Goldman Sachs Access Etf Market Value
| GIGB Etf | USD 44.42 0.08 0.18% |
| Symbol | Goldman |
The market value of Goldman Sachs Access 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. However, Goldman Sachs' price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.
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.
| 05/24/2023 |
| 04/18/2024 |
If you would invest 0.00 in Goldman Sachs on May 24, 2023 and sell it all today you would earn a total of 0.00 from holding Goldman Sachs Access or generate 0.0% return on investment in Goldman Sachs over 330 days. Goldman Sachs is related to or competes with PrimeEnergy, Israel Acquisitions, CKX Lands, HUMANA, Barloworld, Thrivent High, and Morningstar Unconstrained. The fund seeks to achieve its investment objective by investing at least 80 percent of its assets in securities included... 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 Access upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.25) | |||
| Maximum Drawdown | 1.94 | |||
| Value At Risk | (0.83) | |||
| Potential Upside | 0.4866 |
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 | (0.08) | |||
| Jensen Alpha | (0.07) | |||
| Total Risk Alpha | (0.08) | |||
| Treynor Ratio | (0.16) |
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 Access Backtested Returns
Goldman Sachs Access holds Efficiency (Sharpe) Ratio of -0.082, which attests that the entity had a -0.082% return per unit of risk over the last 3 months. Goldman Sachs Access exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out Goldman Sachs' Market Risk Adjusted Performance of (0.15), standard deviation of 0.3925, and Risk Adjusted Performance of (0.08) to validate the risk estimate we provide. The etf retains a Market Volatility (i.e., Beta) of 0.33, which attests to possible diversification benefits within a given portfolio. 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 | -0.16 |
Insignificant reverse predictability
Goldman Sachs Access has insignificant reverse predictability. Overlapping area represents the amount of predictability between Goldman Sachs time series from 24th of May 2023 to 5th of November 2023 and 5th of November 2023 to 18th 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 Access price movement. The serial correlation of -0.16 indicates that over 16.0% of current Goldman Sachs price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.16 | |
| Spearman Rank Test | -0.36 | |
| Residual Average | 0.0 | |
| Price Variance | 0.75 |
Goldman Sachs Access lagged returns against current returns
Autocorrelation, which is Goldman Sachs etf'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' etf 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 etf 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 etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Goldman Sachs etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Goldman Sachs etf 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 etf 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 etf current value and its past values and can show if there is a momentum factor associated with investing in Goldman Sachs Access.
Regressed Prices |
| Timeline |
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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 Access 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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.