Correlation Between Credit Agricole and PNC Financial
Can any of the company-specific risk be diversified away by investing in both Credit Agricole and PNC Financial 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 Credit Agricole and PNC Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Credit Agricole SA and PNC Financial Services, you can compare the effects of market volatilities on Credit Agricole and PNC Financial 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 Credit Agricole with a short position of PNC Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Credit Agricole and PNC Financial.
Diversification Opportunities for Credit Agricole and PNC Financial
-0.91 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Credit and PNC is -0.91. Overlapping area represents the amount of risk that can be diversified away by holding Credit Agricole SA and PNC Financial Services in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PNC Financial Services and Credit Agricole 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 Credit Agricole SA are associated (or correlated) with PNC Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PNC Financial Services has no effect on the direction of Credit Agricole i.e., Credit Agricole and PNC Financial go up and down completely randomly.
Pair Corralation between Credit Agricole and PNC Financial
Assuming the 90 days horizon Credit Agricole SA is expected to under-perform the PNC Financial. But the pink sheet apears to be less risky and, when comparing its historical volatility, Credit Agricole SA is 1.07 times less risky than PNC Financial. The pink sheet trades about -0.09 of its potential returns per unit of risk. The PNC Financial Services is currently generating about 0.19 of returns per unit of risk over similar time horizon. If you would invest 15,143 in PNC Financial Services on September 2, 2024 and sell it today you would earn a total of 6,329 from holding PNC Financial Services or generate 41.79% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Credit Agricole SA vs. PNC Financial Services
Performance |
Timeline |
Credit Agricole SA |
PNC Financial Services |
Credit Agricole and PNC Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Credit Agricole and PNC Financial
The main advantage of trading using opposite Credit Agricole and PNC Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Credit Agricole position performs unexpectedly, PNC Financial 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 PNC Financial will offset losses from the drop in PNC Financial's long position.Credit Agricole vs. Piraeus Bank SA | Credit Agricole vs. Turkiye Garanti Bankasi | Credit Agricole vs. Uwharrie Capital 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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