Correlation Between Goldman Sachs and Abrdn Physical
Can any of the company-specific risk be diversified away by investing in both Goldman Sachs and Abrdn Physical 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 Abrdn Physical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Goldman Sachs Physical and abrdn Physical Gold, you can compare the effects of market volatilities on Goldman Sachs and Abrdn Physical 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 Abrdn Physical. Check out your portfolio center. Please also check ongoing floating volatility patterns of Goldman Sachs and Abrdn Physical.
Diversification Opportunities for Goldman Sachs and Abrdn Physical
1.0 | Correlation Coefficient |
No risk reduction
The 3 months correlation between Goldman and Abrdn is 1.0. Overlapping area represents the amount of risk that can be diversified away by holding Goldman Sachs Physical and abrdn Physical Gold in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on abrdn Physical Gold 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 Physical are associated (or correlated) with Abrdn Physical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of abrdn Physical Gold has no effect on the direction of Goldman Sachs i.e., Goldman Sachs and Abrdn Physical go up and down completely randomly.
Pair Corralation between Goldman Sachs and Abrdn Physical
Given the investment horizon of 90 days Goldman Sachs is expected to generate 1.0 times less return on investment than Abrdn Physical. But when comparing it to its historical volatility, Goldman Sachs Physical is 1.0 times less risky than Abrdn Physical. It trades about 0.11 of its potential returns per unit of risk. abrdn Physical Gold is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 2,381 in abrdn Physical Gold on September 2, 2024 and sell it today you would earn a total of 159.00 from holding abrdn Physical Gold or generate 6.68% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Goldman Sachs Physical vs. abrdn Physical Gold
Performance |
Timeline |
Goldman Sachs Physical |
abrdn Physical Gold |
Goldman Sachs and Abrdn Physical Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Goldman Sachs and Abrdn Physical
The main advantage of trading using opposite Goldman Sachs and Abrdn Physical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Goldman Sachs position performs unexpectedly, Abrdn Physical 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 Abrdn Physical will offset losses from the drop in Abrdn Physical's long position.Goldman Sachs vs. MicroSectors Gold 3X | Goldman Sachs vs. Franklin Responsibly Sourced | Goldman Sachs vs. ProShares Ultra Silver | Goldman Sachs vs. GraniteShares Gold Trust |
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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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