Correlation Between Credit Suisse and Ppm High
Can any of the company-specific risk be diversified away by investing in both Credit Suisse and Ppm High 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 Ppm High into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Credit Suisse Floating and Ppm High Yield, you can compare the effects of market volatilities on Credit Suisse and Ppm High 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 Ppm High. Check out your portfolio center. Please also check ongoing floating volatility patterns of Credit Suisse and Ppm High.
Diversification Opportunities for Credit Suisse and Ppm High
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Credit and Ppm is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Credit Suisse Floating and Ppm High Yield in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ppm High Yield 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 Floating are associated (or correlated) with Ppm High. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ppm High Yield has no effect on the direction of Credit Suisse i.e., Credit Suisse and Ppm High go up and down completely randomly.
Pair Corralation between Credit Suisse and Ppm High
Assuming the 90 days horizon Credit Suisse Floating is expected to generate 0.63 times more return on investment than Ppm High. However, Credit Suisse Floating is 1.59 times less risky than Ppm High. It trades about 0.21 of its potential returns per unit of risk. Ppm High Yield is currently generating about 0.12 per unit of risk. If you would invest 526.00 in Credit Suisse Floating on September 4, 2024 and sell it today you would earn a total of 111.00 from holding Credit Suisse Floating or generate 21.1% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Credit Suisse Floating vs. Ppm High Yield
Performance |
| Timeline |
| Credit Suisse Floating |
| Ppm High Yield |
Credit Suisse and Ppm High Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Credit Suisse and Ppm High
The main advantage of trading using opposite Credit Suisse and Ppm High positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Credit Suisse position performs unexpectedly, Ppm High 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 Ppm High will offset losses from the drop in Ppm High's long position.| Credit Suisse vs. Franklin High Yield | Credit Suisse vs. Nuveen Minnesota Municipal | Credit Suisse vs. T Rowe Price | Credit Suisse vs. T Rowe Price |
| Ppm High vs. Ppm Core Plus | Ppm High vs. Fidelity Advisor Industrials | Ppm High vs. Blackrock Resources Commodities | Ppm High vs. Small Cap Equity |
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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