Autoeconometrics modeling method

• US 9,547,477 B2
• Filed: 10/23/2013
• Issued: 01/17/2017
• Est. Priority Date: 02/11/2009
• Status: Active Grant

• Current Assignee: Johnathan Mun
• Original Assignee: Johnathan Mun
• Inventors: Mun, Johnathan
• Primary Examiner(s): ALHIJA, SAIF A
• Application Number:
  US14/061,099
• Publication Number:
  US 20140052423A1
• Time in Patent Office: 1,182 Days
• Field of Search: 703/2
• US Class Current: 1/1
• CPC Class Codes: G06F 7/60 Methods or arrangements for performing computations using a digital non-denominational number representation, i.e. number representation without radix; Computing devices using combinations of denominational and non-denominational quantity representations , e.g. using difunction pulse trains, STEELE computers, phase computers conversion of digital data to or from non-denominational form H03M5/00, H03M7/00
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03

Abstract

A method and system allowing the ability to automatically and systematically run thousands and even millions of combinations and permutations of regression, forecasting and econometric trials to determine the best-fitting predictive model.

Claims

1. A non-transitory computer-readable medium that stores computer-executable instructions that are executable by a computer processor, the instructions when executed embodying a method for determining the best fitting econometric models for explaining a set of variables that comprises the steps of:

receiving (i) an input dataset comprising one or more sets of initial independent variables for insertion into a data grid, (ii) an input selection of criteria identifying types of econometric models to analyze, and (iii) a p-value cut-off threshold used to eliminate variables when performing an econometric model analysis;

generating one or more sets of intermediate independent variables derived from said one or more sets of initial independent variables;

generating a plurality of econometric models which are based on said selection criteria and said one or more sets of initial and intermediate independent variables, wherein each model of said plurality of models contains one or more independent variable from said one or more sets of initial and intermediate independent variables;

calculating p-value for each dependent variable contained in each model of said plurality of models;

storing each calculated p-value in memory;

eliminating one or more of said one or more independent variables from each of said models as insignificant whenever said one or more independent variables have a p-value greater than said p-value cut-off threshold; and

presenting a report of best-fitting models wherein all of the independent variables'"'"' p-value is greater than said p-value cut-off threshold.

2. A computer implemented method for determining the best fitting econometric models for explaining a set of variables, the method comprising the steps of:

receiving (i) an input dataset comprising one or more sets of initial independent variables for insertion into a data grid, (ii) an input selection of criteria identifying types of econometric models to analyze, and (iii) a p-value cut-off threshold used to eliminate variables when performing an econometric model analysis;

generating one or more sets of intermediate independent variables derived from said one or more sets of initial independent variables;

generating a plurality of econometric models which are based on said selection criteria and said one or more sets of initial and intermediate independent variables, wherein each model of said plurality of models contains one or more independent variable from said one or more sets of initial and intermediate independent variables;

calculating a p-value for each dependent variable contained in each model of said plurality of models;

storing each calculated p-value in memory;

eliminating one or more of said one or more independent variables from each of said models as insignificant whenever said one or more independent variables have a p-value greater than said p-value cut-off threshold; and

presenting a report of best-fitting models wherein all of the independent variables'"'"' p-value is greater than said p-value cut-off threshold.

3. A system comprising a processor and a memory that stores computer-executable instructions that are executable by the processor, the instructions when executed embodying a method for determining the best fitting econometric models for explaining a set of variables that comprises the steps of:

receiving (i) an input dataset comprising one or more sets of initial independent variables for insertion into a data grid, (ii) an input selection of criteria identifying types of econometric models to analyze, and (iii) a p-value cut-off threshold used to eliminate variables when performing an econometric model analysis;

generating one or more sets of intermediate independent variables derived from said one or more sets of initial independent variables;

generating a plurality of econometric models which are based on said selection criteria and said one or more sets of initial and intermediate independent variables, wherein each model of said plurality of models contains one or more independent variable from said one or more sets of initial and intermediate independent variables;

calculating a p-value for each dependent variable contained in each model of said plurality of models;

storing each calculated p-value in memory; and

eliminating one or more of said one or more independent variables from each of said models as insignificant whenever said one or more independent variables have a p-value greater than said p-value cut-off threshold; and

presenting a report of best-fitting models wherein all of the independent variables'"'"' p-value is greater than said p-value cut-off threshold.