Correlation Between Fidelity Series and Nationwide Bond
Can any of the company-specific risk be diversified away by investing in both Fidelity Series and Nationwide Bond 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 Fidelity Series and Nationwide Bond into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fidelity Series 1000 and Nationwide Bond Fund, you can compare the effects of market volatilities on Fidelity Series and Nationwide Bond 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 Fidelity Series with a short position of Nationwide Bond. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fidelity Series and Nationwide Bond.
Diversification Opportunities for Fidelity Series and Nationwide Bond
-0.67 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Fidelity and Nationwide is -0.67. Overlapping area represents the amount of risk that can be diversified away by holding Fidelity Series 1000 and Nationwide Bond Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nationwide Bond and Fidelity Series 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 Fidelity Series 1000 are associated (or correlated) with Nationwide Bond. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nationwide Bond has no effect on the direction of Fidelity Series i.e., Fidelity Series and Nationwide Bond go up and down completely randomly.
Pair Corralation between Fidelity Series and Nationwide Bond
Assuming the 90 days horizon Fidelity Series 1000 is expected to generate 2.22 times more return on investment than Nationwide Bond. However, Fidelity Series is 2.22 times more volatile than Nationwide Bond Fund. It trades about 0.35 of its potential returns per unit of risk. Nationwide Bond Fund is currently generating about 0.1 per unit of risk. If you would invest 1,694 in Fidelity Series 1000 on September 4, 2024 and sell it today you would earn a total of 100.00 from holding Fidelity Series 1000 or generate 5.9% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 95.24% |
Values | Daily Returns |
Fidelity Series 1000 vs. Nationwide Bond Fund
Performance |
Timeline |
Fidelity Series 1000 |
Nationwide Bond |
Fidelity Series and Nationwide Bond Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Fidelity Series and Nationwide Bond
The main advantage of trading using opposite Fidelity Series and Nationwide Bond positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fidelity Series position performs unexpectedly, Nationwide Bond 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 Nationwide Bond will offset losses from the drop in Nationwide Bond's long position.Fidelity Series vs. Fidelity Freedom 2015 | Fidelity Series vs. Fidelity Puritan Fund | Fidelity Series vs. Fidelity Puritan Fund | Fidelity Series vs. Fidelity Pennsylvania Municipal |
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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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