Correlation Between John Hancock and Goldman Sachs
Can any of the company-specific risk be diversified away by investing in both John Hancock and Goldman Sachs 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 John Hancock and Goldman Sachs into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between John Hancock Variable and Goldman Sachs Real, you can compare the effects of market volatilities on John Hancock and Goldman Sachs 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 John Hancock with a short position of Goldman Sachs. Check out your portfolio center. Please also check ongoing floating volatility patterns of John Hancock and Goldman Sachs.
Diversification Opportunities for John Hancock and Goldman Sachs
0.81 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between John and GOLDMAN is 0.81. Overlapping area represents the amount of risk that can be diversified away by holding John Hancock Variable and Goldman Sachs Real in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Goldman Sachs Real and John Hancock 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 John Hancock Variable are associated (or correlated) with Goldman Sachs. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Goldman Sachs Real has no effect on the direction of John Hancock i.e., John Hancock and Goldman Sachs go up and down completely randomly.
Pair Corralation between John Hancock and Goldman Sachs
Assuming the 90 days horizon John Hancock Variable is expected to under-perform the Goldman Sachs. But the mutual fund apears to be less risky and, when comparing its historical volatility, John Hancock Variable is 1.03 times less risky than Goldman Sachs. The mutual fund trades about -0.02 of its potential returns per unit of risk. The Goldman Sachs Real is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 1,197 in Goldman Sachs Real on December 21, 2024 and sell it today you would earn a total of 26.00 from holding Goldman Sachs Real or generate 2.17% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
John Hancock Variable vs. Goldman Sachs Real
Performance |
Timeline |
John Hancock Variable |
Goldman Sachs Real |
John Hancock and Goldman Sachs Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with John Hancock and Goldman Sachs
The main advantage of trading using opposite John Hancock and Goldman Sachs positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if John Hancock position performs unexpectedly, Goldman Sachs 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 Goldman Sachs will offset losses from the drop in Goldman Sachs' long position.John Hancock vs. Longboard Alternative Growth | John Hancock vs. Qs Growth Fund | John Hancock vs. Morgan Stanley Multi | John Hancock vs. Tfa Alphagen Growth |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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