Correlation Between Pimco Energy and Hennessy
Can any of the company-specific risk be diversified away by investing in both Pimco Energy and Hennessy 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 Pimco Energy and Hennessy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pimco Energy Tactical and Hennessy Bp Energy, you can compare the effects of market volatilities on Pimco Energy and Hennessy 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 Pimco Energy with a short position of Hennessy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pimco Energy and Hennessy.
Diversification Opportunities for Pimco Energy and Hennessy
0.58 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Pimco and Hennessy is 0.58. Overlapping area represents the amount of risk that can be diversified away by holding Pimco Energy Tactical and Hennessy Bp Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hennessy Bp Energy and Pimco 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 Pimco Energy Tactical are associated (or correlated) with Hennessy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hennessy Bp Energy has no effect on the direction of Pimco Energy i.e., Pimco Energy and Hennessy go up and down completely randomly.
Pair Corralation between Pimco Energy and Hennessy
Considering the 90-day investment horizon Pimco Energy Tactical is expected to generate 0.86 times more return on investment than Hennessy. However, Pimco Energy Tactical is 1.17 times less risky than Hennessy. It trades about 0.15 of its potential returns per unit of risk. Hennessy Bp Energy is currently generating about 0.02 per unit of risk. If you would invest 1,963 in Pimco Energy Tactical on October 12, 2024 and sell it today you would earn a total of 632.00 from holding Pimco Energy Tactical or generate 32.2% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Pimco Energy Tactical vs. Hennessy Bp Energy
Performance |
| Timeline |
| Pimco Energy Tactical |
| Hennessy Bp Energy |
Pimco Energy and Hennessy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Pimco Energy and Hennessy
The main advantage of trading using opposite Pimco Energy and Hennessy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pimco Energy position performs unexpectedly, Hennessy 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 Hennessy will offset losses from the drop in Hennessy's long position.| Pimco Energy vs. Nasdaq 100 Profund Nasdaq 100 | Pimco Energy vs. Alternative Asset Allocation | Pimco Energy vs. Issachar Fund Class | Pimco Energy vs. Rbb Fund |
| Hennessy vs. World Energy Fund | Hennessy vs. Ivy Energy Fund | Hennessy vs. Blackrock All Cap Energy | Hennessy vs. Energy Fund Class |
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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