Correlation Between KeyCorp and HomeStreet
Can any of the company-specific risk be diversified away by investing in both KeyCorp and HomeStreet 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 HomeStreet into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KeyCorp and HomeStreet, you can compare the effects of market volatilities on KeyCorp and HomeStreet 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 HomeStreet. Check out your portfolio center. Please also check ongoing floating volatility patterns of KeyCorp and HomeStreet.
Diversification Opportunities for KeyCorp and HomeStreet
-0.59 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between KeyCorp and HomeStreet is -0.59. Overlapping area represents the amount of risk that can be diversified away by holding KeyCorp and HomeStreet in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on HomeStreet 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 HomeStreet. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of HomeStreet has no effect on the direction of KeyCorp i.e., KeyCorp and HomeStreet go up and down completely randomly.
Pair Corralation between KeyCorp and HomeStreet
Assuming the 90 days trading horizon KeyCorp is expected to generate 0.18 times more return on investment than HomeStreet. However, KeyCorp is 5.63 times less risky than HomeStreet. It trades about 0.06 of its potential returns per unit of risk. HomeStreet is currently generating about -0.05 per unit of risk. If you would invest 2,237 in KeyCorp on September 13, 2024 and sell it today you would earn a total of 79.00 from holding KeyCorp or generate 3.53% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
KeyCorp vs. HomeStreet
Performance |
Timeline |
KeyCorp |
HomeStreet |
KeyCorp and HomeStreet Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with KeyCorp and HomeStreet
The main advantage of trading using opposite KeyCorp and HomeStreet positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KeyCorp position performs unexpectedly, HomeStreet 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 HomeStreet will offset losses from the drop in HomeStreet's long position.The idea behind KeyCorp and HomeStreet 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.HomeStreet vs. Heartland Financial USA | HomeStreet vs. Heritage Commerce Corp | HomeStreet vs. Business First Bancshares | HomeStreet vs. German American Bancorp |
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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