Correlation Between Goldman Sachs and Fidelity Freedom
Can any of the company-specific risk be diversified away by investing in both Goldman Sachs and Fidelity Freedom 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 Fidelity Freedom into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Goldman Sachs Equity and Fidelity Freedom Index, you can compare the effects of market volatilities on Goldman Sachs and Fidelity Freedom 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 Fidelity Freedom. Check out your portfolio center. Please also check ongoing floating volatility patterns of Goldman Sachs and Fidelity Freedom.
Diversification Opportunities for Goldman Sachs and Fidelity Freedom
1.0 | Correlation Coefficient |
No risk reduction
The 3 months correlation between Goldman and Fidelity is 1.0. Overlapping area represents the amount of risk that can be diversified away by holding Goldman Sachs Equity and Fidelity Freedom Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fidelity Freedom Index 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 Equity are associated (or correlated) with Fidelity Freedom. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fidelity Freedom Index has no effect on the direction of Goldman Sachs i.e., Goldman Sachs and Fidelity Freedom go up and down completely randomly.
Pair Corralation between Goldman Sachs and Fidelity Freedom
Assuming the 90 days horizon Goldman Sachs Equity is expected to generate 1.16 times more return on investment than Fidelity Freedom. However, Goldman Sachs is 1.16 times more volatile than Fidelity Freedom Index. It trades about 0.19 of its potential returns per unit of risk. Fidelity Freedom Index is currently generating about 0.2 per unit of risk. If you would invest 2,272 in Goldman Sachs Equity on June 12, 2025 and sell it today you would earn a total of 177.00 from holding Goldman Sachs Equity or generate 7.79% 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 Equity vs. Fidelity Freedom Index
Performance |
| Timeline |
| Goldman Sachs Equity |
| Fidelity Freedom Index |
Goldman Sachs and Fidelity Freedom Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Goldman Sachs and Fidelity Freedom
The main advantage of trading using opposite Goldman Sachs and Fidelity Freedom positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Goldman Sachs position performs unexpectedly, Fidelity Freedom 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 Fidelity Freedom will offset losses from the drop in Fidelity Freedom's long position.| Goldman Sachs vs. Red Oak Technology | Goldman Sachs vs. Science Technology Fund | Goldman Sachs vs. Firsthand Technology Opportunities | Goldman Sachs vs. Allianzgi Technology Fund |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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