Correlation Between Great Southern and Cullman Bancorp
Can any of the company-specific risk be diversified away by investing in both Great Southern and Cullman 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 Great Southern and Cullman Bancorp into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Great Southern Bancorp and Cullman Bancorp, you can compare the effects of market volatilities on Great Southern and Cullman 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 Great Southern with a short position of Cullman Bancorp. Check out your portfolio center. Please also check ongoing floating volatility patterns of Great Southern and Cullman Bancorp.
Diversification Opportunities for Great Southern and Cullman Bancorp
-0.2 | Correlation Coefficient |
Good diversification
The 3 months correlation between Great and Cullman is -0.2. Overlapping area represents the amount of risk that can be diversified away by holding Great Southern Bancorp and Cullman Bancorp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cullman Bancorp and Great Southern 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 Great Southern Bancorp are associated (or correlated) with Cullman Bancorp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cullman Bancorp has no effect on the direction of Great Southern i.e., Great Southern and Cullman Bancorp go up and down completely randomly.
Pair Corralation between Great Southern and Cullman Bancorp
Given the investment horizon of 90 days Great Southern Bancorp is expected to generate 1.63 times more return on investment than Cullman Bancorp. However, Great Southern is 1.63 times more volatile than Cullman Bancorp. It trades about 0.02 of its potential returns per unit of risk. Cullman Bancorp is currently generating about -0.02 per unit of risk. If you would invest 5,729 in Great Southern Bancorp on August 24, 2024 and sell it today you would earn a total of 695.00 from holding Great Southern Bancorp or generate 12.13% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 80.04% |
| Values | Daily Returns |
Great Southern Bancorp vs. Cullman Bancorp
Performance |
| Timeline |
| Great Southern Bancorp |
| Cullman Bancorp |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Great Southern and Cullman Bancorp Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Great Southern and Cullman Bancorp
The main advantage of trading using opposite Great Southern and Cullman Bancorp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Great Southern position performs unexpectedly, Cullman 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 Cullman Bancorp will offset losses from the drop in Cullman Bancorp's long position.| Great Southern vs. First Northwest Bancorp | Great Southern vs. Community West Bancshares | Great Southern vs. First Financial Northwest | Great Southern vs. First Capital |
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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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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