Goldman Sachs Income Fund Market Value
GSBCX Fund | USD 24.36 0.04 0.16% |
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.
04/09/2022 |
| 03/29/2024 |
If you would invest 0.00 in Goldman Sachs on April 9, 2022 and sell it all today you would earn a total of 0.00 from holding Goldman Sachs Income or generate 0.0% return on investment in Goldman Sachs over 720 days. Goldman Sachs is related to or competes with Vanguard Wellesley, Blackrock Multi-asset, The Hartford, The Hartford, The Hartford, The Hartford, and The Hartford. The fund seeks to provide income through investments in fixed income securities and high dividend paying equities, prefe... 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 Income upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.3914 | |||
Information Ratio | (0.22) | |||
Maximum Drawdown | 1.61 | |||
Value At Risk | (0.56) | |||
Potential Upside | 0.597 |
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 | 0.093 | |||
Jensen Alpha | (0.02) | |||
Total Risk Alpha | (0.03) | |||
Sortino Ratio | (0.19) | |||
Treynor Ratio | 0.0933 |
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 Income Backtested Returns
We consider Goldman Sachs out of control. Goldman Sachs Income holds Efficiency (Sharpe) Ratio of 0.17, which attests that the entity had a 0.17% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Goldman Sachs Income, which you can use to evaluate the volatility of the entity. Please check out Goldman Sachs' Market Risk Adjusted Performance of 0.1033, downside deviation of 0.3914, and Risk Adjusted Performance of 0.093 to validate if the risk estimate we provide is consistent with the expected return of 0.0593%. The fund retains a Market Volatility (i.e., Beta) of 0.55, 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 | 0.37 |
Below average predictability
Goldman Sachs Income has below average predictability. Overlapping area represents the amount of predictability between Goldman Sachs time series from 9th of April 2022 to 4th of April 2023 and 4th of April 2023 to 29th of March 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 Income price movement. The serial correlation of 0.37 indicates that just about 37.0% of current Goldman Sachs price fluctuation can be explain by its past prices.
Correlation Coefficient | 0.37 | |
Spearman Rank Test | -0.12 | |
Residual Average | 0.0 | |
Price Variance | 0.64 |
Goldman Sachs Income 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 Income.
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 Income 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 Sectors module to list of equity sectors categorizing publicly traded companies based on their primary business activities.
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When running Goldman Sachs' price analysis, check to measure Goldman Sachs' market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Goldman Sachs is operating at the current time. Most of Goldman Sachs' value examination focuses on studying past and present price action to predict the probability of Goldman Sachs' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Goldman Sachs' price. Additionally, you may evaluate how the addition of Goldman Sachs to your portfolios can decrease your overall portfolio volatility.
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