Correlation Between First Horizon and Morgan Stanley
Can any of the company-specific risk be diversified away by investing in both First Horizon and Morgan Stanley 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 First Horizon and Morgan Stanley into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Horizon and Morgan Stanley, you can compare the effects of market volatilities on First Horizon and Morgan Stanley 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 First Horizon with a short position of Morgan Stanley. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Horizon and Morgan Stanley.
Diversification Opportunities for First Horizon and Morgan Stanley
0.58 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between First and Morgan is 0.58. Overlapping area represents the amount of risk that can be diversified away by holding First Horizon and Morgan Stanley in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Morgan Stanley and First Horizon 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 First Horizon are associated (or correlated) with Morgan Stanley. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Morgan Stanley has no effect on the direction of First Horizon i.e., First Horizon and Morgan Stanley go up and down completely randomly.
Pair Corralation between First Horizon and Morgan Stanley
Assuming the 90 days trading horizon First Horizon is expected to generate 1.58 times less return on investment than Morgan Stanley. In addition to that, First Horizon is 1.43 times more volatile than Morgan Stanley. It trades about 0.03 of its total potential returns per unit of risk. Morgan Stanley is currently generating about 0.06 per unit of volatility. If you would invest 2,527 in Morgan Stanley on September 5, 2024 and sell it today you would earn a total of 87.00 from holding Morgan Stanley or generate 3.44% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
First Horizon vs. Morgan Stanley
Performance |
| Timeline |
| First Horizon |
| Morgan Stanley |
First Horizon and Morgan Stanley Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with First Horizon and Morgan Stanley
The main advantage of trading using opposite First Horizon and Morgan Stanley positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Horizon position performs unexpectedly, Morgan Stanley 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 Morgan Stanley will offset losses from the drop in Morgan Stanley's long position.| First Horizon vs. First Horizon | First Horizon vs. First Horizon | First Horizon vs. Citizens Financial Group | First Horizon vs. Customers Bancorp |
| Morgan Stanley vs. Morgan Stanley | Morgan Stanley vs. Morgan Stanley | Morgan Stanley vs. KeyCorp | Morgan Stanley vs. Bank of America |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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