Correlation Between Calvert Global and Fidelity Series
Can any of the company-specific risk be diversified away by investing in both Calvert Global and Fidelity Series 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 Calvert Global and Fidelity Series into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Calvert Global Energy and Fidelity Series 1000, you can compare the effects of market volatilities on Calvert Global and Fidelity Series 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 Calvert Global with a short position of Fidelity Series. Check out your portfolio center. Please also check ongoing floating volatility patterns of Calvert Global and Fidelity Series.
Diversification Opportunities for Calvert Global and Fidelity Series
-0.17 | Correlation Coefficient |
Good diversification
The 3 months correlation between Calvert and Fidelity is -0.17. Overlapping area represents the amount of risk that can be diversified away by holding Calvert Global Energy and Fidelity Series 1000 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fidelity Series 1000 and Calvert 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 Calvert Global Energy are associated (or correlated) with Fidelity Series. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fidelity Series 1000 has no effect on the direction of Calvert Global i.e., Calvert Global and Fidelity Series go up and down completely randomly.
Pair Corralation between Calvert Global and Fidelity Series
Assuming the 90 days horizon Calvert Global is expected to generate 21.64 times less return on investment than Fidelity Series. In addition to that, Calvert Global is 1.38 times more volatile than Fidelity Series 1000. It trades about 0.01 of its total potential returns per unit of risk. Fidelity Series 1000 is currently generating about 0.18 per unit of volatility. If you would invest 1,670 in Fidelity Series 1000 on August 31, 2024 and sell it today you would earn a total of 130.00 from holding Fidelity Series 1000 or generate 7.78% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Calvert Global Energy vs. Fidelity Series 1000
Performance |
Timeline |
Calvert Global Energy |
Fidelity Series 1000 |
Calvert Global and Fidelity Series Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Calvert Global and Fidelity Series
The main advantage of trading using opposite Calvert Global and Fidelity Series positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Calvert Global position performs unexpectedly, Fidelity Series 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 Series will offset losses from the drop in Fidelity Series' long position.Calvert Global vs. Jpmorgan Small Cap | Calvert Global vs. Qs Small Capitalization | Calvert Global vs. Chartwell Small Cap | Calvert Global vs. Vanguard Small Cap Growth |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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