Correlation Between Cboe UK and Public Service

Can any of the company-specific risk be diversified away by investing in both Cboe UK and Public Service 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 Public Service 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 Public Service Enterprise, you can compare the effects of market volatilities on Cboe UK and Public Service 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 Public Service. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cboe UK and Public Service.

Diversification Opportunities for Cboe UK and Public Service

0.12

Correlation Coefficient

Cboe UK  Public Service

Average diversification

The 3 months correlation between Cboe and Public is 0.12. Overlapping area represents the amount of risk that can be diversified away by holding Cboe UK Consumer and Public Service Enterprise in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Public Service Enterprise 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 Public Service. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Public Service Enterprise has no effect on the direction of Cboe UK i.e., Cboe UK and Public Service go up and down completely randomly.

Pair Corralation between Cboe UK and Public Service

Assuming the 90 days trading horizon Cboe UK Consumer is expected to generate 0.69 times more return on investment than Public Service. However, Cboe UK Consumer is 1.45 times less risky than Public Service. It trades about 0.19 of its potential returns per unit of risk. Public Service Enterprise is currently generating about -0.03 per unit of risk. If you would invest  2,867,072  in Cboe UK Consumer on September 23, 2024 and sell it today you would earn a total of  348,574  from holding Cboe UK Consumer or generate 12.16% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Insignificant
Accuracy	98.48%
Values	Daily Returns

Cboe UK Consumer  vs.  Public Service Enterprise

Pair Trading with Cboe UK and Public Service

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

The idea behind Cboe UK Consumer and Public Service Enterprise 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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.