EconPapers    
Economics at your fingertips  
 

Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values

David Ardia, Keven Bluteau and Kris Boudt

International Journal of Forecasting, 2019, vol. 35, issue 4, 1370-1386

Abstract: The modern calculation of textual sentiment involves a myriad of choices as to the actual calibration. We introduce a general sentiment engineering framework that optimizes the design for forecasting purposes. It includes the use of the elastic net for sparse data-driven selection and the weighting of thousands of sentiment values. These values are obtained by pooling the textual sentiment values across publication venues, article topics, sentiment construction methods, and time. We apply the framework to the investigation of the value added by textual analysis-based sentiment indices for forecasting economic growth in the US. We find that the additional use of optimized news-based sentiment values yields significant accuracy gains for forecasting the nine-month and annual growth rates of the US industrial production, compared to the use of high-dimensional forecasting techniques based on only economic and financial indicators.

Keywords: Elastic net; Sentiment analysis; Time series aggregation; Topic-sentiment; US industrial production; Sentometrics (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207018302036
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:35:y:2019:i:4:p:1370-1386

DOI: 10.1016/j.ijforecast.2018.10.010

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Haili He ().

 
Page updated 2020-11-08
Handle: RePEc:eee:intfor:v:35:y:2019:i:4:p:1370-1386