Correlation Between NYSE Composite and Fidelity Summer
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Fidelity Summer 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 NYSE Composite and Fidelity Summer into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Fidelity Summer Street, you can compare the effects of market volatilities on NYSE Composite and Fidelity Summer 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 NYSE Composite with a short position of Fidelity Summer. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Fidelity Summer.
Diversification Opportunities for NYSE Composite and Fidelity Summer
0.54 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between NYSE and Fidelity is 0.54. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Fidelity Summer Street in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fidelity Summer Street and NYSE Composite 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 NYSE Composite are associated (or correlated) with Fidelity Summer. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fidelity Summer Street has no effect on the direction of NYSE Composite i.e., NYSE Composite and Fidelity Summer go up and down completely randomly.
Pair Corralation between NYSE Composite and Fidelity Summer
Assuming the 90 days trading horizon NYSE Composite is expected to generate 0.73 times more return on investment than Fidelity Summer. However, NYSE Composite is 1.36 times less risky than Fidelity Summer. It trades about 0.08 of its potential returns per unit of risk. Fidelity Summer Street is currently generating about 0.03 per unit of risk. If you would invest 1,529,105 in NYSE Composite on August 30, 2024 and sell it today you would earn a total of 491,877 from holding NYSE Composite or generate 32.17% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 27.47% |
| Values | Daily Returns |
NYSE Composite vs. Fidelity Summer Street
Performance |
| Timeline |
NYSE Composite and Fidelity Summer Volatility Contrast
Predicted Return Density |
| Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
Pair Trading with NYSE Composite and Fidelity Summer
The main advantage of trading using opposite NYSE Composite and Fidelity Summer positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Fidelity Summer 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 Summer will offset losses from the drop in Fidelity Summer's long position.| NYSE Composite vs. Sphere Entertainment Co | NYSE Composite vs. Weibo Corp | NYSE Composite vs. BCE Inc | NYSE Composite vs. Pinterest |
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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