Correlation Between Morgan Stanley and Exel Composites
Can any of the company-specific risk be diversified away by investing in both Morgan Stanley and Exel Composites 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 Exel Composites 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 Exel Composites Oyj, you can compare the effects of market volatilities on Morgan Stanley and Exel Composites 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 Exel Composites. Check out your portfolio center. Please also check ongoing floating volatility patterns of Morgan Stanley and Exel Composites.
Diversification Opportunities for Morgan Stanley and Exel Composites
0.04 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Morgan and Exel is 0.04. Overlapping area represents the amount of risk that can be diversified away by holding Morgan Stanley Direct and Exel Composites Oyj in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Exel Composites Oyj 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 Exel Composites. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Exel Composites Oyj has no effect on the direction of Morgan Stanley i.e., Morgan Stanley and Exel Composites go up and down completely randomly.
Pair Corralation between Morgan Stanley and Exel Composites
Given the investment horizon of 90 days Morgan Stanley Direct is expected to under-perform the Exel Composites. But the stock apears to be less risky and, when comparing its historical volatility, Morgan Stanley Direct is 2.86 times less risky than Exel Composites. The stock trades about -0.03 of its potential returns per unit of risk. The Exel Composites Oyj is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 33.00 in Exel Composites Oyj on December 4, 2024 and sell it today you would earn a total of 3.00 from holding Exel Composites Oyj or generate 9.09% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 96.61% |
Values | Daily Returns |
Morgan Stanley Direct vs. Exel Composites Oyj
Performance |
Timeline |
Morgan Stanley Direct |
Exel Composites Oyj |
Morgan Stanley and Exel Composites Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Morgan Stanley and Exel Composites
The main advantage of trading using opposite Morgan Stanley and Exel Composites positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Morgan Stanley position performs unexpectedly, Exel Composites 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 Exel Composites will offset losses from the drop in Exel Composites' long position.Morgan Stanley vs. WPP PLC ADR | Morgan Stanley vs. Townsquare Media | Morgan Stanley vs. CenterPoint Energy | Morgan Stanley vs. ZW Data Action |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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