Correlation Between NYSE Composite and Hannover

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Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Hannover 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 Hannover into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Hannover Re, you can compare the effects of market volatilities on NYSE Composite and Hannover 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 Hannover. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Hannover.

Diversification Opportunities for NYSE Composite and Hannover

-0.42
  Correlation Coefficient

Very good diversification

The 3 months correlation between NYSE and Hannover is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Hannover Re in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hannover Re 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 Hannover. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hannover Re has no effect on the direction of NYSE Composite i.e., NYSE Composite and Hannover go up and down completely randomly.
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Pair Corralation between NYSE Composite and Hannover

Assuming the 90 days trading horizon NYSE Composite is expected to generate 2.0 times less return on investment than Hannover. But when comparing it to its historical volatility, NYSE Composite is 1.95 times less risky than Hannover. It trades about 0.07 of its potential returns per unit of risk. Hannover Re is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest  2,993  in Hannover Re on September 19, 2024 and sell it today you would earn a total of  1,462  from holding Hannover Re or generate 48.85% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthVery Weak
Accuracy100.0%
ValuesDaily Returns

NYSE Composite  vs.  Hannover Re

 Performance 
       Timeline  

NYSE Composite and Hannover Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NYSE Composite and Hannover

The main advantage of trading using opposite NYSE Composite and Hannover positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Hannover 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 Hannover will offset losses from the drop in Hannover's long position.
The idea behind NYSE Composite and Hannover Re 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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.

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