Correlation Between Woori Financial and Customers Bancorp
Can any of the company-specific risk be diversified away by investing in both Woori Financial and Customers 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 Woori Financial and Customers Bancorp into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Woori Financial Group and Customers Bancorp, you can compare the effects of market volatilities on Woori Financial and Customers 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 Woori Financial with a short position of Customers Bancorp. Check out your portfolio center. Please also check ongoing floating volatility patterns of Woori Financial and Customers Bancorp.
Diversification Opportunities for Woori Financial and Customers Bancorp
0.4 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Woori and Customers is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding Woori Financial Group and Customers Bancorp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Customers Bancorp and Woori Financial 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 Woori Financial Group are associated (or correlated) with Customers Bancorp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Customers Bancorp has no effect on the direction of Woori Financial i.e., Woori Financial and Customers Bancorp go up and down completely randomly.
Pair Corralation between Woori Financial and Customers Bancorp
Allowing for the 90-day total investment horizon Woori Financial Group is expected to generate 3.88 times more return on investment than Customers Bancorp. However, Woori Financial is 3.88 times more volatile than Customers Bancorp. It trades about 0.09 of its potential returns per unit of risk. Customers Bancorp is currently generating about 0.07 per unit of risk. If you would invest 3,212 in Woori Financial Group on December 20, 2024 and sell it today you would earn a total of 222.00 from holding Woori Financial Group or generate 6.91% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Woori Financial Group vs. Customers Bancorp
Performance |
Timeline |
Woori Financial Group |
Customers Bancorp |
Woori Financial and Customers Bancorp Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Woori Financial and Customers Bancorp
The main advantage of trading using opposite Woori Financial and Customers Bancorp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Woori Financial position performs unexpectedly, Customers 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 Customers Bancorp will offset losses from the drop in Customers Bancorp's long position.Woori Financial vs. Shinhan Financial Group | Woori Financial vs. KB Financial Group | Woori Financial vs. Banco De Chile | Woori Financial vs. Orix Corp Ads |
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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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