Correlation Between Calamos Global and Fidelity Salem
Can any of the company-specific risk be diversified away by investing in both Calamos Global and Fidelity Salem 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 Fidelity Salem 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 Fidelity Salem Street, you can compare the effects of market volatilities on Calamos Global and Fidelity Salem 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 Fidelity Salem. Check out your portfolio center. Please also check ongoing floating volatility patterns of Calamos Global and Fidelity Salem.
Diversification Opportunities for Calamos Global and Fidelity Salem
-0.22 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Calamos and Fidelity is -0.22. Overlapping area represents the amount of risk that can be diversified away by holding Calamos Global Equity and Fidelity Salem Street in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fidelity Salem Street 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 Fidelity Salem. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fidelity Salem Street has no effect on the direction of Calamos Global i.e., Calamos Global and Fidelity Salem go up and down completely randomly.
Pair Corralation between Calamos Global and Fidelity Salem
Assuming the 90 days horizon Calamos Global Equity is expected to under-perform the Fidelity Salem. In addition to that, Calamos Global is 1.61 times more volatile than Fidelity Salem Street. It trades about -0.08 of its total potential returns per unit of risk. Fidelity Salem Street is currently generating about 0.08 per unit of volatility. If you would invest 1,228 in Fidelity Salem Street on December 30, 2024 and sell it today you would earn a total of 54.00 from holding Fidelity Salem Street or generate 4.4% 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. Fidelity Salem Street
Performance |
Timeline |
Calamos Global Equity |
Fidelity Salem Street |
Calamos Global and Fidelity Salem Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Calamos Global and Fidelity Salem
The main advantage of trading using opposite Calamos Global and Fidelity Salem positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Calamos Global position performs unexpectedly, Fidelity Salem 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 Fidelity Salem will offset losses from the drop in Fidelity Salem's long position.Calamos Global vs. Aqr Long Short Equity | Calamos Global vs. Calvert International Equity | Calamos Global vs. Old Westbury Fixed | Calamos Global vs. Scharf Fund Retail |
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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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