Correlation Between Cref Inflation and Credit Suisse
Can any of the company-specific risk be diversified away by investing in both Cref Inflation and Credit Suisse 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 Cref Inflation and Credit Suisse into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cref Inflation Linked Bond and Credit Suisse Modity, you can compare the effects of market volatilities on Cref Inflation and Credit Suisse 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 Cref Inflation with a short position of Credit Suisse. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cref Inflation and Credit Suisse.
Diversification Opportunities for Cref Inflation and Credit Suisse
-0.09 | Correlation Coefficient |
Good diversification
The 3 months correlation between Cref and Credit is -0.09. Overlapping area represents the amount of risk that can be diversified away by holding Cref Inflation Linked Bond and Credit Suisse Modity in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Credit Suisse Modity and Cref Inflation 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 Cref Inflation Linked Bond are associated (or correlated) with Credit Suisse. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Credit Suisse Modity has no effect on the direction of Cref Inflation i.e., Cref Inflation and Credit Suisse go up and down completely randomly.
Pair Corralation between Cref Inflation and Credit Suisse
Assuming the 90 days trading horizon Cref Inflation Linked Bond is expected to generate 0.23 times more return on investment than Credit Suisse. However, Cref Inflation Linked Bond is 4.28 times less risky than Credit Suisse. It trades about 0.19 of its potential returns per unit of risk. Credit Suisse Modity is currently generating about 0.01 per unit of risk. If you would invest 8,785 in Cref Inflation Linked Bond on May 18, 2025 and sell it today you would earn a total of 186.00 from holding Cref Inflation Linked Bond or generate 2.12% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Cref Inflation Linked Bond vs. Credit Suisse Modity
Performance |
Timeline |
Cref Inflation Linked |
Credit Suisse Modity |
Cref Inflation and Credit Suisse Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cref Inflation and Credit Suisse
The main advantage of trading using opposite Cref Inflation and Credit Suisse positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cref Inflation position performs unexpectedly, Credit Suisse 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 Credit Suisse will offset losses from the drop in Credit Suisse's long position.Cref Inflation vs. Thornburg Limited Term | Cref Inflation vs. Loomis Sayles Limited | Cref Inflation vs. Us Government Securities | Cref Inflation vs. Jpmorgan Government Bond |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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