Correlation Between Morgan Stanley and Kellanova
Can any of the company-specific risk be diversified away by investing in both Morgan Stanley and Kellanova 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 Morgan Stanley and Kellanova into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Morgan Stanley Direct and Kellanova, you can compare the effects of market volatilities on Morgan Stanley and Kellanova 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 Morgan Stanley with a short position of Kellanova. Check out your portfolio center. Please also check ongoing floating volatility patterns of Morgan Stanley and Kellanova.
Diversification Opportunities for Morgan Stanley and Kellanova
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Morgan and Kellanova is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Morgan Stanley Direct and Kellanova in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kellanova and Morgan Stanley 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 Morgan Stanley Direct are associated (or correlated) with Kellanova. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kellanova has no effect on the direction of Morgan Stanley i.e., Morgan Stanley and Kellanova go up and down completely randomly.
Pair Corralation between Morgan Stanley and Kellanova
Given the investment horizon of 90 days Morgan Stanley is expected to generate 1.68 times less return on investment than Kellanova. But when comparing it to its historical volatility, Morgan Stanley Direct is 1.27 times less risky than Kellanova. It trades about 0.09 of its potential returns per unit of risk. Kellanova is currently generating about 0.12 of returns per unit of risk over similar time horizon. If you would invest 22,732 in Kellanova on October 15, 2024 and sell it today you would earn a total of 2,079 from holding Kellanova or generate 9.15% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 96.72% |
Values | Daily Returns |
Morgan Stanley Direct vs. Kellanova
Performance |
Timeline |
Morgan Stanley Direct |
Kellanova |
Morgan Stanley and Kellanova Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Morgan Stanley and Kellanova
The main advantage of trading using opposite Morgan Stanley and Kellanova positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Morgan Stanley position performs unexpectedly, Kellanova 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 Kellanova will offset losses from the drop in Kellanova's long position.Morgan Stanley vs. Sun Life Financial | Morgan Stanley vs. Empresa Distribuidora y | Morgan Stanley vs. Cheniere Energy Partners | Morgan Stanley vs. United Utilities Group |
Kellanova vs. Metalrgica Riosulense SA | Kellanova vs. Delta Air Lines | Kellanova vs. Tyson Foods | Kellanova vs. Nordon Indstrias Metalrgicas |
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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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