Correlation Between Wells Fargo and Regions Financial
Can any of the company-specific risk be diversified away by investing in both Wells Fargo and Regions Financial 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 Wells Fargo and Regions Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Wells Fargo and Regions Financial, you can compare the effects of market volatilities on Wells Fargo and Regions Financial 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 Wells Fargo with a short position of Regions Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Wells Fargo and Regions Financial.
Diversification Opportunities for Wells Fargo and Regions Financial
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Wells and Regions is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding Wells Fargo and Regions Financial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Regions Financial and Wells Fargo 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 Wells Fargo are associated (or correlated) with Regions Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Regions Financial has no effect on the direction of Wells Fargo i.e., Wells Fargo and Regions Financial go up and down completely randomly.
Pair Corralation between Wells Fargo and Regions Financial
Considering the 90-day investment horizon Wells Fargo is expected to generate 0.61 times more return on investment than Regions Financial. However, Wells Fargo is 1.63 times less risky than Regions Financial. It trades about 0.29 of its potential returns per unit of risk. Regions Financial is currently generating about -0.01 per unit of risk. If you would invest 5,673 in Wells Fargo on January 25, 2024 and sell it today you would earn a total of 410.00 from holding Wells Fargo or generate 7.23% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Wells Fargo vs. Regions Financial
Performance |
| Timeline |
| Wells Fargo |
| Regions Financial |
Wells Fargo and Regions Financial Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Wells Fargo and Regions Financial
The main advantage of trading using opposite Wells Fargo and Regions Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Wells Fargo position performs unexpectedly, Regions Financial 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 Regions Financial will offset losses from the drop in Regions Financial's long position.| Wells Fargo vs. Bank of America | Wells Fargo vs. JPMorgan Chase Co | Wells Fargo vs. Toronto Dominion Bank | Wells Fargo vs. Nu Holdings |
| Regions Financial vs. KeyCorp | Regions Financial vs. Fifth Third Bancorp | Regions Financial vs. New York Community | Regions Financial vs. Zions Bancorporation |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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