Correlation Between KeyCorp and US Bancorp
Can any of the company-specific risk be diversified away by investing in both KeyCorp and US Bancorp 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 US Bancorp into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KeyCorp and US Bancorp, you can compare the effects of market volatilities on KeyCorp and US Bancorp 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 US Bancorp. Check out your portfolio center. Please also check ongoing floating volatility patterns of KeyCorp and US Bancorp.
Diversification Opportunities for KeyCorp and US Bancorp
0.31 | Correlation Coefficient |
Weak diversification
The 3 months correlation between KeyCorp and USB-PQ is 0.31. Overlapping area represents the amount of risk that can be diversified away by holding KeyCorp and US Bancorp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on US Bancorp 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 US Bancorp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of US Bancorp has no effect on the direction of KeyCorp i.e., KeyCorp and US Bancorp go up and down completely randomly.
Pair Corralation between KeyCorp and US Bancorp
Assuming the 90 days trading horizon KeyCorp is expected to generate 0.7 times more return on investment than US Bancorp. However, KeyCorp is 1.43 times less risky than US Bancorp. It trades about 0.11 of its potential returns per unit of risk. US Bancorp is currently generating about -0.13 per unit of risk. If you would invest 2,270 in KeyCorp on August 24, 2024 and sell it today you would earn a total of 49.00 from holding KeyCorp or generate 2.16% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
KeyCorp vs. US Bancorp
Performance |
| Timeline |
| KeyCorp |
| US Bancorp |
KeyCorp and US Bancorp Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with KeyCorp and US Bancorp
The main advantage of trading using opposite KeyCorp and US Bancorp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KeyCorp position performs unexpectedly, US Bancorp 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 US Bancorp will offset losses from the drop in US Bancorp's long position.The idea behind KeyCorp and US Bancorp pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| US Bancorp vs. US Bancorp | US Bancorp vs. US Bancorp | US Bancorp vs. Truist Financial | US Bancorp vs. JPMorgan Chase Co |
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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