Correlation Between NYSE Composite and China Life

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

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

Diversification Opportunities for NYSE Composite and China Life

0.03

Correlation Coefficient

NYSE Composite  China Life

Significant diversification

The 3 months correlation between NYSE and China is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and China Life Insurance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China Life Insurance 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 China Life. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China Life Insurance has no effect on the direction of NYSE Composite i.e., NYSE Composite and China Life go up and down completely randomly.

Pair Corralation between NYSE Composite and China Life

Assuming the 90 days trading horizon NYSE Composite is expected to generate 4.27 times less return on investment than China Life. But when comparing it to its historical volatility, NYSE Composite is 3.17 times less risky than China Life. It trades about 0.02 of its potential returns per unit of risk. China Life Insurance is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest  190.00  in China Life Insurance on December 29, 2024 and sell it today you would earn a total of  6.00  from holding China Life Insurance or generate 3.16% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Insignificant
Accuracy	98.36%
Values	Daily Returns

NYSE Composite  vs.  China Life Insurance

Pair Trading with NYSE Composite and China Life

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

The idea behind NYSE Composite and China Life Insurance 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.