Goldman Sachs E Fund Market Value
| GCFCX Fund | USD 8.91 0.06 0.67% |
| Symbol | Goldman |
Goldman Sachs 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Goldman Sachs' mutual fund what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Goldman Sachs.
| 04/27/2022 |
| 04/16/2024 |
If you would invest 0.00 in Goldman Sachs on April 27, 2022 and sell it all today you would earn a total of 0.00 from holding Goldman Sachs E or generate 0.0% return on investment in Goldman Sachs over 720 days. Goldman Sachs is related to or competes with Goldman Sachs, Goldman Sachs, Goldman Sachs, Goldman Sachs, Goldman Sachs, Goldman Sachs, and Goldman Sachs. The fund normally invests at least 80 percent of its net assets plus any borrowings for investment purposes in fixed inc... More
Goldman Sachs Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Goldman Sachs' mutual fund current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Goldman Sachs E upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.26) | |||
| Maximum Drawdown | 1.98 | |||
| Value At Risk | (0.77) | |||
| Potential Upside | 0.443 |
Goldman Sachs Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Goldman Sachs' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Goldman Sachs' standard deviation. In reality, there are many statistical measures that can use Goldman Sachs historical prices to predict the future Goldman Sachs' volatility.| Risk Adjusted Performance | (0.07) | |||
| Jensen Alpha | (0.07) | |||
| Total Risk Alpha | (0.09) | |||
| Treynor Ratio | (0.20) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Goldman Sachs' price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Goldman Sachs E Backtested Returns
Goldman Sachs E holds Efficiency (Sharpe) Ratio of -0.0959, which attests that the entity had a -0.0959% return per unit of risk over the last 3 months. Goldman Sachs E exposes twenty-one different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out Goldman Sachs' Risk Adjusted Performance of (0.07), market risk adjusted performance of (0.19), and Standard Deviation of 0.3999 to validate the risk estimate we provide. The fund retains a Market Volatility (i.e., Beta) of 0.26, which attests to not very significant fluctuations relative to the market. As returns on the market increase, Goldman Sachs' returns are expected to increase less than the market. However, during the bear market, the loss of holding Goldman Sachs is expected to be smaller as well.
Auto-correlation | 0.59 |
Modest predictability
Goldman Sachs E has modest predictability. Overlapping area represents the amount of predictability between Goldman Sachs time series from 27th of April 2022 to 22nd of April 2023 and 22nd of April 2023 to 16th of April 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Goldman Sachs E price movement. The serial correlation of 0.59 indicates that roughly 59.0% of current Goldman Sachs price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.59 | |
| Spearman Rank Test | -0.26 | |
| Residual Average | 0.0 | |
| Price Variance | 0.04 |
Goldman Sachs E lagged returns against current returns
Autocorrelation, which is Goldman Sachs mutual fund's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Goldman Sachs' mutual fund expected returns. We can calculate the autocorrelation of Goldman Sachs returns to help us make a trade decision. For example, suppose you find that Goldman Sachs has exhibited high autocorrelation historically, and you observe that the mutual fund is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Goldman Sachs regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Goldman Sachs mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Goldman Sachs mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Goldman Sachs mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Goldman Sachs Lagged Returns
When evaluating Goldman Sachs' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Goldman Sachs mutual fund have on its future price. Goldman Sachs autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Goldman Sachs autocorrelation shows the relationship between Goldman Sachs mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Goldman Sachs E.
Regressed Prices |
| Timeline |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Goldman Sachs in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Goldman Sachs' short interest history, or implied volatility extrapolated from Goldman Sachs options trading.
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Try AI Portfolio ArchitectCheck out Goldman Sachs Correlation, Goldman Sachs Volatility and Goldman Sachs Alpha and Beta module to complement your research on Goldman Sachs. Note that the Goldman Sachs E information on this page should be used as a complementary analysis to other Goldman Sachs' statistical models used 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 Balance Of Power module to check stock momentum by analyzing Balance Of Power indicator and other technical ratios.
Goldman Sachs technical mutual fund analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, fund market cycles, or different charting patterns.