF has no effect on the direction of NYSE Composite i.e., NYSE Composite and Invesco India go up and down completely randomly.

Pair Corralation between NYSE Composite and Invesco India

Assuming the 90 days trading horizon NYSE Composite is expected to generate 0.89 times more return on investment than Invesco India. However, NYSE Composite is 1.12 times less risky than Invesco India. It trades about 0.07 of its potential returns per unit of risk. Invesco India ETF is currently generating about -0.04 per unit of risk. If you would invest  1,804,858  in NYSE Composite on October 7, 2024 and sell it today you would earn a total of  120,571  from holding NYSE Composite or generate 6.68% return on investment over 90 days.

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

NYSE Composite  vs.  Invesco India ETF

Pair Trading with NYSE Composite and Invesco India

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

The idea behind NYSE Composite and Invesco India ETF 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.