Correlation Between WAB and MTL

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

Diversification Opportunities for WAB and MTL

0.0
  Correlation Coefficient
 WAB
 MTL

Pay attention - limited upside

The 3 months correlation between WAB and MTL is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding WAB and MTL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MTL and WAB 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 WAB are associated (or correlated) with MTL. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MTL has no effect on the direction of WAB i.e., WAB and MTL go up and down completely randomly.

Pair Corralation between WAB and MTL

If you would invest (100.00) in WAB on November 10, 2024 and sell it today you would earn a total of  100.00  from holding WAB or generate -100.0% return on investment over 90 days.
Time Period3 Months [change]
DirectionFlat 
StrengthInsignificant
Accuracy0.0%
ValuesDaily Returns

WAB  vs.  MTL

 Performance 
       Timeline  
WAB 

Risk-Adjusted Performance

Very Weak

 
Weak
 
Strong
Over the last 90 days WAB has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of rather sound fundamental drivers, WAB is not utilizing all of its potentials. The latest stock price tumult, may contribute to shorter-term losses for the shareholders.
MTL 

Risk-Adjusted Performance

Very Weak

 
Weak
 
Strong
Over the last 90 days MTL has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of latest unsteady performance, the Crypto's essential indicators remain sound and the latest tumult on Wall Street may also be a sign of longer-term gains for MTL shareholders.

WAB and MTL Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with WAB and MTL

The main advantage of trading using opposite WAB and MTL positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if WAB position performs unexpectedly, MTL 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 MTL will offset losses from the drop in MTL's long position.
The idea behind WAB and MTL 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.
Check out your portfolio center.
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.

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