GOLDMAN SACHS Mutual Fund Forward View - Triple Exponential Smoothing
| GLPIX Fund | USD 42.82 0.31 0.73% |
The Triple Exponential Smoothing forecast shown here for GOLDMAN SACHS is reference data produced from its historical price series. The projected value and error measures below serve as reference information. This data is provided for reference and analytical review. The Triple Exponential Smoothing output serves as one input among many for analytical review.
The Triple Exponential Smoothing forecasted value of Goldman Sachs Mlp on the next trading day is expected to be 42.95 with a mean absolute deviation of 0.21 and the sum of the absolute errors of 12.36.As with simple exponential smoothing, in triple exponential smoothing models past GOLDMAN SACHS observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Goldman Sachs Mlp observations. This Triple Exponential Smoothing reference page for GOLDMAN SACHS presents model-generated projections from historical price data for informational purposes. Triple Exponential Smoothing Price Forecast For the 28th of March
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Goldman Sachs Mlp on the next trading day is expected to be 42.95 with a mean absolute deviation of 0.21 , mean absolute percentage error of 0.07 , and the sum of the absolute errors of 12.36 .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's 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
Forecasting Goldman Sachs Mlp for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. The current forecast range spans downside near 42.30 and upside near 43.61.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Triple 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 | Huge |
| Bias | Arithmetic mean of the errors | 0.0406 |
| MAD | Mean absolute deviation | 0.206 |
| MAPE | Mean absolute percentage error | 0.0052 |
| SAE | Sum of the absolute errors | 12.3606 |
Other Forecasting Options for GOLDMAN SACHS
The distribution of GOLDMAN SACHS's daily returns is typically non-normal, with fatter tails than a Gaussian model predicts. This can reveal hidden support and resistance zones in GOLDMAN SACHS's chart that simple price charts miss. The slope of GOLDMAN SACHS's linear regression channel quantifies trend direction and strength over a chosen lookback period. Divergences between OBV and price can foreshadow trend changes in GOLDMAN.GOLDMAN SACHS Related Equities
GOLDMAN SACHS's market space within the Energy Limited Partnership space is best grasped by looking at the firms listed below. Revenue and margin checks across this group help investors set expectations for GOLDMAN SACHS's results. Peer review is most useful when paired with absolute pricing and trend checks. The peer review below gives a clear framework for judging GOLDMAN SACHS's standing among rivals.
| Risk & Return | Correlation |
GOLDMAN SACHS Market Strength Events
Market strength indicators for GOLDMAN SACHS give insight into the mutual fund's responsiveness to broader forces. These indicators are useful for traders seeking optimal timing for positions in Goldman Sachs Mlp. Market strength analysis for Goldman Sachs Mlp works best when combined with volume and volatility data. For GOLDMAN SACHS, strength indicators are a practical complement to price and fundamental analysis.
| Rate Of Daily Change | 1.01 | |||
| Day Median Price | 42.82 | |||
| Day Typical Price | 42.82 | |||
| Price Action Indicator | 0.16 | |||
| Period Momentum Indicator | 0.31 | |||
| Relative Strength Index | 72.66 |
GOLDMAN SACHS Risk Indicators
A thorough review of GOLDMAN SACHS's risk indicators is an important first step in forecasting its price. Quantifying the risk involved in GOLDMAN SACHS's allows investors to make better decisions about entry, sizing, and hedging. The assessment of GOLDMAN SACHS's risk indicators plays a key role in managing investment exposure. Identifying the magnitude of risk in GOLDMAN SACHS's provides context to choose between accepting or hedging exposure.
| Mean Deviation | 0.5155 | |||
| Standard Deviation | 0.6365 | |||
| Variance | 0.4052 | |||
| Downside Variance | 0.3181 | |||
| Semi Variance | -0.05 | |||
| Expected Short fall | -0.65 |
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 Mlp shows when the security is attracting above-average attention from contributors and market observers. The practical risk is that faster visibility can increase both interest and skepticism at the same time.
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