Correlation Between Cboe UK and Helios Towers

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

Diversification Opportunities for Cboe UK and Helios Towers

-0.81
  Correlation Coefficient

Pay attention - limited upside

The 3 months correlation between Cboe and Helios is -0.81. Overlapping area represents the amount of risk that can be diversified away by holding Cboe UK Consumer and Helios Towers Plc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Helios Towers Plc and Cboe UK 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 Cboe UK Consumer are associated (or correlated) with Helios Towers. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Helios Towers Plc has no effect on the direction of Cboe UK i.e., Cboe UK and Helios Towers go up and down completely randomly.
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Pair Corralation between Cboe UK and Helios Towers

Assuming the 90 days trading horizon Cboe UK Consumer is expected to generate 0.53 times more return on investment than Helios Towers. However, Cboe UK Consumer is 1.9 times less risky than Helios Towers. It trades about 0.28 of its potential returns per unit of risk. Helios Towers Plc is currently generating about -0.11 per unit of risk. If you would invest  2,764,966  in Cboe UK Consumer on September 3, 2024 and sell it today you would earn a total of  495,336  from holding Cboe UK Consumer or generate 17.91% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthSignificant
Accuracy100.0%
ValuesDaily Returns

Cboe UK Consumer  vs.  Helios Towers Plc

 Performance 
       Timeline  

Cboe UK and Helios Towers Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Cboe UK and Helios Towers

The main advantage of trading using opposite Cboe UK and Helios Towers positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cboe UK position performs unexpectedly, Helios Towers 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 Helios Towers will offset losses from the drop in Helios Towers' long position.
The idea behind Cboe UK Consumer and Helios Towers Plc 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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.

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