Correlation Between NYSE Composite and BNY Mellon
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and BNY Mellon 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 BNY Mellon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and BNY Mellon ETF, you can compare the effects of market volatilities on NYSE Composite and BNY Mellon 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 BNY Mellon. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and BNY Mellon.
Diversification Opportunities for NYSE Composite and BNY Mellon
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between NYSE and BNY is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and BNY Mellon ETF in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BNY Mellon ETF 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 BNY Mellon. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BNY Mellon ETF has no effect on the direction of NYSE Composite i.e., NYSE Composite and BNY Mellon go up and down completely randomly.
Pair Corralation between NYSE Composite and BNY Mellon
Assuming the 90 days trading horizon NYSE Composite is expected to generate 1.84 times less return on investment than BNY Mellon. But when comparing it to its historical volatility, NYSE Composite is 2.36 times less risky than BNY Mellon. It trades about 0.42 of its potential returns per unit of risk. BNY Mellon ETF is currently generating about 0.33 of returns per unit of risk over similar time horizon. If you would invest 9,957 in BNY Mellon ETF on September 1, 2024 and sell it today you would earn a total of 1,042 from holding BNY Mellon ETF or generate 10.46% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 95.45% |
| Values | Daily Returns |
NYSE Composite vs. BNY Mellon ETF
Performance |
| Timeline |
NYSE Composite and BNY Mellon Volatility Contrast
Predicted Return Density |
| Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
BNY Mellon ETF
Pair trading matchups for BNY Mellon
Pair Trading with NYSE Composite and BNY Mellon
The main advantage of trading using opposite NYSE Composite and BNY Mellon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, BNY Mellon 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 BNY Mellon will offset losses from the drop in BNY Mellon's long position.| NYSE Composite vs. Acumen Pharmaceuticals | NYSE Composite vs. Mind Medicine | NYSE Composite vs. NL Industries | NYSE Composite vs. Ecovyst |
| BNY Mellon vs. BNY Mellon Mid | BNY Mellon vs. BNY Mellon International | BNY Mellon vs. BNY Mellon Large | BNY Mellon vs. BNY Mellon ETF |
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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