Correlation Between FXP and GAIA

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

Diversification Opportunities for FXP and GAIA

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  Correlation Coefficient

Pay attention - limited upside

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

Pair Corralation between FXP and GAIA

If you would invest  0.06  in FXP on September 1, 2024 and sell it today you would earn a total of  0.00  from holding FXP or generate 0.0% return on investment over 90 days.
Time Period3 Months [change]
DirectionFlat 
StrengthInsignificant
Accuracy1.54%
ValuesDaily Returns

FXP  vs.  GAIA

 Performance 
       Timeline  
FXP 

Risk-Adjusted Performance

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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.
GAIA 

Risk-Adjusted Performance

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Weak
 
Strong
Very Weak
Over the last 90 days GAIA has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of unsteady performance in the last few months, the Crypto's fundamental indicators remain rather sound which may send shares a bit higher in December 2024. The latest tumult may also be a sign of longer-term up-swing for GAIA shareholders.

FXP and GAIA Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with FXP and GAIA

The main advantage of trading using opposite FXP and GAIA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if FXP position performs unexpectedly, GAIA 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 GAIA will offset losses from the drop in GAIA's long position.
The idea behind FXP and GAIA 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.

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