Correlation Between BNY Mellon and BNY Mellon
Can any of the company-specific risk be diversified away by investing in both BNY Mellon 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 BNY Mellon and BNY Mellon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BNY Mellon International and BNY Mellon ETF, you can compare the effects of market volatilities on BNY Mellon 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 BNY Mellon with a short position of BNY Mellon. Check out your portfolio center. Please also check ongoing floating volatility patterns of BNY Mellon and BNY Mellon.
Diversification Opportunities for BNY Mellon and BNY Mellon
0.35 | Correlation Coefficient |
Weak diversification
The 3 months correlation between BNY and BNY is 0.35. Overlapping area represents the amount of risk that can be diversified away by holding BNY Mellon International 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 BNY Mellon 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 BNY Mellon International 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 BNY Mellon i.e., BNY Mellon and BNY Mellon go up and down completely randomly.
Pair Corralation between BNY Mellon and BNY Mellon
Given the investment horizon of 90 days BNY Mellon is expected to generate 1.81 times less return on investment than BNY Mellon. But when comparing it to its historical volatility, BNY Mellon International is 1.45 times less risky than BNY Mellon. It trades about 0.05 of its potential returns per unit of risk. BNY Mellon ETF is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 8,806 in BNY Mellon ETF on November 3, 2024 and sell it today you would earn a total of 1,608 from holding BNY Mellon ETF or generate 18.25% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
BNY Mellon International vs. BNY Mellon ETF
Performance |
| Timeline |
| BNY Mellon International |
| BNY Mellon ETF |
BNY Mellon and BNY Mellon Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BNY Mellon and BNY Mellon
The main advantage of trading using opposite BNY Mellon and BNY Mellon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BNY Mellon 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.| BNY Mellon vs. BNY Mellon ETF | BNY Mellon vs. BNY Mellon Large | BNY Mellon vs. BNY Mellon Mid | BNY Mellon vs. BNY Mellon High |
| 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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