Correlation Between First Trust and BNY Mellon
Can any of the company-specific risk be diversified away by investing in both First Trust 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 First Trust and BNY Mellon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Trust Low and BNY Mellon High, you can compare the effects of market volatilities on First Trust 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 First Trust with a short position of BNY Mellon. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Trust and BNY Mellon.
Diversification Opportunities for First Trust and BNY Mellon
0.25 | Correlation Coefficient |
Modest diversification
The 3 months correlation between First and BNY is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding First Trust Low and BNY Mellon High in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BNY Mellon High and First Trust 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 First Trust Low 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 High has no effect on the direction of First Trust i.e., First Trust and BNY Mellon go up and down completely randomly.
Pair Corralation between First Trust and BNY Mellon
Given the investment horizon of 90 days First Trust is expected to generate 1.9 times less return on investment than BNY Mellon. But when comparing it to its historical volatility, First Trust Low is 2.6 times less risky than BNY Mellon. It trades about 0.11 of its potential returns per unit of risk. BNY Mellon High is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 3,995 in BNY Mellon High on August 26, 2024 and sell it today you would earn a total of 835.00 from holding BNY Mellon High or generate 20.9% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
First Trust Low vs. BNY Mellon High
Performance |
| Timeline |
| First Trust Low |
| BNY Mellon High |
First Trust and BNY Mellon Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with First Trust and BNY Mellon
The main advantage of trading using opposite First Trust and BNY Mellon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Trust 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.| First Trust vs. SPDR Barclays Short | First Trust vs. iShares Agency Bond | First Trust vs. Rbb Fund | First Trust vs. Bondbloxx ETF Trust |
| BNY Mellon vs. First Trust Senior | BNY Mellon vs. First Trust Low | BNY Mellon vs. First Trust Enhanced | BNY Mellon vs. First Trust TCW |
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 Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
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