Correlation Between CPFL Energia and Empresa Metropolitana
Can any of the company-specific risk be diversified away by investing in both CPFL Energia and Empresa Metropolitana 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 CPFL Energia and Empresa Metropolitana into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CPFL Energia SA and Empresa Metropolitana de, you can compare the effects of market volatilities on CPFL Energia and Empresa Metropolitana 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 CPFL Energia with a short position of Empresa Metropolitana. Check out your portfolio center. Please also check ongoing floating volatility patterns of CPFL Energia and Empresa Metropolitana.
Diversification Opportunities for CPFL Energia and Empresa Metropolitana
0.6 | Correlation Coefficient |
Poor diversification
The 3 months correlation between CPFL and Empresa is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding CPFL Energia SA and Empresa Metropolitana de in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Empresa Metropolitana and CPFL Energia 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 CPFL Energia SA are associated (or correlated) with Empresa Metropolitana. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Empresa Metropolitana has no effect on the direction of CPFL Energia i.e., CPFL Energia and Empresa Metropolitana go up and down completely randomly.
Pair Corralation between CPFL Energia and Empresa Metropolitana
Assuming the 90 days trading horizon CPFL Energia SA is expected to generate 0.43 times more return on investment than Empresa Metropolitana. However, CPFL Energia SA is 2.31 times less risky than Empresa Metropolitana. It trades about 0.13 of its potential returns per unit of risk. Empresa Metropolitana de is currently generating about 0.04 per unit of risk. If you would invest 3,262 in CPFL Energia SA on November 29, 2024 and sell it today you would earn a total of 304.00 from holding CPFL Energia SA or generate 9.32% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
CPFL Energia SA vs. Empresa Metropolitana de
Performance |
Timeline |
CPFL Energia SA |
Empresa Metropolitana |
CPFL Energia and Empresa Metropolitana Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with CPFL Energia and Empresa Metropolitana
The main advantage of trading using opposite CPFL Energia and Empresa Metropolitana positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CPFL Energia position performs unexpectedly, Empresa Metropolitana 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 Empresa Metropolitana will offset losses from the drop in Empresa Metropolitana's long position.CPFL Energia vs. Vulcan Materials | CPFL Energia vs. Metalrgica Riosulense SA | CPFL Energia vs. METISA Metalrgica Timboense | CPFL Energia vs. Annaly Capital Management, |
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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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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