Ford Motor Naive Prediction

Ford Motor Company -- USA Stock  

USD 11.93  0.010000  0.080000%

Investors can use this prediction interface to forecast Ford Motor historic prices and determine the direction of Ford Motor Company 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 Ford Motor 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 Ford Motor Company systematic risks associated with finding meaningful patterns of Ford Motor fundamentals over time. Additionally see Historical Fundamental Analysis of Ford Motor to cross-verify your projections.
Investment Horizon     30 Days    Login   to change
A naive forecasting model for Ford Motor is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Ford Motor Company value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.
Given 30 days horizon, the value of Ford Motor Company on the next trading day is expected to be 12.0

Ford Motor Prediction Pattern

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Ford Motor Forecasted Value

September 26, 2017
Market Value
Downside upside
Next Trading Day Expected Value
Target Price Odds
 Above  Below  
Upside upside

Model Predictive Factors

AICAkaike Information Criteria31.3365
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0416
MAPEMean absolute percentage error0.0036
SAESum of the absolute errors0.7067
This model is not at all useful as a medium-long range forecasting tool of Ford Motor Company. This model really is a simplistic model, and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly. Instead, consider using either the moving average model, or the more general weighted moving average model with a higher (i.e. greater than 1) number of periods, and possibly a different set of weights.