Correlation Between PX Prague and Cboe UK

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

Diversification Opportunities for PX Prague and Cboe UK

0.88
  Correlation Coefficient

Very poor diversification

The 3 months correlation between PX Prague and Cboe is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding PX Prague Stock and Cboe UK Consumer in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cboe UK Consumer and PX Prague 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 PX Prague Stock are associated (or correlated) with Cboe UK. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cboe UK Consumer has no effect on the direction of PX Prague i.e., PX Prague and Cboe UK go up and down completely randomly.
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Pair Corralation between PX Prague and Cboe UK

Assuming the 90 days trading horizon PX Prague is expected to generate 3.78 times less return on investment than Cboe UK. But when comparing it to its historical volatility, PX Prague Stock is 1.97 times less risky than Cboe UK. It trades about 0.25 of its potential returns per unit of risk. Cboe UK Consumer is currently generating about 0.48 of returns per unit of risk over similar time horizon. If you would invest  2,957,042  in Cboe UK Consumer on September 1, 2024 and sell it today you would earn a total of  303,260  from holding Cboe UK Consumer or generate 10.26% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthStrong
Accuracy100.0%
ValuesDaily Returns

PX Prague Stock  vs.  Cboe UK Consumer

 Performance 
       Timeline  

PX Prague and Cboe UK Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with PX Prague and Cboe UK

The main advantage of trading using opposite PX Prague and Cboe UK positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PX Prague position performs unexpectedly, Cboe UK 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 Cboe UK will offset losses from the drop in Cboe UK's long position.
The idea behind PX Prague Stock and Cboe UK Consumer 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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