Correlation Between Credit Suisse and Mfs Intermediate
Can any of the company-specific risk be diversified away by investing in both Credit Suisse and Mfs Intermediate 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 Credit Suisse and Mfs Intermediate into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Credit Suisse High and Mfs Intermediate High, you can compare the effects of market volatilities on Credit Suisse and Mfs Intermediate 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 Credit Suisse with a short position of Mfs Intermediate. Check out your portfolio center. Please also check ongoing floating volatility patterns of Credit Suisse and Mfs Intermediate.
Diversification Opportunities for Credit Suisse and Mfs Intermediate
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Credit and Mfs is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding Credit Suisse High and Mfs Intermediate High in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Intermediate High and Credit Suisse 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 Credit Suisse High are associated (or correlated) with Mfs Intermediate. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Intermediate High has no effect on the direction of Credit Suisse i.e., Credit Suisse and Mfs Intermediate go up and down completely randomly.
Pair Corralation between Credit Suisse and Mfs Intermediate
Considering the 90-day investment horizon Credit Suisse is expected to generate 1.2 times less return on investment than Mfs Intermediate. In addition to that, Credit Suisse is 1.15 times more volatile than Mfs Intermediate High. It trades about 0.03 of its total potential returns per unit of risk. Mfs Intermediate High is currently generating about 0.04 per unit of volatility. If you would invest 168.00 in Mfs Intermediate High on December 27, 2024 and sell it today you would earn a total of 2.00 from holding Mfs Intermediate High or generate 1.19% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Credit Suisse High vs. Mfs Intermediate High
Performance |
Timeline |
Credit Suisse High |
Mfs Intermediate High |
Credit Suisse and Mfs Intermediate Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Credit Suisse and Mfs Intermediate
The main advantage of trading using opposite Credit Suisse and Mfs Intermediate positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Credit Suisse position performs unexpectedly, Mfs Intermediate 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 Mfs Intermediate will offset losses from the drop in Mfs Intermediate's long position.Credit Suisse vs. Bny Mellon Municipalome | Credit Suisse vs. BNY Mellon High | Credit Suisse vs. Western Asset Global | Credit Suisse vs. Mfs Intermediate High |
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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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