Correlation Between Dow Jones and Fidelity Municipal
Can any of the company-specific risk be diversified away by investing in both Dow Jones and Fidelity Municipal 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 Dow Jones and Fidelity Municipal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dow Jones Industrial and Fidelity Municipal Income, you can compare the effects of market volatilities on Dow Jones and Fidelity Municipal 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 Dow Jones with a short position of Fidelity Municipal. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and Fidelity Municipal.
Diversification Opportunities for Dow Jones and Fidelity Municipal
0.55 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Dow and Fidelity is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Fidelity Municipal Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fidelity Municipal Income and Dow Jones 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 Dow Jones Industrial are associated (or correlated) with Fidelity Municipal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fidelity Municipal Income has no effect on the direction of Dow Jones i.e., Dow Jones and Fidelity Municipal go up and down completely randomly.
Pair Corralation between Dow Jones and Fidelity Municipal
Assuming the 90 days trading horizon Dow Jones Industrial is expected to under-perform the Fidelity Municipal. In addition to that, Dow Jones is 9.85 times more volatile than Fidelity Municipal Income. It trades about -0.2 of its total potential returns per unit of risk. Fidelity Municipal Income is currently generating about 0.2 per unit of volatility. If you would invest 997.00 in Fidelity Municipal Income on September 28, 2024 and sell it today you would earn a total of 3.00 from holding Fidelity Municipal Income or generate 0.3% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 95.24% |
Values | Daily Returns |
Dow Jones Industrial vs. Fidelity Municipal Income
Performance |
Timeline |
Dow Jones and Fidelity Municipal Volatility Contrast
Predicted Return Density |
Returns |
Dow Jones Industrial
Pair trading matchups for Dow Jones
Fidelity Municipal Income
Pair trading matchups for Fidelity Municipal
Pair Trading with Dow Jones and Fidelity Municipal
The main advantage of trading using opposite Dow Jones and Fidelity Municipal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, Fidelity Municipal 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 Municipal will offset losses from the drop in Fidelity Municipal's long position.Dow Jones vs. Copa Holdings SA | Dow Jones vs. Delta Air Lines | Dow Jones vs. Azul SA | Dow Jones vs. SkyWest |
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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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