Correlation Between Sp Midcap and Calamos Vertible
Can any of the company-specific risk be diversified away by investing in both Sp Midcap and Calamos Vertible 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 Sp Midcap and Calamos Vertible into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sp Midcap Index and Calamos Vertible Fund, you can compare the effects of market volatilities on Sp Midcap and Calamos Vertible 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 Sp Midcap with a short position of Calamos Vertible. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sp Midcap and Calamos Vertible.
Diversification Opportunities for Sp Midcap and Calamos Vertible
0.22 | Correlation Coefficient |
Modest diversification
The 3 months correlation between SPMIX and Calamos is 0.22. Overlapping area represents the amount of risk that can be diversified away by holding Sp Midcap Index and Calamos Vertible Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Calamos Vertible and Sp Midcap 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 Sp Midcap Index are associated (or correlated) with Calamos Vertible. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Calamos Vertible has no effect on the direction of Sp Midcap i.e., Sp Midcap and Calamos Vertible go up and down completely randomly.
Pair Corralation between Sp Midcap and Calamos Vertible
Assuming the 90 days horizon Sp Midcap Index is expected to generate 1.27 times more return on investment than Calamos Vertible. However, Sp Midcap is 1.27 times more volatile than Calamos Vertible Fund. It trades about 0.16 of its potential returns per unit of risk. Calamos Vertible Fund is currently generating about 0.13 per unit of risk. If you would invest 2,576 in Sp Midcap Index on November 5, 2024 and sell it today you would earn a total of 67.00 from holding Sp Midcap Index or generate 2.6% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Sp Midcap Index vs. Calamos Vertible Fund
Performance |
| Timeline |
| Sp Midcap Index |
| Calamos Vertible |
Sp Midcap and Calamos Vertible Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Sp Midcap and Calamos Vertible
The main advantage of trading using opposite Sp Midcap and Calamos Vertible positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sp Midcap position performs unexpectedly, Calamos Vertible 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 Calamos Vertible will offset losses from the drop in Calamos Vertible's long position.| Sp Midcap vs. Locorr Market Trend | Sp Midcap vs. Calvert Developed Market | Sp Midcap vs. Ab All Market | Sp Midcap vs. Extended Market Index |
| Calamos Vertible vs. Vy Columbia Small | Calamos Vertible vs. Hunter Small Cap | Calamos Vertible vs. Smallcap Fund Fka | Calamos Vertible vs. Ab Small Cap |
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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