Correlation Between KeyCorp and First Republic
Can any of the company-specific risk be diversified away by investing in both KeyCorp and First Republic 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 KeyCorp and First Republic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KeyCorp and First Republic Bank, you can compare the effects of market volatilities on KeyCorp and First Republic 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 KeyCorp with a short position of First Republic. Check out your portfolio center. Please also check ongoing floating volatility patterns of KeyCorp and First Republic.
Diversification Opportunities for KeyCorp and First Republic
-0.69 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between KeyCorp and First is -0.69. Overlapping area represents the amount of risk that can be diversified away by holding KeyCorp and First Republic Bank in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on First Republic Bank and KeyCorp 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 KeyCorp are associated (or correlated) with First Republic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of First Republic Bank has no effect on the direction of KeyCorp i.e., KeyCorp and First Republic go up and down completely randomly.
Pair Corralation between KeyCorp and First Republic
Assuming the 90 days trading horizon KeyCorp is expected to generate 15.25 times less return on investment than First Republic. But when comparing it to its historical volatility, KeyCorp is 19.68 times less risky than First Republic. It trades about 0.08 of its potential returns per unit of risk. First Republic Bank is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 1.80 in First Republic Bank on August 27, 2024 and sell it today you would lose (1.78) from holding First Republic Bank or give up 98.89% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 13.49% |
| Values | Daily Returns |
KeyCorp vs. First Republic Bank
Performance |
| Timeline |
| KeyCorp |
| First Republic Bank |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
KeyCorp and First Republic Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with KeyCorp and First Republic
The main advantage of trading using opposite KeyCorp and First Republic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KeyCorp position performs unexpectedly, First Republic 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 First Republic will offset losses from the drop in First Republic's long position.| KeyCorp vs. KeyCorp | KeyCorp vs. Regions Financial | KeyCorp vs. US Bancorp | KeyCorp vs. Fifth Third Bancorp |
| First Republic vs. GoHealth | First Republic vs. Maiden Holdings | First Republic vs. Organic Sales and | First Republic vs. The Hanover Insurance |
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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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