Correlation Between MicroSectors FANG and Goldman Sachs
Can any of the company-specific risk be diversified away by investing in both MicroSectors FANG 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 MicroSectors FANG and Goldman Sachs into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MicroSectors FANG Index and Goldman Sachs Future, you can compare the effects of market volatilities on MicroSectors FANG 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 MicroSectors FANG with a short position of Goldman Sachs. Check out your portfolio center. Please also check ongoing floating volatility patterns of MicroSectors FANG and Goldman Sachs.
Diversification Opportunities for MicroSectors FANG and Goldman Sachs
-0.06 | Correlation Coefficient |
Good diversification
The 3 months correlation between MicroSectors and Goldman is -0.06. Overlapping area represents the amount of risk that can be diversified away by holding MicroSectors FANG Index and Goldman Sachs Future in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Goldman Sachs Future and MicroSectors FANG 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 MicroSectors FANG Index 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 Future has no effect on the direction of MicroSectors FANG i.e., MicroSectors FANG and Goldman Sachs go up and down completely randomly.
Pair Corralation between MicroSectors FANG and Goldman Sachs
Given the investment horizon of 90 days MicroSectors FANG Index is expected to under-perform the Goldman Sachs. In addition to that, MicroSectors FANG is 4.14 times more volatile than Goldman Sachs Future. It trades about -0.04 of its total potential returns per unit of risk. Goldman Sachs Future is currently generating about -0.08 per unit of volatility. If you would invest 3,279 in Goldman Sachs Future on December 6, 2024 and sell it today you would lose (128.00) from holding Goldman Sachs Future or give up 3.9% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
MicroSectors FANG Index vs. Goldman Sachs Future
Performance |
| Timeline |
| MicroSectors FANG Index |
| Goldman Sachs Future |
MicroSectors FANG and Goldman Sachs Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with MicroSectors FANG and Goldman Sachs
The main advantage of trading using opposite MicroSectors FANG and Goldman Sachs positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MicroSectors FANG 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.| MicroSectors FANG vs. MicroSectors FANG ETN | ||
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| Goldman Sachs vs. Goldman Sachs Future |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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