Correlation Between NYSE Composite and MedMira

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

Diversification Opportunities for NYSE Composite and MedMira

0.55
  Correlation Coefficient

Very weak diversification

The 3 months correlation between NYSE and MedMira is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and MedMira in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MedMira 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 MedMira. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MedMira has no effect on the direction of NYSE Composite i.e., NYSE Composite and MedMira go up and down completely randomly.
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Pair Corralation between NYSE Composite and MedMira

Assuming the 90 days trading horizon NYSE Composite is expected to generate 2.34 times less return on investment than MedMira. But when comparing it to its historical volatility, NYSE Composite is 4.0 times less risky than MedMira. It trades about 0.13 of its potential returns per unit of risk. MedMira is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest  5.00  in MedMira on September 12, 2024 and sell it today you would earn a total of  0.50  from holding MedMira or generate 10.0% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy100.0%
ValuesDaily Returns

NYSE Composite  vs.  MedMira

 Performance 
       Timeline  

NYSE Composite and MedMira Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NYSE Composite and MedMira

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

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