Correlation Between CPFL Energia and Companhia
Can any of the company-specific risk be diversified away by investing in both CPFL Energia and Companhia 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 Companhia 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 Companhia de Saneamento, you can compare the effects of market volatilities on CPFL Energia and Companhia 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 Companhia. Check out your portfolio center. Please also check ongoing floating volatility patterns of CPFL Energia and Companhia.
Diversification Opportunities for CPFL Energia and Companhia
0.17 | Correlation Coefficient |
Average diversification
The 3 months correlation between CPFL and Companhia is 0.17. Overlapping area represents the amount of risk that can be diversified away by holding CPFL Energia SA and Companhia de Saneamento in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Companhia de Saneamento 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 Companhia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Companhia de Saneamento has no effect on the direction of CPFL Energia i.e., CPFL Energia and Companhia go up and down completely randomly.
Pair Corralation between CPFL Energia and Companhia
Assuming the 90 days trading horizon CPFL Energia SA is expected to generate 0.67 times more return on investment than Companhia. However, CPFL Energia SA is 1.5 times less risky than Companhia. It trades about 0.01 of its potential returns per unit of risk. Companhia de Saneamento is currently generating about 0.0 per unit of risk. If you would invest 3,322 in CPFL Energia SA on August 31, 2024 and sell it today you would earn a total of 5.00 from holding CPFL Energia SA or generate 0.15% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
CPFL Energia SA vs. Companhia de Saneamento
Performance |
Timeline |
CPFL Energia SA |
Companhia de Saneamento |
CPFL Energia and Companhia Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with CPFL Energia and Companhia
The main advantage of trading using opposite CPFL Energia and Companhia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CPFL Energia position performs unexpectedly, Companhia 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 Companhia will offset losses from the drop in Companhia's long position.CPFL Energia vs. salesforce inc | CPFL Energia vs. Unity Software | CPFL Energia vs. The Trade Desk | CPFL Energia vs. Cognizant Technology Solutions |
Companhia vs. CCR SA | Companhia vs. Centrais Eltricas Brasileiras | Companhia vs. Companhia Energtica de | Companhia vs. Centrais Eltricas Brasileiras |
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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