Correlation Between SC and ABL

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

Diversification Opportunities for SC and ABL

0.0
  Correlation Coefficient
 SC
 ABL

Pay attention - limited upside

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

Pair Corralation between SC and ABL

If you would invest (100.00) in ABL on December 27, 2024 and sell it today you would earn a total of  100.00  from holding ABL or generate -100.0% return on investment over 90 days.
Time Period3 Months [change]
DirectionFlat 
StrengthInsignificant
Accuracy0.0%
ValuesDaily Returns

SC  vs.  ABL

 Performance 
       Timeline  
SC 

Risk-Adjusted Performance

Very Weak

 
Weak
 
Strong
Over the last 90 days SC has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of unsteady performance in the last few months, the Crypto's fundamental indicators remain rather sound which may send shares a bit higher in April 2025. The latest tumult may also be a sign of longer-term up-swing for SC shareholders.
ABL 

Risk-Adjusted Performance

Very Weak

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

SC and ABL Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with SC and ABL

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