Correlation Between THC and FXP

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

Diversification Opportunities for THC and FXP

0.0
  Correlation Coefficient
 THC
 FXP

Pay attention - limited upside

The 3 months correlation between THC and FXP is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding THC and FXP in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FXP and THC 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 THC 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 THC i.e., THC and FXP go up and down completely randomly.

Pair Corralation between THC and FXP

If you would invest  0.28  in THC on January 29, 2024 and sell it today you would lose (0.10) from holding THC or give up 34.43% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionFlat 
StrengthInsignificant
Accuracy4.55%
ValuesDaily Returns

THC  vs.  FXP

 Performance 
       Timeline  
THC 

Risk-Adjusted Performance

9 of 100

 
Weak
 
Strong
OK
Compared to the overall equity markets, risk-adjusted returns on investments in THC are ranked lower than 9 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, THC 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.

THC and FXP Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with THC and FXP

The main advantage of trading using opposite THC and FXP positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if THC 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 THC 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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.

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