Correlation Between JNT and UQC

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

Diversification Opportunities for JNT and UQC

0.55
  Correlation Coefficient
 JNT
 UQC

Very weak diversification

The 3 months correlation between JNT and UQC is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding JNT and UQC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on UQC 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 UQC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of UQC has no effect on the direction of JNT i.e., JNT and UQC go up and down completely randomly.

Pair Corralation between JNT and UQC

If you would invest  733.00  in UQC on September 4, 2024 and sell it today you would earn a total of  199.00  from holding UQC or generate 27.15% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy4.55%
ValuesDaily Returns

JNT  vs.  UQC

 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.
UQC 

Risk-Adjusted Performance

10 of 100

 
Weak
 
Strong
OK
Compared to the overall equity markets, risk-adjusted returns on investments in UQC are ranked lower than 10 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, UQC exhibited solid returns over the last few months and may actually be approaching a breakup point.

JNT and UQC Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with JNT and UQC

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