Correlation Between Deutsche Bank and Morgan Stanley
Can any of the company-specific risk be diversified away by investing in both Deutsche Bank 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 Deutsche Bank and Morgan Stanley into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Deutsche Bank Aktiengesellschaft and Morgan Stanley, you can compare the effects of market volatilities on Deutsche Bank 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 Deutsche Bank with a short position of Morgan Stanley. Check out your portfolio center. Please also check ongoing floating volatility patterns of Deutsche Bank and Morgan Stanley.
Diversification Opportunities for Deutsche Bank and Morgan Stanley
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Deutsche and Morgan is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding Deutsche Bank Aktiengesellscha and Morgan Stanley in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Morgan Stanley and Deutsche Bank 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 Deutsche Bank Aktiengesellschaft 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 Deutsche Bank i.e., Deutsche Bank and Morgan Stanley go up and down completely randomly.
Pair Corralation between Deutsche Bank and Morgan Stanley
Assuming the 90 days trading horizon Deutsche Bank is expected to generate 3.17 times less return on investment than Morgan Stanley. But when comparing it to its historical volatility, Deutsche Bank Aktiengesellschaft is 1.49 times less risky than Morgan Stanley. It trades about 0.12 of its potential returns per unit of risk. Morgan Stanley is currently generating about 0.25 of returns per unit of risk over similar time horizon. If you would invest 13,454 in Morgan Stanley on September 4, 2024 and sell it today you would earn a total of 2,247 from holding Morgan Stanley or generate 16.7% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Deutsche Bank Aktiengesellscha vs. Morgan Stanley
Performance |
Timeline |
Deutsche Bank Aktien |
Morgan Stanley |
Deutsche Bank and Morgan Stanley Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Deutsche Bank and Morgan Stanley
The main advantage of trading using opposite Deutsche Bank and Morgan Stanley positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Deutsche Bank 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.Deutsche Bank vs. Ita Unibanco Holding | Deutsche Bank vs. Ita Unibanco Holding | Deutsche Bank vs. Banco Bradesco SA | Deutsche Bank vs. Itasa Investimentos |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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