Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/229119
Authors: 
Diaz, Elena
Pérez-Quirós, Gabriel
Year of Publication: 
2020
Series/Report no.: 
ECB Working Paper No. 2505
Abstract: 
This paper develops a novel indicator of global economic activity, the GEA Tracker, which is based on commodity prices selected recursively through a genetic algorithm. The GEA Tracker allows for daily real-time knowledge of international business conditions using a minimum amount of information. We find that the GEA Tracker outperforms its competitors in forecasting stock returns, especially in emerging markets, and in predicting standard indicators of international business conditions. We show that an investor would have inexorably profited from using the forecasts provided by the GEA Tracker to weight a portfolio. Finally, the GEA Tracker allows us to present the daily evolution of global economic activity during the COVID-19 pandemic.
Subjects: 
Global Economic Activity
Commodity Prices
Factor Models
Variable Selection
Genetic Algorithm
Leading Indicators
JEL: 
F44
G17
Q02
Persistent Identifier of the first edition: 
ISBN: 
978-92-899-4451-9
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.