Starbucks Polynomial Regression

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SBUX -- USA Stock  

Earning Report: January 23, 2020  

Investors can use this prediction interface to forecast Starbucks historic prices and determine the direction of Starbucks 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 Starbucks 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 Starbucks Corporation systematic risks associated with finding meaningful patterns of Starbucks fundamentals over time. Additionally take a look at Historical Fundamental Analysis of Starbucks to cross-verify your projections.
Horizon     30 Days    Login   to change
Starbucks polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Starbucks Corporation as well as the accuracy indicators are determined from the period prices.
Given 30 days horizon, the value of Starbucks Corporation on the next trading day is expected to be 91.823062

Starbucks Prediction Pattern

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Starbucks Forecasted Value

Market Value
January 17, 2020
Expected Value

Model Predictive Factors

AICAkaike Information Criteria117.9804
BiasArithmetic mean of the errors None
MADMean absolute deviation0.7357
MAPEMean absolute percentage error0.0085
SAESum of the absolute errors44.8784
A single variable polynomial regression model attempts to put a curve through the Starbucks 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

Starbucks Risk Indicators