Facebook Double Exponential Smoothing

FB -- USA Stock  

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Investors can use this prediction interface to forecast Facebook historic prices and determine the direction of Facebook 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 Facebook 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 Facebook systematic risks associated with finding meaningful patterns of Facebook fundamentals over time. Additionally see Historical Fundamental Analysis of Facebook to cross-verify your projections.
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Horizon     30 Days    Login   to change
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for Facebook works best with periods where there are trends or seasonality.
Given 30 days horizon, the value of Facebook on the next trading day is expected to be 199.579401

Facebook Prediction Pattern

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Facebook Forecasted Value

Market Value
199.36
December 6, 2019
195.67
Downside
199.58
Expected Value
203.49
Upside

Model Predictive Factors

AICAkaike Information CriteriaHuge
BiasArithmetic mean of the errors -0.3188
MADMean absolute deviation1.8669
MAPEMean absolute percentage error0.0099
SAESum of the absolute errors110.1469
When Facebook prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any Facebook trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent Facebook observations are given relatively more weight in forecasting than the older observations.

Volatility Measures

Facebook Risk Indicators

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