Correlation Between Vistra Energy and Pampa Energia
Can any of the company-specific risk be diversified away by investing in both Vistra Energy and Pampa Energia 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 Vistra Energy and Pampa Energia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Vistra Energy Corp and Pampa Energia SA, you can compare the effects of market volatilities on Vistra Energy and Pampa Energia 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 Vistra Energy with a short position of Pampa Energia. Check out your portfolio center. Please also check ongoing floating volatility patterns of Vistra Energy and Pampa Energia.
Diversification Opportunities for Vistra Energy and Pampa Energia
0.76 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Vistra and Pampa is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding Vistra Energy Corp and Pampa Energia SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pampa Energia SA and Vistra Energy 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 Vistra Energy Corp are associated (or correlated) with Pampa Energia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pampa Energia SA has no effect on the direction of Vistra Energy i.e., Vistra Energy and Pampa Energia go up and down completely randomly.
Pair Corralation between Vistra Energy and Pampa Energia
Considering the 90-day investment horizon Vistra Energy Corp is expected to generate 1.33 times more return on investment than Pampa Energia. However, Vistra Energy is 1.33 times more volatile than Pampa Energia SA. It trades about -0.05 of its potential returns per unit of risk. Pampa Energia SA is currently generating about -0.15 per unit of risk. If you would invest 12,425 in Vistra Energy Corp on January 13, 2025 and sell it today you would lose (1,254) from holding Vistra Energy Corp or give up 10.09% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Vistra Energy Corp vs. Pampa Energia SA
Performance |
| Timeline |
| Vistra Energy Corp |
| Pampa Energia SA |
Vistra Energy and Pampa Energia Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Vistra Energy and Pampa Energia
The main advantage of trading using opposite Vistra Energy and Pampa Energia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Vistra Energy position performs unexpectedly, Pampa Energia 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 Pampa Energia will offset losses from the drop in Pampa Energia's long position.| Vistra Energy vs. Pampa Energia SA | Vistra Energy vs. TransAlta Corp | Vistra Energy vs. Kenon Holdings | Vistra Energy vs. NRG Energy |
| Pampa Energia vs. Grupo Financiero Galicia | Pampa Energia vs. Banco Macro SA | Pampa Energia vs. Empresa Distribuidora y | Pampa Energia vs. Transportadora de Gas |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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