Correlation Between AGVC and QKC

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

Diversification Opportunities for AGVC and QKC

-0.07
  Correlation Coefficient

Good diversification

The 3 months correlation between AGVC and QKC is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding AGVC and QKC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on QKC and AGVC 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 AGVC are associated (or correlated) with QKC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of QKC has no effect on the direction of AGVC i.e., AGVC and QKC go up and down completely randomly.

Pair Corralation between AGVC and QKC

If you would invest  0.84  in QKC on August 25, 2024 and sell it today you would earn a total of  0.20  from holding QKC or generate 24.46% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthInsignificant
Accuracy4.55%
ValuesDaily Returns

AGVC  vs.  QKC

 Performance 
       Timeline  
AGVC 

Risk-Adjusted Performance

0 of 100

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

Risk-Adjusted Performance

5 of 100

 
Weak
 
Strong
Modest
Compared to the overall equity markets, risk-adjusted returns on investments in QKC are ranked lower than 5 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, QKC exhibited solid returns over the last few months and may actually be approaching a breakup point.

AGVC and QKC Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with AGVC and QKC

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