Correlation Between Cboe UK and Kellogg
Specify exactly 2 symbols:
By analyzing existing cross correlation between Cboe UK Consumer and Kellogg Co, you can compare the effects of market volatilities on Cboe UK and Kellogg 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 Kellogg. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cboe UK and Kellogg.
Diversification Opportunities for Cboe UK and Kellogg
Very weak diversification
The 3 months correlation between Cboe and Kellogg is 0.45. Overlapping area represents the amount of risk that can be diversified away by holding Cboe UK Consumer and Kellogg Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kellogg 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 Kellogg. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kellogg has no effect on the direction of Cboe UK i.e., Cboe UK and Kellogg go up and down completely randomly.
Pair Corralation between Cboe UK and Kellogg
Assuming the 90 days trading horizon Cboe UK Consumer is expected to generate 4.4 times more return on investment than Kellogg. However, Cboe UK is 4.4 times more volatile than Kellogg Co. It trades about 0.25 of its potential returns per unit of risk. Kellogg Co is currently generating about 0.08 per unit of risk. If you would invest 2,835,223 in Cboe UK Consumer on September 12, 2024 and sell it today you would earn a total of 444,695 from holding Cboe UK Consumer or generate 15.68% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Cboe UK Consumer vs. Kellogg Co
Performance |
Timeline |
Cboe UK and Kellogg Volatility Contrast
Predicted Return Density |
Returns |
Cboe UK Consumer
Pair trading matchups for Cboe UK
Kellogg Co
Pair trading matchups for Kellogg
Pair Trading with Cboe UK and Kellogg
The main advantage of trading using opposite Cboe UK and Kellogg positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cboe UK position performs unexpectedly, Kellogg 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 Kellogg will offset losses from the drop in Kellogg's long position.Cboe UK vs. Tata Steel Limited | Cboe UK vs. Vitec Software Group | Cboe UK vs. Wyndham Hotels Resorts | Cboe UK vs. Impax Environmental Markets |
Kellogg vs. Monks Investment Trust | Kellogg vs. Bankers Investment Trust | Kellogg vs. Federal Realty Investment | Kellogg vs. McEwen Mining |
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 Share Portfolio module to track or share privately all of your investments from the convenience of any device.
Other Complementary Tools
Competition Analyzer Analyze and compare many basic indicators for a group of related or unrelated entities | |
Cryptocurrency Center Build and monitor diversified portfolio of extremely risky digital assets and cryptocurrency | |
Idea Analyzer Analyze all characteristics, volatility and risk-adjusted return of Macroaxis ideas | |
Portfolio Center All portfolio management and optimization tools to improve performance of your portfolios | |
Headlines Timeline Stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity |