Correlation Between William Penn and Park National
Can any of the company-specific risk be diversified away by investing in both William Penn and Park 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 William Penn and Park National into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between William Penn Bancorp and Park National, you can compare the effects of market volatilities on William Penn and Park 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 William Penn with a short position of Park National. Check out your portfolio center. Please also check ongoing floating volatility patterns of William Penn and Park National.
Diversification Opportunities for William Penn and Park National
0.85 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between William and Park is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding William Penn Bancorp and Park National in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Park National and William Penn 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 William Penn Bancorp are associated (or correlated) with Park National. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Park National has no effect on the direction of William Penn i.e., William Penn and Park National go up and down completely randomly.
Pair Corralation between William Penn and Park National
Given the investment horizon of 90 days William Penn Bancorp is expected to generate 1.09 times more return on investment than Park National. However, William Penn is 1.09 times more volatile than Park National. It trades about 0.02 of its potential returns per unit of risk. Park National is currently generating about -0.08 per unit of risk. If you would invest 1,205 in William Penn Bancorp on October 20, 2024 and sell it today you would earn a total of 6.00 from holding William Penn Bancorp or generate 0.5% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 95.0% |
| Values | Daily Returns |
William Penn Bancorp vs. Park National
Performance |
| Timeline |
| William Penn Bancorp |
| Park National |
William Penn and Park National Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with William Penn and Park National
The main advantage of trading using opposite William Penn and Park National positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if William Penn position performs unexpectedly, Park 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 Park National will offset losses from the drop in Park National's long position.| William Penn vs. Home Federal Bancorp | William Penn vs. First Financial Northwest | William Penn vs. First Northwest Bancorp | William Penn vs. First Capital |
| Park National vs. Peoples Bancorp | Park National vs. Lakeland Financial | Park National vs. NBT Bancorp | Park National vs. Trustmark |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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