Correlation Between Apollo Bancorp and Community Bankers
Can any of the company-specific risk be diversified away by investing in both Apollo Bancorp and Community Bankers 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 Apollo Bancorp and Community Bankers into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Apollo Bancorp and Community Bankers, you can compare the effects of market volatilities on Apollo Bancorp and Community Bankers 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 Apollo Bancorp with a short position of Community Bankers. Check out your portfolio center. Please also check ongoing floating volatility patterns of Apollo Bancorp and Community Bankers.
Diversification Opportunities for Apollo Bancorp and Community Bankers
-0.2 | Correlation Coefficient |
Good diversification
The 3 months correlation between Apollo and Community is -0.2. Overlapping area represents the amount of risk that can be diversified away by holding Apollo Bancorp and Community Bankers in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Community Bankers and Apollo Bancorp 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 Apollo Bancorp are associated (or correlated) with Community Bankers. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Community Bankers has no effect on the direction of Apollo Bancorp i.e., Apollo Bancorp and Community Bankers go up and down completely randomly.
Pair Corralation between Apollo Bancorp and Community Bankers
Given the investment horizon of 90 days Apollo Bancorp is expected to under-perform the Community Bankers. But the pink sheet apears to be less risky and, when comparing its historical volatility, Apollo Bancorp is 1.52 times less risky than Community Bankers. The pink sheet trades about -0.07 of its potential returns per unit of risk. The Community Bankers is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 443.00 in Community Bankers on August 31, 2024 and sell it today you would earn a total of 47.00 from holding Community Bankers or generate 10.61% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Apollo Bancorp vs. Community Bankers
Performance |
Timeline |
Apollo Bancorp |
Community Bankers |
Apollo Bancorp and Community Bankers Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Apollo Bancorp and Community Bankers
The main advantage of trading using opposite Apollo Bancorp and Community Bankers positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Apollo Bancorp position performs unexpectedly, Community Bankers 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 Community Bankers will offset losses from the drop in Community Bankers' long position.Apollo Bancorp vs. The Farmers Bank | Apollo Bancorp vs. Bank of Utica | Apollo Bancorp vs. Delhi Bank Corp | Apollo Bancorp vs. CCSB Financial Corp |
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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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