Correlation Between BioNTech and Bank of New York
Can any of the company-specific risk be diversified away by investing in both BioNTech and Bank of New York 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 BioNTech and Bank of New York into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BioNTech SE and Bank of New, you can compare the effects of market volatilities on BioNTech and Bank of New York 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 BioNTech with a short position of Bank of New York. Check out your portfolio center. Please also check ongoing floating volatility patterns of BioNTech and Bank of New York.
Diversification Opportunities for BioNTech and Bank of New York
0.36 | Correlation Coefficient |
Weak diversification
The 3 months correlation between BioNTech and Bank is 0.36. Overlapping area represents the amount of risk that can be diversified away by holding BioNTech SE and Bank of New in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank of New York and BioNTech 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 BioNTech SE are associated (or correlated) with Bank of New York. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank of New York has no effect on the direction of BioNTech i.e., BioNTech and Bank of New York go up and down completely randomly.
Pair Corralation between BioNTech and Bank of New York
Given the investment horizon of 90 days BioNTech is expected to generate 1.41 times less return on investment than Bank of New York. In addition to that, BioNTech is 3.5 times more volatile than Bank of New. It trades about 0.08 of its total potential returns per unit of risk. Bank of New is currently generating about 0.38 per unit of volatility. If you would invest 7,536 in Bank of New on September 1, 2024 and sell it today you would earn a total of 651.00 from holding Bank of New or generate 8.64% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
BioNTech SE vs. Bank of New
Performance |
| Timeline |
| BioNTech SE |
| Bank of New York |
BioNTech and Bank of New York Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BioNTech and Bank of New York
The main advantage of trading using opposite BioNTech and Bank of New York positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BioNTech position performs unexpectedly, Bank of New York 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 Bank of New York will offset losses from the drop in Bank of New York's long position.| BioNTech vs. Novavax | BioNTech vs. Ginkgo Bioworks Holdings | BioNTech vs. Crispr Therapeutics AG | BioNTech vs. Ocean Biomedical |
| Bank of New York vs. Northern Trust | Bank of New York vs. Invesco Plc | Bank of New York vs. Franklin Resources | Bank of New York vs. T Rowe Price |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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