A new methodology for generating and combining statistical forecasting models to enhance competitive event prediction

2012 ◽  
Vol 218 (1) ◽  
pp. 163-174 ◽  
Author(s):  
Stefan Lessmann ◽  
Ming-Chien Sung ◽  
Johnnie E.V. Johnson ◽  
Tiejun Ma
Keyword(s):  
Statistical Forecasting ◽  
Forecasting Models ◽  
Event Prediction

Forecast combination and the Bank of England's suite of statistical forecasting models

2008 ◽  
Vol 25 (4) ◽  
pp. 772-792 ◽  
Author(s):  
George Kapetanios ◽  
Vincent Labhard ◽  
Simon Price
Keyword(s):  
Forecast Combination ◽  
Statistical Forecasting ◽  
Forecasting Models

Optimizing statistical forecasting models in real time with bayesian component using´big data´ in marketing

2017 ◽  
Vol 08 (05) ◽  
pp. 17027-17036
Author(s):  
Antonio Boada ◽  
◽  
Ivelis Montilla ◽  
Francisco Jaramillo ◽  
◽  
...  
Keyword(s):  
Big Data ◽  
Real Time ◽  
Statistical Forecasting ◽  
Forecasting Models

Election Forecasting: Principles and Practice

2005 ◽  
Vol 7 (2) ◽  
pp. 145-164 ◽  
Author(s):  
Michael S. Lewis-Beck
Keyword(s):  
United States ◽  
United Kingdom ◽  
Statistical Models ◽  
Lead Time ◽  
Statistical Modelling ◽  
The United States ◽  
Statistical Forecasting ◽  
Election Forecasting ◽  
Forecasting Models ◽  
The United Kingdom

To forecast an election means to declare the outcome before it happens. Scientific approaches to election forecasting include polls, political stock markets and statistical models. I review these approaches, with an emphasis on the last, since it offers more lead time. Consideration is given to the history and politics of statistical forecasting models of elections. Rules for evaluating such models are offered. Examples of actual models come from the United States, France and the United Kingdom, where this work is rather new. Compared to other approaches, statistical modelling seems a promising method for forecasting elections.

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