Twitter 4 Period Moving Average

TWTR -- USA Stock  

USD 43.24  0.01  0.0231%

Investors can use this prediction interface to forecast Twitter historic prices and determine the direction of Twitter future trends based on various well-known forecasting models. However looking at historical price movement exclusively is usually misleading. Macroaxis recommends to always use this module together with analysis of Twitter historical fundamentals such as revenue growth or operating cash flow patterns. Although naive historical forecasting may sometimes provide an important future outlook for the firm we recommend to always cross-verify it against solid analysis of Twitter systematic risks associated with finding meaningful patterns of Twitter fundamentals over time. Also please take a look at Historical Fundamental Analysis of Twitter to cross-verify your projections.
Horizon     30 Days    Login   to change
A four-period moving average forecast model for Twitter is based on an artificially constructed daily price series in which the value for a given day is replaced by the mean of that value and the values for four preceding and succeeding time periods. This model is best suited to forecast equities with high volatility.
Given 30 days horizon, the value of Twitter on the next trading day is expected to be 43.16

Twitter Prediction Pattern

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Twitter Forecasted Value

September 21, 2019
Market Value
Expected Value

Model Predictive Factors

AICAkaike Information Criteria112.7532
BiasArithmetic mean of the errors -0.3362
MADMean absolute deviation0.8264
MAPEMean absolute percentage error0.0201
SAESum of the absolute errors47.9325
The four period moving average method has an advantage over other forecasting models in that it does smooth out peaks and troughs in a set of daily price observations of Twitter. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Twitter and therefore, it cannot be a useful forecasting tool for medium or long range price predictions

Volatility Measures

Twitter Risk Indicators