Agilent Technologies Simple Regression

A -- USA Stock  

USD 77.90  0.33  0.43%

Investors can use this prediction interface to forecast Agilent Technologies historic prices and determine the direction of Agilent Technologies 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 Agilent Technologies 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 Agilent Technologies systematic risks associated with finding meaningful patterns of Agilent Technologies fundamentals over time. Check also Historical Fundamental Analysis of Agilent Technologies to cross-verify your projections.
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Horizon     30 Days    Login   to change
Simple Regression model is a single variable regression model that attempts to put a straight line through Agilent Technologies price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.
Given 30 days horizon, the value of Agilent Technologies on the next trading day is expected to be 71.479885

Agilent Technologies Prediction Pattern

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Agilent Technologies Forecasted Value

September 15, 2019
77.90
Market Value
71.48
Expected Value
76.50
Upside

Model Predictive Factors

AICAkaike Information Criteria120.2502
BiasArithmetic mean of the errors None
MADMean absolute deviation2.3826
MAPEMean absolute percentage error0.0332
SAESum of the absolute errors145.3412
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Agilent Technologies historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Volatility Measures

Agilent Technologies Risk Indicators

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