Correlation Between TotalEnergies and Entreprendre
Can any of the company-specific risk be diversified away by investing in both TotalEnergies and Entreprendre 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 TotalEnergies and Entreprendre into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between TotalEnergies SE and Entreprendre, you can compare the effects of market volatilities on TotalEnergies and Entreprendre 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 TotalEnergies with a short position of Entreprendre. Check out your portfolio center. Please also check ongoing floating volatility patterns of TotalEnergies and Entreprendre.
Diversification Opportunities for TotalEnergies and Entreprendre
-0.4 | Correlation Coefficient |
Very good diversification
The 3 months correlation between TotalEnergies and Entreprendre is -0.4. Overlapping area represents the amount of risk that can be diversified away by holding TotalEnergies SE and Entreprendre in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Entreprendre and TotalEnergies 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 TotalEnergies SE are associated (or correlated) with Entreprendre. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Entreprendre has no effect on the direction of TotalEnergies i.e., TotalEnergies and Entreprendre go up and down completely randomly.
Pair Corralation between TotalEnergies and Entreprendre
Assuming the 90 days trading horizon TotalEnergies is expected to generate 13.36 times less return on investment than Entreprendre. But when comparing it to its historical volatility, TotalEnergies SE is 5.03 times less risky than Entreprendre. It trades about 0.01 of its potential returns per unit of risk. Entreprendre is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 408.00 in Entreprendre on August 29, 2024 and sell it today you would earn a total of 36.00 from holding Entreprendre or generate 8.82% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 95.45% |
| Values | Daily Returns |
TotalEnergies SE vs. Entreprendre
Performance |
| Timeline |
| TotalEnergies SE |
| Entreprendre |
TotalEnergies and Entreprendre Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with TotalEnergies and Entreprendre
The main advantage of trading using opposite TotalEnergies and Entreprendre positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if TotalEnergies position performs unexpectedly, Entreprendre 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 Entreprendre will offset losses from the drop in Entreprendre's long position.| TotalEnergies vs. Air Liquide SA | TotalEnergies vs. Engie SA | TotalEnergies vs. Sanofi SA | TotalEnergies vs. AXA SA |
| Entreprendre vs. Entreparticuli | Entreprendre vs. Enertime SAS | Entreprendre vs. Oeneo SA | Entreprendre vs. Enogia SAS |
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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