Correlation Between Byline Bancorp and IF Bancorp
Can any of the company-specific risk be diversified away by investing in both Byline Bancorp and IF 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 Byline Bancorp and IF Bancorp into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Byline Bancorp and IF Bancorp, you can compare the effects of market volatilities on Byline Bancorp and IF 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 Byline Bancorp with a short position of IF Bancorp. Check out your portfolio center. Please also check ongoing floating volatility patterns of Byline Bancorp and IF Bancorp.
Diversification Opportunities for Byline Bancorp and IF Bancorp
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Byline and IROQ is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Byline Bancorp and IF Bancorp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on IF Bancorp and Byline 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 Byline Bancorp are associated (or correlated) with IF Bancorp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of IF Bancorp has no effect on the direction of Byline Bancorp i.e., Byline Bancorp and IF Bancorp go up and down completely randomly.
Pair Corralation between Byline Bancorp and IF Bancorp
Allowing for the 90-day total investment horizon Byline Bancorp is expected to under-perform the IF Bancorp. But the stock apears to be less risky and, when comparing its historical volatility, Byline Bancorp is 3.83 times less risky than IF Bancorp. The stock trades about -0.14 of its potential returns per unit of risk. The IF Bancorp is currently generating about 0.17 of returns per unit of risk over similar time horizon. If you would invest 2,125 in IF Bancorp on September 12, 2024 and sell it today you would earn a total of 242.00 from holding IF Bancorp or generate 11.39% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Byline Bancorp vs. IF Bancorp
Performance |
| Timeline |
| Byline Bancorp |
| IF Bancorp |
Byline Bancorp and IF Bancorp Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Byline Bancorp and IF Bancorp
The main advantage of trading using opposite Byline Bancorp and IF Bancorp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Byline Bancorp position performs unexpectedly, IF 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 IF Bancorp will offset losses from the drop in IF Bancorp's long position.| Byline Bancorp vs. Affinity Bancshares | Byline Bancorp vs. Home Federal Bancorp | Byline Bancorp vs. LINKBANCORP | Byline Bancorp vs. Bankwell Financial Group |
| IF Bancorp vs. Home Bancorp | IF Bancorp vs. Commerzbank AG PK | IF Bancorp vs. ConnectOne Bancorp | IF Bancorp vs. Home Federal 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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