Correlation Between PAY and FXP

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

Diversification Opportunities for PAY and FXP

0.0
  Correlation Coefficient
 PAY
 FXP

Pay attention - limited upside

The 3 months correlation between PAY and FXP is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding PAY and FXP in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FXP and PAY 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 PAY are associated (or correlated) with FXP. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FXP has no effect on the direction of PAY i.e., PAY and FXP go up and down completely randomly.

Pair Corralation between PAY and FXP

If you would invest  0.71  in PAY on August 23, 2024 and sell it today you would earn a total of  0.00  from holding PAY or generate 0.14% return on investment over 90 days.
Time Period3 Months [change]
DirectionFlat 
StrengthInsignificant
Accuracy4.35%
ValuesDaily Returns

PAY  vs.  FXP

 Performance 
       Timeline  
PAY 

Risk-Adjusted Performance

2 of 100

 
Weak
 
Strong
Weak
Compared to the overall equity markets, risk-adjusted returns on investments in PAY are ranked lower than 2 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, PAY exhibited solid returns over the last few months and may actually be approaching a breakup point.
FXP 

Risk-Adjusted Performance

0 of 100

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

PAY and FXP Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with PAY and FXP

The main advantage of trading using opposite PAY and FXP positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PAY position performs unexpectedly, FXP 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 FXP will offset losses from the drop in FXP's long position.
The idea behind PAY and FXP 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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.

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