Correlation Between Great Southern and Farmers National
Can any of the company-specific risk be diversified away by investing in both Great Southern and Farmers National 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 Farmers National 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 Farmers National Banc, you can compare the effects of market volatilities on Great Southern and Farmers National 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 Farmers National. Check out your portfolio center. Please also check ongoing floating volatility patterns of Great Southern and Farmers National.
Diversification Opportunities for Great Southern and Farmers National
0.36 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Great and Farmers is 0.36. Overlapping area represents the amount of risk that can be diversified away by holding Great Southern Bancorp and Farmers National Banc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Farmers National Banc 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 Farmers National. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Farmers National Banc has no effect on the direction of Great Southern i.e., Great Southern and Farmers National go up and down completely randomly.
Pair Corralation between Great Southern and Farmers National
Given the investment horizon of 90 days Great Southern Bancorp is expected to generate 0.99 times more return on investment than Farmers National. However, Great Southern Bancorp is 1.01 times less risky than Farmers National. It trades about -0.03 of its potential returns per unit of risk. Farmers National Banc is currently generating about -0.06 per unit of risk. If you would invest 5,977 in Great Southern Bancorp on December 28, 2024 and sell it today you would lose (191.00) from holding Great Southern Bancorp or give up 3.2% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 98.36% |
Values | Daily Returns |
Great Southern Bancorp vs. Farmers National Banc
Performance |
Timeline |
Great Southern Bancorp |
Farmers National Banc |
Great Southern and Farmers National Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Great Southern and Farmers National
The main advantage of trading using opposite Great Southern and Farmers National positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Great Southern position performs unexpectedly, Farmers National 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 Farmers National will offset losses from the drop in Farmers National'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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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