Natural Language Processing in Finance and Empirical Macroeconomics

Research output: ThesisDoctoral Thesis

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Abstract

The three essays collected in this Ph.D. thesis apply Natural Language Processing
(NLP) tools to asset pricing and household finance. The first essay identifies
the triggers of flight-to-safety episodes from financial news and highlights the
importance of political, geopolitical, and macroeconomic risks. The second essay
shows how the inflation expectation gap between households and experts widens
with narrative disagreement between general and specialized newspapers about
the demand or supply origins of inflation. The third essay demonstrates how the
temporal references of newspaper articles can add predictive power toward future
excess stock returns above and beyond their tone and topics.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Tilburg University
Supervisors/Advisors
  • Baele, Lieven, Promotor
  • de Jong, Frank, Promotor
Award date10 Oct 2025
Place of PublicationTilburg
Publisher
Print ISBNs978 90 5668 781 6
DOIs
Publication statusPublished - 2025

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