Correlation Between XMX and GSC

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

Diversification Opportunities for XMX and GSC

0.45
  Correlation Coefficient
 XMX
 GSC

Very weak diversification

The 3 months correlation between XMX and GSC is 0.45. Overlapping area represents the amount of risk that can be diversified away by holding XMX and GSC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GSC and XMX 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 XMX are associated (or correlated) with GSC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GSC has no effect on the direction of XMX i.e., XMX and GSC go up and down completely randomly.

Pair Corralation between XMX and GSC

If you would invest  0.00  in XMX on September 1, 2024 and sell it today you would lose  0.00  from holding XMX or give up 14.29% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy0.76%
ValuesDaily Returns

XMX  vs.  GSC

 Performance 
       Timeline  
XMX 

Risk-Adjusted Performance

6 of 100

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

Risk-Adjusted Performance

0 of 100

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

XMX and GSC Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with XMX and GSC

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

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