# General Mills Polynomial Regression

GIS -- USA Stock

## Fiscal Quarter End: November 30, 2019

Investors can use this prediction interface to forecast General Mills historic prices and determine the direction of General Mills 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 General Mills 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 General Mills systematic risks associated with finding meaningful patterns of General Mills fundamentals over time. Please also check Historical Fundamental Analysis of General Mills to cross-verify your projections.
 Symbol Refresh
 Horizon 30 Days     to change
General Mills polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for General Mills as well as the accuracy indicators are determined from the period prices.
Given 30 days horizon, the value of General Mills on the next trading day is expected to be 54.225939

## General Mills Prediction Pattern

 Backtest General Mills | General Mills Price Prediction | Buy or Sell Advice

## General Mills Forecasted Value

October 14, 2019
54.08
Market Value
54.23
Expected Value
Target Odds
 Above Odds Below Odds
57.57
Upside

## Model Predictive Factors

 AIC Akaike Information Criteria 117.1393 Bias Arithmetic mean of the errors None MAD Mean absolute deviation 0.4529 MAPE Mean absolute percentage error 0.0084 SAE Sum of the absolute errors 27.6287
A single variable polynomial regression model attempts to put a curve through the General Mills 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

## General Mills Technical Indicators

### General Mills Technical and Predictive Analytics

 Cycle Indicators Math Operators Math Transform Momentum Indicators Overlap Studies Pattern Recognition Price Transform Statistic Functions Volatility Indicators Volume Indicators

## Volatility Measures

### General Mills Risk Indicators

 Mean Deviation 0.8303 Semi Deviation 1.13 Standard Deviation 1.11 Variance 1.23 Downside Variance 1.43 Semi Variance 1.28 Expected Short fall (0.86)
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