Correlation Between Chongqing Rural and Banco Bradesco
Can any of the company-specific risk be diversified away by investing in both Chongqing Rural and Banco Bradesco 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 Chongqing Rural and Banco Bradesco into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Chongqing Rural Commercial and Banco Bradesco SA, you can compare the effects of market volatilities on Chongqing Rural and Banco Bradesco 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 Chongqing Rural with a short position of Banco Bradesco. Check out your portfolio center. Please also check ongoing floating volatility patterns of Chongqing Rural and Banco Bradesco.
Diversification Opportunities for Chongqing Rural and Banco Bradesco
-0.75 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Chongqing and Banco is -0.75. Overlapping area represents the amount of risk that can be diversified away by holding Chongqing Rural Commercial and Banco Bradesco SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Banco Bradesco SA and Chongqing Rural 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 Chongqing Rural Commercial are associated (or correlated) with Banco Bradesco. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Banco Bradesco SA has no effect on the direction of Chongqing Rural i.e., Chongqing Rural and Banco Bradesco go up and down completely randomly.
Pair Corralation between Chongqing Rural and Banco Bradesco
Assuming the 90 days horizon Chongqing Rural Commercial is expected to generate 3.09 times more return on investment than Banco Bradesco. However, Chongqing Rural is 3.09 times more volatile than Banco Bradesco SA. It trades about 0.07 of its potential returns per unit of risk. Banco Bradesco SA is currently generating about -0.07 per unit of risk. If you would invest 1,626 in Chongqing Rural Commercial on September 23, 2024 and sell it today you would earn a total of 1,082 from holding Chongqing Rural Commercial or generate 66.54% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 64.44% |
Values | Daily Returns |
Chongqing Rural Commercial vs. Banco Bradesco SA
Performance |
Timeline |
Chongqing Rural Comm |
Banco Bradesco SA |
Chongqing Rural and Banco Bradesco Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Chongqing Rural and Banco Bradesco
The main advantage of trading using opposite Chongqing Rural and Banco Bradesco positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Chongqing Rural position performs unexpectedly, Banco Bradesco 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 Banco Bradesco will offset losses from the drop in Banco Bradesco's long position.Chongqing Rural vs. Banco Bradesco SA | Chongqing Rural vs. Itau Unibanco Banco | Chongqing Rural vs. Lloyds Banking Group | Chongqing Rural vs. Deutsche Bank AG |
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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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