Correlation Between Federated Ohio and Calamos Short-term
Can any of the company-specific risk be diversified away by investing in both Federated Ohio and Calamos Short-term 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 Federated Ohio and Calamos Short-term into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Federated Ohio Municipal and Calamos Short Term Bond, you can compare the effects of market volatilities on Federated Ohio and Calamos Short-term 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 Federated Ohio with a short position of Calamos Short-term. Check out your portfolio center. Please also check ongoing floating volatility patterns of Federated Ohio and Calamos Short-term.
Diversification Opportunities for Federated Ohio and Calamos Short-term
0.25 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Federated and Calamos is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding Federated Ohio Municipal and Calamos Short Term Bond in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Calamos Short Term and Federated Ohio 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 Federated Ohio Municipal are associated (or correlated) with Calamos Short-term. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Calamos Short Term has no effect on the direction of Federated Ohio i.e., Federated Ohio and Calamos Short-term go up and down completely randomly.
Pair Corralation between Federated Ohio and Calamos Short-term
Assuming the 90 days horizon Federated Ohio Municipal is expected to under-perform the Calamos Short-term. In addition to that, Federated Ohio is 1.78 times more volatile than Calamos Short Term Bond. It trades about -0.01 of its total potential returns per unit of risk. Calamos Short Term Bond is currently generating about 0.14 per unit of volatility. If you would invest 940.00 in Calamos Short Term Bond on November 20, 2024 and sell it today you would earn a total of 11.00 from holding Calamos Short Term Bond or generate 1.17% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Federated Ohio Municipal vs. Calamos Short Term Bond
Performance |
Timeline |
Federated Ohio Municipal |
Calamos Short Term |
Federated Ohio and Calamos Short-term Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Federated Ohio and Calamos Short-term
The main advantage of trading using opposite Federated Ohio and Calamos Short-term positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Federated Ohio position performs unexpectedly, Calamos Short-term 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 Short-term will offset losses from the drop in Calamos Short-term's long position.Federated Ohio vs. Federated Emerging Market | Federated Ohio vs. Federated Mdt All | Federated Ohio vs. Federated Mdt Balanced | Federated Ohio vs. Federated Global Allocation |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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