Goldman Sachs Mutual Fund Forward View - Simple Regression
| GCEPX Fund | USD 12.35 -0.48 -3.74% |
This Simple Regression reference page for Goldman Sachs Clean presents model-generated forecast data based on historical daily prices. The output values and deviation metrics are provided for informational reference.
The Simple Regression forecasted value of Goldman Sachs Clean on the next trading day is expected to be 13.07 with a mean absolute deviation of 0.25 and the sum of the absolute errors of 15.70.In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Goldman Sachs Clean historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data. All Simple Regression forecast figures shown for Goldman Sachs Clean are reference data reflecting model output based on available historical prices. Simple Regression Price Forecast For the 22nd of March
Given 90 days horizon, the Simple Regression forecasted value of Goldman Sachs Clean on the next trading day is expected to be 13.07 with a mean absolute deviation of 0.25 , mean absolute percentage error of 0.09 , and the sum of the absolute errors of 15.70 .Please note that although there have been many attempts to predict Goldman Mutual Fund prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Goldman Sachs' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Mutual Fund Forecast Pattern
| Backtest Goldman Sachs | Goldman Sachs Price Prediction | Research Analysis |
Forecasted Value
For the next trading day, Macroaxis evaluates Goldman Sachs' predictive range by looking for statistically meaningful downside and upside boundaries. Investors should still remember that no empirical framework consistently proves that one family of forecasting models will outperform all other approaches in live markets.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of Goldman Sachs mutual fund data series using in forecasting. Note that when a statistical model is used to represent Goldman Sachs mutual fund, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 117.4868 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.2533 |
| MAPE | Mean absolute percentage error | 0.0206 |
| SAE | Sum of the absolute errors | 15.7035 |
Other Forecasting Options for Goldman Sachs
Price movement is the most fundamental factor that determines whether Goldman is a viable investment for any investor. Goldman Mutual Fund price charts are often noisy, making it difficult to identify meaningful patterns without analytical tools.Goldman Sachs Related Equities
The following equities are related to Goldman Sachs within the Miscellaneous Sector space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing Goldman Sachs against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.
| Risk & Return | Correlation |
Goldman Sachs Market Strength Events
Assessing the market strength of Goldman Sachs mutual fund provides investors with a clearer picture of how the security reacts to evolving market dynamics. These indicators can be used to identify periods when trading Goldman Sachs Clean is most likely to be profitable.
| Rate Of Daily Change | 0.96 | |||
| Day Median Price | 12.35 | |||
| Day Typical Price | 12.35 | |||
| Price Action Indicator | -0.24 | |||
| Period Momentum Indicator | -0.48 |
Goldman Sachs Risk Indicators
The analysis of Goldman Sachs' basic risk metrics provides a foundation for forecasting its future price and managing investment risk. Identifying the magnitude of risk in Goldman Sachs' provides context to choose between accepting or hedging their exposure.
| Mean Deviation | 0.8382 | |||
| Semi Deviation | 1.15 | |||
| Standard Deviation | 1.14 | |||
| Variance | 1.3 | |||
| Downside Variance | 2.17 | |||
| Semi Variance | 1.33 | |||
| Expected Short fall | -0.85 |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
Story Coverage note for Goldman Sachs
A coverage review of Goldman Sachs Clean shows when the security is attracting above-average attention from contributors and market observers. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.
Other Macroaxis Stories
Macroaxis publishes story content for a diverse readership that includes finance students, independent investors, money managers, and market-focused operating teams. What connects that audience is a focus on building stronger portfolios through better research, risk awareness, and comparative analysis.