Correlation Between Bank of America and Schwab Us
Can any of the company-specific risk be diversified away by investing in both Bank of America and Schwab Us 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 Bank of America and Schwab Us into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank of America and Schwab Treasury Money, you can compare the effects of market volatilities on Bank of America and Schwab Us 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 Bank of America with a short position of Schwab Us. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of America and Schwab Us.
Diversification Opportunities for Bank of America and Schwab Us
0.47 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Bank and Schwab is 0.47. Overlapping area represents the amount of risk that can be diversified away by holding Bank of America and Schwab Treasury Money in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Schwab Treasury Money and Bank of America 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 Bank of America are associated (or correlated) with Schwab Us. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Schwab Treasury Money has no effect on the direction of Bank of America i.e., Bank of America and Schwab Us go up and down completely randomly.
Pair Corralation between Bank of America and Schwab Us
Considering the 90-day investment horizon Bank of America is expected to generate 5.55 times more return on investment than Schwab Us. However, Bank of America is 5.55 times more volatile than Schwab Treasury Money. It trades about 0.12 of its potential returns per unit of risk. Schwab Treasury Money is currently generating about 0.06 per unit of risk. If you would invest 3,815 in Bank of America on August 28, 2024 and sell it today you would earn a total of 935.00 from holding Bank of America or generate 24.51% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 98.43% |
| Values | Daily Returns |
Bank of America vs. Schwab Treasury Money
Performance |
| Timeline |
| Bank of America |
| Schwab Treasury Money |
Bank of America and Schwab Us Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of America and Schwab Us
The main advantage of trading using opposite Bank of America and Schwab Us positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of America position performs unexpectedly, Schwab Us 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 Schwab Us will offset losses from the drop in Schwab Us' long position.| Bank of America vs. Nu Holdings | Bank of America vs. HSBC Holdings PLC | Bank of America vs. Bank of Montreal | Bank of America vs. Bank of Nova |
| Schwab Us vs. Vanguard Total Stock | Schwab Us vs. Vanguard 500 Index | Schwab Us vs. Vanguard Total Stock | Schwab Us vs. Vanguard Total Stock |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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