Correlation Between METALL ZUG and Cboe UK

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

Diversification Opportunities for METALL ZUG and Cboe UK

-0.86
  Correlation Coefficient

Pay attention - limited upside

The 3 months correlation between METALL and Cboe is -0.86. Overlapping area represents the amount of risk that can be diversified away by holding METALL ZUG AG and Cboe UK Consumer in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cboe UK Consumer and METALL ZUG 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 METALL ZUG AG are associated (or correlated) with Cboe UK. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cboe UK Consumer has no effect on the direction of METALL ZUG i.e., METALL ZUG and Cboe UK go up and down completely randomly.
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Pair Corralation between METALL ZUG and Cboe UK

Assuming the 90 days trading horizon METALL ZUG AG is expected to under-perform the Cboe UK. But the stock apears to be less risky and, when comparing its historical volatility, METALL ZUG AG is 1.1 times less risky than Cboe UK. The stock trades about -0.09 of its potential returns per unit of risk. The Cboe UK Consumer is currently generating about 0.17 of returns per unit of risk over similar time horizon. If you would invest  2,630,440  in Cboe UK Consumer on September 23, 2024 and sell it today you would earn a total of  585,206  from holding Cboe UK Consumer or generate 22.25% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthSignificant
Accuracy94.62%
ValuesDaily Returns

METALL ZUG AG  vs.  Cboe UK Consumer

 Performance 
       Timeline  

METALL ZUG and Cboe UK Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with METALL ZUG and Cboe UK

The main advantage of trading using opposite METALL ZUG and Cboe UK positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if METALL ZUG position performs unexpectedly, Cboe UK 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 Cboe UK will offset losses from the drop in Cboe UK's long position.
The idea behind METALL ZUG AG and Cboe UK Consumer 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.

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