Correlation Between Mid Penn and Central Pacific
Can any of the company-specific risk be diversified away by investing in both Mid Penn and Central Pacific 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 Mid Penn and Central Pacific into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mid Penn Bancorp and Central Pacific Financial, you can compare the effects of market volatilities on Mid Penn and Central Pacific 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 Mid Penn with a short position of Central Pacific. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mid Penn and Central Pacific.
Diversification Opportunities for Mid Penn and Central Pacific
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Mid and Central is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding Mid Penn Bancorp and Central Pacific Financial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Central Pacific Financial and Mid 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 Mid Penn Bancorp are associated (or correlated) with Central Pacific. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Central Pacific Financial has no effect on the direction of Mid Penn i.e., Mid Penn and Central Pacific go up and down completely randomly.
Pair Corralation between Mid Penn and Central Pacific
Considering the 90-day investment horizon Mid Penn Bancorp is expected to under-perform the Central Pacific. But the stock apears to be less risky and, when comparing its historical volatility, Mid Penn Bancorp is 1.18 times less risky than Central Pacific. The stock trades about -0.1 of its potential returns per unit of risk. The Central Pacific Financial is currently generating about -0.02 of returns per unit of risk over similar time horizon. If you would invest 2,851 in Central Pacific Financial on December 27, 2024 and sell it today you would lose (101.00) from holding Central Pacific Financial or give up 3.54% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Mid Penn Bancorp vs. Central Pacific Financial
Performance |
Timeline |
Mid Penn Bancorp |
Central Pacific Financial |
Mid Penn and Central Pacific Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mid Penn and Central Pacific
The main advantage of trading using opposite Mid Penn and Central Pacific positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mid Penn position performs unexpectedly, Central Pacific 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 Central Pacific will offset losses from the drop in Central Pacific's long position.Mid Penn vs. Affinity Bancshares | Mid Penn vs. Home Federal Bancorp | Mid Penn vs. Franklin Financial Services | Mid Penn vs. ACNB Corporation |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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