Correlation Between Bny Mellon and Dreyfus Strategic
Can any of the company-specific risk be diversified away by investing in both Bny Mellon and Dreyfus Strategic 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 Dreyfus Strategic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bny Mellon Short and Dreyfus Strategic Value, you can compare the effects of market volatilities on Bny Mellon and Dreyfus Strategic 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 Dreyfus Strategic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bny Mellon and Dreyfus Strategic.
Diversification Opportunities for Bny Mellon and Dreyfus Strategic
-0.35 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Bny and Dreyfus is -0.35. Overlapping area represents the amount of risk that can be diversified away by holding Bny Mellon Short and Dreyfus Strategic Value in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dreyfus Strategic Value 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 Short are associated (or correlated) with Dreyfus Strategic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dreyfus Strategic Value has no effect on the direction of Bny Mellon i.e., Bny Mellon and Dreyfus Strategic go up and down completely randomly.
Pair Corralation between Bny Mellon and Dreyfus Strategic
Assuming the 90 days horizon Bny Mellon is expected to generate 3.34 times less return on investment than Dreyfus Strategic. But when comparing it to its historical volatility, Bny Mellon Short is 4.16 times less risky than Dreyfus Strategic. It trades about 0.12 of its potential returns per unit of risk. Dreyfus Strategic Value is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest 3,713 in Dreyfus Strategic Value on August 31, 2024 and sell it today you would earn a total of 1,384 from holding Dreyfus Strategic Value or generate 37.27% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bny Mellon Short vs. Dreyfus Strategic Value
Performance |
| Timeline |
| Bny Mellon Short |
| Dreyfus Strategic Value |
Bny Mellon and Dreyfus Strategic Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bny Mellon and Dreyfus Strategic
The main advantage of trading using opposite Bny Mellon and Dreyfus Strategic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bny Mellon position performs unexpectedly, Dreyfus Strategic 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 Dreyfus Strategic will offset losses from the drop in Dreyfus Strategic's long position.| Bny Mellon vs. Precious Metals And | Bny Mellon vs. International Investors Gold | Bny Mellon vs. International Investors Gold | Bny Mellon vs. James Balanced Golden |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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