Goldman Sachs Mutual Fund Forward View - Simple Exponential Smoothing
| GCEPX Fund | USD 12.35 -0.48 -3.74% |
Goldman Sachs Clean's Simple Exponential Smoothing reference page covers the model's projected value and error measures from recent price data. The forecast output and associated deviation metrics are shown for informational use.
The Simple Exponential Smoothing forecasted value of Goldman Sachs Clean on the next trading day is expected to be 12.35 with a mean absolute deviation of 0.11 and the sum of the absolute errors of 6.61.This simple exponential smoothing model begins by setting Goldman Sachs Clean forecast for the second period equal to the observation of the first period. In other words, recent Goldman Sachs observations are given relatively more weight in forecasting than the older observations. All Simple Exponential Smoothing forecast figures shown for Goldman Sachs Clean are reference data reflecting model output based on available historical prices. Simple Exponential Smoothing Price Forecast For the 24th of March
Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Goldman Sachs Clean on the next trading day is expected to be 12.35 with a mean absolute deviation of 0.11 , mean absolute percentage error of 0.02 , and the sum of the absolute errors of 6.61 .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
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Forecasted Value
The next-day forecast for Goldman Sachs Clean focuses on identifying predictive downside and upside bands that can frame a realistic trading range. No forecasting approach has been shown to beat all others over time. Investors should treat any model output as a guide, not a guarantee.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing 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 | 112.4376 |
| Bias | Arithmetic mean of the errors | -0.0188 |
| MAD | Mean absolute deviation | 0.1102 |
| MAPE | Mean absolute percentage error | 0.0089 |
| SAE | Sum of the absolute errors | 6.61 |
Other Forecasting Options for Goldman Sachs
Bollinger Bands applied to Goldman Mutual Fund price data measure how far Goldman has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to Goldman Sachs' price data.Goldman Sachs Related Equities
Sizing up Goldman Sachs against these stocks within the Miscellaneous Sector space shows how it compares on key financial measures. Peer review on balance sheet metrics shows how Goldman Sachs' capital structure stacks up against similar firms. How Goldman Sachs ranks within this group can shift over time as the competitive picture changes.
| Risk & Return | Correlation |
Goldman Sachs Market Strength Events
For investors tracking Goldman Sachs Clean, market strength indicators offer quantitative evaluation of mutual fund behavior. By using these indicators, traders can make more informed decisions about when to buy or sell Goldman Sachs Clean.
| 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 | |||
| Relative Strength Index | 50.1 |
Goldman Sachs Risk Indicators
Analyzing Goldman Sachs' basic risk indicators provides investors with a structured view of the risk-return trade-off for goldman mutual fund. By identifying the level of risk embedded in Goldman Sachs' investment, investors can make informed decisions about position sizing.
| 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
Coverage intensity for Goldman Sachs Clean matters because narrative visibility can influence sentiment, participation, and volatility around the name. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.
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