Correlation Between LBA and PING

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

Diversification Opportunities for LBA and PING

-0.23
  Correlation Coefficient

Very good diversification

The 3 months correlation between LBA and PING is -0.23. Overlapping area represents the amount of risk that can be diversified away by holding LBA and PING in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PING and LBA 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 LBA are associated (or correlated) with PING. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PING has no effect on the direction of LBA i.e., LBA and PING go up and down completely randomly.

Pair Corralation between LBA and PING

If you would invest  0.03  in LBA on September 1, 2024 and sell it today you would lose (0.01) from holding LBA or give up 19.53% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthInsignificant
Accuracy0.76%
ValuesDaily Returns

LBA  vs.  PING

 Performance 
       Timeline  
LBA 

Risk-Adjusted Performance

6 of 100

 
Weak
 
Strong
Modest
Compared to the overall equity markets, risk-adjusted returns on investments in LBA are ranked lower than 6 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, LBA exhibited solid returns over the last few months and may actually be approaching a breakup point.
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.

LBA and PING Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with LBA and PING

The main advantage of trading using opposite LBA and PING positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if LBA position performs unexpectedly, PING 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 PING will offset losses from the drop in PING's long position.
The idea behind LBA and PING 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 Equity Valuation module to check real value of public entities based on technical and fundamental data.

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