Correlation Between Energisa and Plascar Participaes
Can any of the company-specific risk be diversified away by investing in both Energisa and Plascar Participaes 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 Energisa and Plascar Participaes into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Energisa SA and Plascar Participaes Industriais, you can compare the effects of market volatilities on Energisa and Plascar Participaes 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 Energisa with a short position of Plascar Participaes. Check out your portfolio center. Please also check ongoing floating volatility patterns of Energisa and Plascar Participaes.
Diversification Opportunities for Energisa and Plascar Participaes
0.1 | Correlation Coefficient |
Average diversification
The 3 months correlation between Energisa and Plascar is 0.1. Overlapping area represents the amount of risk that can be diversified away by holding Energisa SA and Plascar Participaes Industriai in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Plascar Participaes and Energisa 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 Energisa SA are associated (or correlated) with Plascar Participaes. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Plascar Participaes has no effect on the direction of Energisa i.e., Energisa and Plascar Participaes go up and down completely randomly.
Pair Corralation between Energisa and Plascar Participaes
Assuming the 90 days trading horizon Energisa SA is expected to under-perform the Plascar Participaes. But the stock apears to be less risky and, when comparing its historical volatility, Energisa SA is 1.38 times less risky than Plascar Participaes. The stock trades about -0.12 of its potential returns per unit of risk. The Plascar Participaes Industriais is currently generating about -0.04 of returns per unit of risk over similar time horizon. If you would invest 600.00 in Plascar Participaes Industriais on October 25, 2024 and sell it today you would lose (50.00) from holding Plascar Participaes Industriais or give up 8.33% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Energisa SA vs. Plascar Participaes Industriai
Performance |
Timeline |
Energisa SA |
Plascar Participaes |
Energisa and Plascar Participaes Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Energisa and Plascar Participaes
The main advantage of trading using opposite Energisa and Plascar Participaes positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Energisa position performs unexpectedly, Plascar Participaes 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 Plascar Participaes will offset losses from the drop in Plascar Participaes' long position.Energisa vs. Equatorial Energia SA | Energisa vs. CPFL Energia SA | Energisa vs. Eneva SA | Energisa vs. Companhia de Saneamento |
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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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