Correlation Between Red Electrica and CMS Energy
Can any of the company-specific risk be diversified away by investing in both Red Electrica and CMS Energy 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 Red Electrica and CMS Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Red Electrica Corporacion and CMS Energy, you can compare the effects of market volatilities on Red Electrica and CMS Energy 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 Red Electrica with a short position of CMS Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Red Electrica and CMS Energy.
Diversification Opportunities for Red Electrica and CMS Energy
0.31 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Red and CMS is 0.31. Overlapping area represents the amount of risk that can be diversified away by holding Red Electrica Corporacion and CMS Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CMS Energy and Red Electrica 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 Red Electrica Corporacion are associated (or correlated) with CMS Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CMS Energy has no effect on the direction of Red Electrica i.e., Red Electrica and CMS Energy go up and down completely randomly.
Pair Corralation between Red Electrica and CMS Energy
Assuming the 90 days horizon Red Electrica is expected to generate 1.88 times less return on investment than CMS Energy. In addition to that, Red Electrica is 1.03 times more volatile than CMS Energy. It trades about 0.01 of its total potential returns per unit of risk. CMS Energy is currently generating about 0.03 per unit of volatility. If you would invest 5,875 in CMS Energy on October 25, 2024 and sell it today you would earn a total of 711.00 from holding CMS Energy or generate 12.1% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Red Electrica Corporacion vs. CMS Energy
Performance |
| Timeline |
| Red Electrica Corporacion |
| CMS Energy |
Red Electrica and CMS Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Red Electrica and CMS Energy
The main advantage of trading using opposite Red Electrica and CMS Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Red Electrica position performs unexpectedly, CMS Energy 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 CMS Energy will offset losses from the drop in CMS Energy's long position.| Red Electrica vs. Engie Brasil Energia | Red Electrica vs. Centrais Eltricas Brasileiras | Red Electrica vs. Centrais Electricas Brasileiras | Red Electrica vs. Ameren Corp |
| CMS Energy vs. Entergy | CMS Energy vs. Ameren Corp | CMS Energy vs. CenterPoint Energy | CMS Energy vs. Alliant 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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