Correlation Between Franklin Templeton and BNY Mellon
Can any of the company-specific risk be diversified away by investing in both Franklin Templeton 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 Franklin Templeton and BNY Mellon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Franklin Templeton ETF and BNY Mellon Core, you can compare the effects of market volatilities on Franklin Templeton 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 Franklin Templeton with a short position of BNY Mellon. Check out your portfolio center. Please also check ongoing floating volatility patterns of Franklin Templeton and BNY Mellon.
Diversification Opportunities for Franklin Templeton and BNY Mellon
1.0 | Correlation Coefficient |
No risk reduction
The 3 months correlation between Franklin and BNY is 1.0. Overlapping area represents the amount of risk that can be diversified away by holding Franklin Templeton ETF and BNY Mellon Core in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BNY Mellon Core and Franklin Templeton 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 Franklin Templeton ETF 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 Core has no effect on the direction of Franklin Templeton i.e., Franklin Templeton and BNY Mellon go up and down completely randomly.
Pair Corralation between Franklin Templeton and BNY Mellon
Given the investment horizon of 90 days Franklin Templeton is expected to generate 1.01 times less return on investment than BNY Mellon. In addition to that, Franklin Templeton is 1.09 times more volatile than BNY Mellon Core. It trades about 0.05 of its total potential returns per unit of risk. BNY Mellon Core is currently generating about 0.06 per unit of volatility. If you would invest 4,180 in BNY Mellon Core on August 29, 2024 and sell it today you would earn a total of 18.00 from holding BNY Mellon Core or generate 0.43% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Franklin Templeton ETF vs. BNY Mellon Core
Performance |
| Timeline |
| Franklin Templeton ETF |
| BNY Mellon Core |
Franklin Templeton and BNY Mellon Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Franklin Templeton and BNY Mellon
The main advantage of trading using opposite Franklin Templeton and BNY Mellon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Franklin Templeton 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.| Franklin Templeton vs. iShares Agency Bond | Franklin Templeton vs. iShares GNMA Bond | Franklin Templeton vs. iShares JP Morgan | Franklin Templeton vs. iShares Aaa |
| BNY Mellon vs. BNY Mellon Large | BNY Mellon vs. BNY Mellon International | BNY Mellon vs. BNY Mellon High | 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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