Correlation Between JNT and CMT

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

Diversification Opportunities for JNT and CMT

0.62
  Correlation Coefficient
 JNT
 CMT

Poor diversification

The 3 months correlation between JNT and CMT is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding JNT and CMT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CMT and JNT 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 JNT are associated (or correlated) with CMT. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CMT has no effect on the direction of JNT i.e., JNT and CMT go up and down completely randomly.

Pair Corralation between JNT and CMT

If you would invest  0.56  in CMT on September 4, 2024 and sell it today you would earn a total of  0.20  from holding CMT or generate 35.98% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthSignificant
Accuracy4.55%
ValuesDaily Returns

JNT  vs.  CMT

 Performance 
       Timeline  
JNT 

Risk-Adjusted Performance

0 of 100

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

Risk-Adjusted Performance

20 of 100

 
Weak
 
Strong
Solid
Compared to the overall equity markets, risk-adjusted returns on investments in CMT are ranked lower than 20 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, CMT exhibited solid returns over the last few months and may actually be approaching a breakup point.

JNT and CMT Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with JNT and CMT

The main advantage of trading using opposite JNT and CMT positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if JNT position performs unexpectedly, CMT 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 CMT will offset losses from the drop in CMT's long position.
The idea behind JNT and CMT 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.

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