Correlation Between NXS and ABL

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

Diversification Opportunities for NXS and ABL

0.54
  Correlation Coefficient
 NXS
 ABL

Very weak diversification

The 3 months correlation between NXS and ABL is 0.54. Overlapping area represents the amount of risk that can be diversified away by holding NXS and ABL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ABL and NXS 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 NXS 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 NXS i.e., NXS and ABL go up and down completely randomly.

Pair Corralation between NXS and ABL

If you would invest  16.00  in NXS on August 25, 2024 and sell it today you would earn a total of  8.00  from holding NXS or generate 50.0% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy4.55%
ValuesDaily Returns

NXS  vs.  ABL

 Performance 
       Timeline  
NXS 

Risk-Adjusted Performance

18 of 100

 
Weak
 
Strong
Solid
Compared to the overall equity markets, risk-adjusted returns on investments in NXS are ranked lower than 18 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, NXS exhibited solid returns over the last few months and may actually be approaching a breakup point.
ABL 

Risk-Adjusted Performance

0 of 100

 
Weak
 
Strong
Very Weak
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.

NXS and ABL Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with NXS and ABL

The main advantage of trading using opposite NXS and ABL positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NXS 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 NXS 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.
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.

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