Citigroup Simple Regression

C -- USA Stock

Earnings Call

Investors can use this prediction interface to forecast Citigroup historic prices and determine the direction of Citigroup 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 Citigroup 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 Citigroup systematic risks associated with finding meaningful patterns of Citigroup fundamentals over time. Check also Historical Fundamental Analysis of Citigroup to cross-verify your projections.
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 Horizon 30 Days     to change
Simple Regression model is a single variable regression model that attempts to put a straight line through Citigroup 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 Citigroup on the next trading day is expected to be 76.704548

Citigroup Forecasted Value

Market Value
75.33
December 12, 2019
76.70
Expected Value
Target Odds
 Above Odds Below Odds
80.55
Upside

Model Predictive Factors

 AIC Akaike Information Criteria 120.6481 Bias Arithmetic mean of the errors None MAD Mean absolute deviation 1.1459 MAPE Mean absolute percentage error 0.016 SAE Sum of the absolute errors 71.044
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 Citigroup historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Citigroup Technical Indicators

Citigroup 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

Citigroup Risk Indicators

 Mean Deviation 0.9847 Semi Deviation 1.07 Standard Deviation 1.26 Variance 1.6 Downside Variance 1.43 Semi Variance 1.15 Expected Short fall (1.13)
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