Correlation Between Vistra Energy and Power Assets
Can any of the company-specific risk be diversified away by investing in both Vistra Energy and Power Assets 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 Power Assets 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 Power Assets Holdings, you can compare the effects of market volatilities on Vistra Energy and Power Assets 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 Power Assets. Check out your portfolio center. Please also check ongoing floating volatility patterns of Vistra Energy and Power Assets.
Diversification Opportunities for Vistra Energy and Power Assets
-0.56 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Vistra and Power is -0.56. Overlapping area represents the amount of risk that can be diversified away by holding Vistra Energy Corp and Power Assets Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Power Assets Holdings 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 Power Assets. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Power Assets Holdings has no effect on the direction of Vistra Energy i.e., Vistra Energy and Power Assets go up and down completely randomly.
Pair Corralation between Vistra Energy and Power Assets
Considering the 90-day investment horizon Vistra Energy Corp is expected to generate 2.18 times more return on investment than Power Assets. However, Vistra Energy is 2.18 times more volatile than Power Assets Holdings. It trades about 0.11 of its potential returns per unit of risk. Power Assets Holdings is currently generating about 0.05 per unit of risk. If you would invest 10,567 in Vistra Energy Corp on August 24, 2024 and sell it today you would earn a total of 6,094 from holding Vistra Energy Corp or generate 57.67% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Vistra Energy Corp vs. Power Assets Holdings
Performance |
| Timeline |
| Vistra Energy Corp |
| Power Assets Holdings |
Vistra Energy and Power Assets Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Vistra Energy and Power Assets
The main advantage of trading using opposite Vistra Energy and Power Assets positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Vistra Energy position performs unexpectedly, Power Assets 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 Power Assets will offset losses from the drop in Power Assets' long position.| Vistra Energy vs. Pampa Energia SA | Vistra Energy vs. TransAlta Corp | Vistra Energy vs. Kenon Holdings | Vistra Energy vs. NRG Energy |
| Power Assets vs. Southern Company Series | Power Assets vs. Southern Co | Power Assets vs. Talen Energy | Power Assets vs. CMS Energy Corp |
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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