Correlation Between Intesa Sanpaolo and Credit Agricole
Can any of the company-specific risk be diversified away by investing in both Intesa Sanpaolo and Credit Agricole 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 Intesa Sanpaolo and Credit Agricole into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Intesa Sanpaolo SpA and Credit Agricole SA, you can compare the effects of market volatilities on Intesa Sanpaolo and Credit Agricole 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 Intesa Sanpaolo with a short position of Credit Agricole. Check out your portfolio center. Please also check ongoing floating volatility patterns of Intesa Sanpaolo and Credit Agricole.
Diversification Opportunities for Intesa Sanpaolo and Credit Agricole
0.99 | Correlation Coefficient |
No risk reduction
The 3 months correlation between Intesa and Credit is 0.99. Overlapping area represents the amount of risk that can be diversified away by holding Intesa Sanpaolo SpA and Credit Agricole SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Credit Agricole SA and Intesa Sanpaolo 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 Intesa Sanpaolo SpA are associated (or correlated) with Credit Agricole. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Credit Agricole SA has no effect on the direction of Intesa Sanpaolo i.e., Intesa Sanpaolo and Credit Agricole go up and down completely randomly.
Pair Corralation between Intesa Sanpaolo and Credit Agricole
Assuming the 90 days horizon Intesa Sanpaolo is expected to generate 1.07 times less return on investment than Credit Agricole. In addition to that, Intesa Sanpaolo is 1.22 times more volatile than Credit Agricole SA. It trades about 0.28 of its total potential returns per unit of risk. Credit Agricole SA is currently generating about 0.36 per unit of volatility. If you would invest 689.00 in Credit Agricole SA on December 29, 2024 and sell it today you would earn a total of 221.00 from holding Credit Agricole SA or generate 32.08% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Intesa Sanpaolo SpA vs. Credit Agricole SA
Performance |
Timeline |
Intesa Sanpaolo SpA |
Credit Agricole SA |
Intesa Sanpaolo and Credit Agricole Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Intesa Sanpaolo and Credit Agricole
The main advantage of trading using opposite Intesa Sanpaolo and Credit Agricole positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Intesa Sanpaolo position performs unexpectedly, Credit Agricole 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 Credit Agricole will offset losses from the drop in Credit Agricole's long position.Intesa Sanpaolo vs. Banco Do Brasil | Intesa Sanpaolo vs. KBC Groep NV | Intesa Sanpaolo vs. Credit Agricole SA | Intesa Sanpaolo vs. BNP Paribas SA |
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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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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