Correlation Between Calamos Global and Dreyfus/standish
Can any of the company-specific risk be diversified away by investing in both Calamos Global and Dreyfus/standish 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 Calamos Global and Dreyfus/standish into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Calamos Global Equity and Dreyfusstandish Global Fixed, you can compare the effects of market volatilities on Calamos Global and Dreyfus/standish 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 Calamos Global with a short position of Dreyfus/standish. Check out your portfolio center. Please also check ongoing floating volatility patterns of Calamos Global and Dreyfus/standish.
Diversification Opportunities for Calamos Global and Dreyfus/standish
-0.27 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Calamos and Dreyfus/standish is -0.27. Overlapping area represents the amount of risk that can be diversified away by holding Calamos Global Equity and Dreyfusstandish Global Fixed in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dreyfusstandish Global and Calamos Global 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 Calamos Global Equity are associated (or correlated) with Dreyfus/standish. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dreyfusstandish Global has no effect on the direction of Calamos Global i.e., Calamos Global and Dreyfus/standish go up and down completely randomly.
Pair Corralation between Calamos Global and Dreyfus/standish
Assuming the 90 days horizon Calamos Global Equity is expected to generate 4.81 times more return on investment than Dreyfus/standish. However, Calamos Global is 4.81 times more volatile than Dreyfusstandish Global Fixed. It trades about 0.06 of its potential returns per unit of risk. Dreyfusstandish Global Fixed is currently generating about -0.03 per unit of risk. If you would invest 1,870 in Calamos Global Equity on August 16, 2024 and sell it today you would earn a total of 68.00 from holding Calamos Global Equity or generate 3.64% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Calamos Global Equity vs. Dreyfusstandish Global Fixed
Performance |
Timeline |
Calamos Global Equity |
Dreyfusstandish Global |
Calamos Global and Dreyfus/standish Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Calamos Global and Dreyfus/standish
The main advantage of trading using opposite Calamos Global and Dreyfus/standish positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Calamos Global position performs unexpectedly, Dreyfus/standish 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 Dreyfus/standish will offset losses from the drop in Dreyfus/standish's long position.Calamos Global vs. Qs International Equity | Calamos Global vs. Gmo Global Equity | Calamos Global vs. The Hartford Equity | Calamos Global vs. Cutler Equity |
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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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