Correlation Between Cboe UK and Kosdaq Composite

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

Diversification Opportunities for Cboe UK and Kosdaq Composite

-0.76

Correlation Coefficient

Cboe UK  Kosdaq Composite

Pay attention - limited upside

The 3 months correlation between Cboe and Kosdaq is -0.76. Overlapping area represents the amount of risk that can be diversified away by holding Cboe UK Consumer and Kosdaq Composite Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kosdaq Composite Index 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 Kosdaq Composite. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kosdaq Composite Index has no effect on the direction of Cboe UK i.e., Cboe UK and Kosdaq Composite go up and down completely randomly.

Pair Corralation between Cboe UK and Kosdaq Composite

Assuming the 90 days trading horizon Cboe UK Consumer is expected to generate 0.63 times more return on investment than Kosdaq Composite. However, Cboe UK Consumer is 1.59 times less risky than Kosdaq Composite. It trades about 0.28 of its potential returns per unit of risk. Kosdaq Composite Index is currently generating about -0.11 per unit of risk. If you would invest  2,771,134  in Cboe UK Consumer on August 30, 2024 and sell it today you would earn a total of  490,113  from holding Cboe UK Consumer or generate 17.69% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Weak
Accuracy	92.19%
Values	Daily Returns

Cboe UK Consumer  vs.  Kosdaq Composite Index

Pair Trading with Cboe UK and Kosdaq Composite

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

The idea behind Cboe UK Consumer and Kosdaq Composite Index 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.

Check out your portfolio center.

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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.