Correlation Between Cboe UK and General Motors

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

Diversification Opportunities for Cboe UK and General Motors

0.69

Correlation Coefficient

Cboe UK  General Motors

Poor diversification

The 3 months correlation between Cboe and General is 0.69. Overlapping area represents the amount of risk that can be diversified away by holding Cboe UK Consumer and General Motors Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on General Motors 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 General Motors. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of General Motors has no effect on the direction of Cboe UK i.e., Cboe UK and General Motors go up and down completely randomly.

Pair Corralation between Cboe UK and General Motors

Assuming the 90 days trading horizon Cboe UK is expected to generate 1.67 times less return on investment than General Motors. But when comparing it to its historical volatility, Cboe UK Consumer is 2.21 times less risky than General Motors. It trades about 0.13 of its potential returns per unit of risk. General Motors Co is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest  3,286  in General Motors Co on September 27, 2024 and sell it today you would earn a total of  1,984  from holding General Motors Co or generate 60.38% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Significant
Accuracy	97.44%
Values	Daily Returns

Cboe UK Consumer  vs.  General Motors Co

Pair Trading with Cboe UK and General Motors

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

The idea behind Cboe UK Consumer and General Motors Co 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.