Correlation Between PING and DATA

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

Diversification Opportunities for PING and DATA

-0.41
  Correlation Coefficient

Very good diversification

The 3 months correlation between PING and DATA is -0.41. Overlapping area represents the amount of risk that can be diversified away by holding PING and DATA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DATA and PING 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 PING are associated (or correlated) with DATA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DATA has no effect on the direction of PING i.e., PING and DATA go up and down completely randomly.

Pair Corralation between PING and DATA

If you would invest  3.44  in DATA on August 23, 2024 and sell it today you would earn a total of  0.40  from holding DATA or generate 11.63% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthVery Weak
Accuracy4.35%
ValuesDaily Returns

PING  vs.  DATA

 Performance 
       Timeline  
PING 

Risk-Adjusted Performance

0 of 100

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

Risk-Adjusted Performance

0 of 100

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

PING and DATA Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with PING and DATA

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

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