Correlation Between Hennessy and Commodities Strategy
Can any of the company-specific risk be diversified away by investing in both Hennessy and Commodities Strategy 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 Hennessy and Commodities Strategy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hennessy Bp Energy and Commodities Strategy Fund, you can compare the effects of market volatilities on Hennessy and Commodities Strategy 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 Hennessy with a short position of Commodities Strategy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hennessy and Commodities Strategy.
Diversification Opportunities for Hennessy and Commodities Strategy
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hennessy and Commodities is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Hennessy Bp Energy and Commodities Strategy Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Commodities Strategy and Hennessy 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 Hennessy Bp Energy are associated (or correlated) with Commodities Strategy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Commodities Strategy has no effect on the direction of Hennessy i.e., Hennessy and Commodities Strategy go up and down completely randomly.
Pair Corralation between Hennessy and Commodities Strategy
Assuming the 90 days horizon Hennessy Bp Energy is expected to generate 2.06 times more return on investment than Commodities Strategy. However, Hennessy is 2.06 times more volatile than Commodities Strategy Fund. It trades about 0.04 of its potential returns per unit of risk. Commodities Strategy Fund is currently generating about -0.13 per unit of risk. If you would invest 2,813 in Hennessy Bp Energy on December 24, 2024 and sell it today you would earn a total of 25.00 from holding Hennessy Bp Energy or generate 0.89% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Hennessy Bp Energy vs. Commodities Strategy Fund
Performance |
Timeline |
Hennessy Bp Energy |
Commodities Strategy |
Hennessy and Commodities Strategy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hennessy and Commodities Strategy
The main advantage of trading using opposite Hennessy and Commodities Strategy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hennessy position performs unexpectedly, Commodities Strategy 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 Commodities Strategy will offset losses from the drop in Commodities Strategy's long position.Hennessy vs. World Energy Fund | Hennessy vs. Ivy Energy Fund | Hennessy vs. Blackrock All Cap Energy | Hennessy vs. Energy Fund Class |
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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 Theme Ratings module to determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance.
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