Correlation Between Energisa and Kinea Securities
Can any of the company-specific risk be diversified away by investing in both Energisa and Kinea Securities 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 Kinea Securities into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Energisa SA and Kinea Securities Fundo, you can compare the effects of market volatilities on Energisa and Kinea Securities 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 Kinea Securities. Check out your portfolio center. Please also check ongoing floating volatility patterns of Energisa and Kinea Securities.
Diversification Opportunities for Energisa and Kinea Securities
0.31 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Energisa and Kinea is 0.31. Overlapping area represents the amount of risk that can be diversified away by holding Energisa SA and Kinea Securities Fundo in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kinea Securities Fundo 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 Kinea Securities. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kinea Securities Fundo has no effect on the direction of Energisa i.e., Energisa and Kinea Securities go up and down completely randomly.
Pair Corralation between Energisa and Kinea Securities
Assuming the 90 days trading horizon Energisa SA is expected to under-perform the Kinea Securities. In addition to that, Energisa is 1.09 times more volatile than Kinea Securities Fundo. It trades about -0.14 of its total potential returns per unit of risk. Kinea Securities Fundo is currently generating about 0.0 per unit of volatility. If you would invest 833.00 in Kinea Securities Fundo on October 25, 2024 and sell it today you would lose (8.00) from holding Kinea Securities Fundo or give up 0.96% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 97.5% |
Values | Daily Returns |
Energisa SA vs. Kinea Securities Fundo
Performance |
Timeline |
Energisa SA |
Kinea Securities Fundo |
Energisa and Kinea Securities Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Energisa and Kinea Securities
The main advantage of trading using opposite Energisa and Kinea Securities positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Energisa position performs unexpectedly, Kinea Securities 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 Kinea Securities will offset losses from the drop in Kinea Securities' long position.Energisa vs. Equatorial Energia SA | Energisa vs. CPFL Energia SA | Energisa vs. Eneva SA | Energisa vs. Companhia de Saneamento |
Kinea Securities vs. Kinea Oportunidades Real | Kinea Securities vs. Kinea Indices Precos | Kinea Securities vs. Kinea Creditas Fundo | Kinea Securities vs. Kinea High Yield |
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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