Goldman Sachs Etf Market Value
| GCAL Etf | 51.13 0.01 0.02% |
| Symbol | Goldman |
The market value of Goldman Sachs ETF is measured differently than its book value, which is the value of Goldman that is recorded on the company's balance sheet. Investors also form their own opinion of Goldman Sachs' value that differs from its market value or its book value, called intrinsic value, which is Goldman Sachs' true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Goldman Sachs' market value can be influenced by many factors that don't directly affect Goldman Sachs' underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Goldman Sachs' value and its price as these two are different measures arrived at by different means. Investors typically determine if Goldman Sachs is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. Meanwhile, Goldman Sachs' quoted price indicates the marketplace figure where supply meets demand through bilateral consent.
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' etf 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.
| 11/04/2025 |
| 02/02/2026 |
If you would invest 0.00 in Goldman Sachs on November 4, 2025 and sell it all today you would earn a total of 0.00 from holding Goldman Sachs ETF or generate 0.0% return on investment in Goldman Sachs over 90 days. Goldman Sachs is related to or competes with Goldman Sachs, First Trust, Rockefeller California, Principal Exchange, IShares Trust, Listed Funds, and Goldman Sachs. Goldman Sachs is entity of United States 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' etf 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 ETF upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.1296 | |||
| Information Ratio | (0.23) | |||
| Maximum Drawdown | 0.5884 | |||
| Value At Risk | (0.16) | |||
| Potential Upside | 0.1584 |
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 | 0.0711 | |||
| Jensen Alpha | 0.0083 | |||
| Total Risk Alpha | 0.004 | |||
| Sortino Ratio | (0.20) | |||
| Treynor Ratio | 0.3021 |
Goldman Sachs February 2, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0711 | |||
| Market Risk Adjusted Performance | 0.3121 | |||
| Mean Deviation | 0.0862 | |||
| Downside Deviation | 0.1296 | |||
| Coefficient Of Variation | 573.03 | |||
| Standard Deviation | 0.1111 | |||
| Variance | 0.0124 | |||
| Information Ratio | (0.23) | |||
| Jensen Alpha | 0.0083 | |||
| Total Risk Alpha | 0.004 | |||
| Sortino Ratio | (0.20) | |||
| Treynor Ratio | 0.3021 | |||
| Maximum Drawdown | 0.5884 | |||
| Value At Risk | (0.16) | |||
| Potential Upside | 0.1584 | |||
| Downside Variance | 0.0168 | |||
| Semi Variance | (0.01) | |||
| Expected Short fall | (0.1) | |||
| Skewness | (0.70) | |||
| Kurtosis | 0.9241 |
Goldman Sachs ETF Backtested Returns
As of now, Goldman Etf is very steady. Goldman Sachs ETF holds Efficiency (Sharpe) Ratio of 0.19, which attests that the entity had a 0.19 % return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Goldman Sachs ETF, which you can use to evaluate the volatility of the entity. Please check out Goldman Sachs' Market Risk Adjusted Performance of 0.3121, risk adjusted performance of 0.0711, and Coefficient Of Variation of 573.03 to validate if the risk estimate we provide is consistent with the expected return of 0.021%. The etf retains a Market Volatility (i.e., Beta) of 0.0311, 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 | 0.50 |
Modest predictability
Goldman Sachs ETF has modest predictability. Overlapping area represents the amount of predictability between Goldman Sachs time series from 4th of November 2025 to 19th of December 2025 and 19th of December 2025 to 2nd of February 2026. 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 ETF price movement. The serial correlation of 0.5 indicates that about 50.0% of current Goldman Sachs price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.5 | |
| Spearman Rank Test | 0.44 | |
| Residual Average | 0.0 | |
| Price Variance | 0.02 |
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Goldman Sachs technical etf 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, etf market cycles, or different charting patterns.