Correlation Between First Mid and Penns Woods
Can any of the company-specific risk be diversified away by investing in both First Mid and Penns Woods 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 First Mid and Penns Woods into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Mid Illinois and Penns Woods Bancorp, you can compare the effects of market volatilities on First Mid and Penns Woods 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 First Mid with a short position of Penns Woods. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Mid and Penns Woods.
Diversification Opportunities for First Mid and Penns Woods
0.25 | Correlation Coefficient |
Modest diversification
The 3 months correlation between First and Penns is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding First Mid Illinois and Penns Woods Bancorp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Penns Woods Bancorp and First Mid 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 First Mid Illinois are associated (or correlated) with Penns Woods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Penns Woods Bancorp has no effect on the direction of First Mid i.e., First Mid and Penns Woods go up and down completely randomly.
Pair Corralation between First Mid and Penns Woods
Given the investment horizon of 90 days First Mid is expected to generate 1.94 times less return on investment than Penns Woods. But when comparing it to its historical volatility, First Mid Illinois is 1.06 times less risky than Penns Woods. It trades about 0.06 of its potential returns per unit of risk. Penns Woods Bancorp is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 1,955 in Penns Woods Bancorp on November 9, 2024 and sell it today you would earn a total of 1,235 from holding Penns Woods Bancorp or generate 63.17% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
First Mid Illinois vs. Penns Woods Bancorp
Performance |
| Timeline |
| First Mid Illinois |
| Penns Woods Bancorp |
First Mid and Penns Woods Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with First Mid and Penns Woods
The main advantage of trading using opposite First Mid and Penns Woods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Mid position performs unexpectedly, Penns Woods 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 Penns Woods will offset losses from the drop in Penns Woods' long position.| First Mid vs. Finward Bancorp | First Mid vs. Great Southern Bancorp | First Mid vs. Franklin Financial Services | First Mid vs. Community West Bancshares |
| Penns Woods vs. 1st Source | Penns Woods vs. Great Southern Bancorp | Penns Woods vs. Waterstone Financial | Penns Woods vs. First Community |
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 Valuation module to check real value of public entities based on technical and fundamental data.
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