Correlation Between Goldman Sachs and Hennessy
Can any of the company-specific risk be diversified away by investing in both Goldman Sachs 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 Goldman Sachs and Hennessy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Goldman Sachs Real and Hennessy Bp Midstream, you can compare the effects of market volatilities on Goldman Sachs 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 Goldman Sachs with a short position of Hennessy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Goldman Sachs and Hennessy.
Diversification Opportunities for Goldman Sachs and Hennessy
0.23 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Goldman and Hennessy is 0.23. Overlapping area represents the amount of risk that can be diversified away by holding Goldman Sachs Real and Hennessy Bp Midstream in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hennessy Bp Midstream and Goldman Sachs 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 Goldman Sachs Real 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 Midstream has no effect on the direction of Goldman Sachs i.e., Goldman Sachs and Hennessy go up and down completely randomly.
Pair Corralation between Goldman Sachs and Hennessy
Assuming the 90 days horizon Goldman Sachs is expected to generate 5.23 times less return on investment than Hennessy. But when comparing it to its historical volatility, Goldman Sachs Real is 1.2 times less risky than Hennessy. It trades about 0.02 of its potential returns per unit of risk. Hennessy Bp Midstream is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 1,304 in Hennessy Bp Midstream on December 30, 2024 and sell it today you would earn a total of 107.00 from holding Hennessy Bp Midstream or generate 8.21% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Goldman Sachs Real vs. Hennessy Bp Midstream
Performance |
Timeline |
Goldman Sachs Real |
Risk-Adjusted Performance
Weak
Weak | Strong |
Hennessy Bp Midstream |
Goldman Sachs and Hennessy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Goldman Sachs and Hennessy
The main advantage of trading using opposite Goldman Sachs and Hennessy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Goldman Sachs 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.Goldman Sachs vs. Goldman Sachs Technology | Goldman Sachs vs. Virtus Artificial Intelligence | Goldman Sachs vs. Janus Global Technology | Goldman Sachs vs. Franklin Biotechnology Discovery |
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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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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