Correlation Between Duke Energy and Consumers Energy
Can any of the company-specific risk be diversified away by investing in both Duke Energy and Consumers 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 Duke Energy and Consumers Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Duke Energy and Consumers Energy, you can compare the effects of market volatilities on Duke Energy and Consumers 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 Duke Energy with a short position of Consumers Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Duke Energy and Consumers Energy.
Diversification Opportunities for Duke Energy and Consumers Energy
-0.02 | Correlation Coefficient |
Good diversification
The 3 months correlation between Duke and Consumers is -0.02. Overlapping area represents the amount of risk that can be diversified away by holding Duke Energy and Consumers Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Consumers Energy and Duke 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 Duke Energy are associated (or correlated) with Consumers Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Consumers Energy has no effect on the direction of Duke Energy i.e., Duke Energy and Consumers Energy go up and down completely randomly.
Pair Corralation between Duke Energy and Consumers Energy
Assuming the 90 days trading horizon Duke Energy is expected to generate 2.08 times less return on investment than Consumers Energy. But when comparing it to its historical volatility, Duke Energy is 3.54 times less risky than Consumers Energy. It trades about 0.04 of its potential returns per unit of risk. Consumers Energy is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 7,992 in Consumers Energy on August 30, 2024 and sell it today you would earn a total of 128.00 from holding Consumers Energy or generate 1.6% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Duke Energy vs. Consumers Energy
Performance |
Timeline |
Duke Energy |
Consumers Energy |
Duke Energy and Consumers Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Duke Energy and Consumers Energy
The main advantage of trading using opposite Duke Energy and Consumers Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Duke Energy position performs unexpectedly, Consumers 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 Consumers Energy will offset losses from the drop in Consumers Energy's long position.Duke Energy vs. Centrais Eltricas Brasileiras | Duke Energy vs. Nextera Energy | Duke Energy vs. Consumers Energy | Duke Energy vs. CMS Energy |
Consumers Energy vs. Nextera Energy | Consumers Energy vs. Duke Energy | Consumers Energy vs. PGE Corp | Consumers Energy vs. Southern Company |
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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