Goldman Sachs Large Fund Market Value
GCGIX Fund | USD 30.10 0.49 1.65% |
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.
01/25/2024 |
| 04/24/2024 |
If you would invest 0.00 in Goldman Sachs on January 25, 2024 and sell it all today you would earn a total of 0.00 from holding Goldman Sachs Large or generate 0.0% return on investment in Goldman Sachs over 90 days. Goldman Sachs is related to or competes with Amana Income, Amana Income, Amana Developing, and Amana Developing. The fund invests at least 80 percent of its net assets plus any borrowings for investment purposes in a broadly diversif... 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 Large upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 1.07 | |||
Information Ratio | (0.02) | |||
Maximum Drawdown | 5.99 | |||
Value At Risk | (1.66) | |||
Potential Upside | 1.65 |
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 | 0.0516 | |||
Jensen Alpha | (0.01) | |||
Total Risk Alpha | (0.07) | |||
Sortino Ratio | (0.02) | |||
Treynor Ratio | 0.0727 |
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 Large Backtested Returns
We consider Goldman Sachs very steady. Goldman Sachs Large holds Efficiency (Sharpe) Ratio of 0.0631, which attests that the entity had a 0.0631% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Goldman Sachs Large, which you can use to evaluate the volatility of the entity. Please check out Goldman Sachs' Risk Adjusted Performance of 0.0516, market risk adjusted performance of 0.0827, and Downside Deviation of 1.07 to validate if the risk estimate we provide is consistent with the expected return of 0.0662%. The fund retains a Market Volatility (i.e., Beta) of 0.94, which attests to possible diversification benefits within a given portfolio. Goldman Sachs returns are very sensitive to returns on the market. As the market goes up or down, Goldman Sachs is expected to follow.
Auto-correlation | -0.43 |
Modest reverse predictability
Goldman Sachs Large has modest reverse predictability. Overlapping area represents the amount of predictability between Goldman Sachs time series from 25th of January 2024 to 10th of March 2024 and 10th of March 2024 to 24th 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 Large price movement. The serial correlation of -0.43 indicates that just about 43.0% of current Goldman Sachs price fluctuation can be explain by its past prices.
Correlation Coefficient | -0.43 | |
Spearman Rank Test | -0.46 | |
Residual Average | 0.0 | |
Price Variance | 0.29 |
Goldman Sachs Large 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 Large.
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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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.