Home Depot Polynomial Regression

Investors can use this prediction interface to forecast Home Depot historic prices and determine the direction of The Home Depot 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 Home Depot 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 The Home Depot systematic risks associated with finding meaningful patterns of Home Depot fundamentals over time. Please also check Risk vs Return Analysis.
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Home Depot polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for The Home Depot as well as the accuracy indicators are determined from the period prices.
A single variable polynomial regression model attempts to put a curve through the Home Depot 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
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