Alcoa Polynomial Regression

AA -- USA Stock  

USD 21.67  0.21  0.98%

Investors can use this prediction interface to forecast Alcoa historic prices and determine the direction of Alcoa Corporation 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 Alcoa 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 Alcoa Corporation systematic risks associated with finding meaningful patterns of Alcoa fundamentals over time. Check also Historical Fundamental Analysis of Alcoa to cross-verify your projections.
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Alcoa polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Alcoa Corporation as well as the accuracy indicators are determined from the period prices.
Given 30 days horizon, the value of Alcoa Corporation on the next trading day is expected to be 24.922983

Alcoa Prediction Pattern

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Alcoa Forecasted Value

September 21, 2019
21.67
Market Value
24.92
Expected Value
33.67
Upside

Model Predictive Factors

AICAkaike Information Criteria120.0213
BiasArithmetic mean of the errors None
MADMean absolute deviation0.8136
MAPEMean absolute percentage error0.0391
SAESum of the absolute errors50.4445
A single variable polynomial regression model attempts to put a curve through the Alcoa historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm

Volatility Measures

Alcoa Risk Indicators

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