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Christian-Albrechts-Universität zu Kiel

Macroeconomic Forecasting and Market Analysis with Newspaper Articles

Abstract

dc:description.abstract

The overarching theme of this dissertation is whether a particular type of alternative data, namely text data, can improve forecasts of key macroeconomic aggregates or help explain the financial market dynamics. Large-scale text data have become available only relatively recently and have attracted substantial attention in the empirical macroeconomic and financial literature. My central research question concerns which dimensions of news data are informative for macroeconomic forecasting and financial analysis, and how these dimensions should be adapted to the variable of interest. The existing literature has predominantly focused on three types of text-based indicators. The first strand constructs sentiment measures that quantify the positive or negative tone of news articles and shows that such measures can predict macroeconomic activity. A second strand uses topic indicators, capturing variation in the intensity with which different themes are covered in the media. A third, more recent strand combines these approaches by assigning sentiment to individual topics, and therefore produces topic-specific sentiment measures that reflect both the thematic focus and the tone of news coverage. My work adopts this hybrid perspective but departs from standard off-the-shelf methods by asking whether commonly used text dimensions are appropriate for the specific forecasting question at hand. Rather than relying directly on existing lexicons or unsupervised topics, I adapt sentiment analysis and topic modelling so that the resulting indicators capture the economically relevant information for the variable being forecast, whether GDP, consumption, investment, or stock returns.

Degree

thesis:*
Level thesis:degree_level
thesis.doctoral
Grantor dc:publisher
Christian-Albrechts-Universität zu Kiel
Year
2026

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Okuneva, Mariia
Contributors dc:contributor
  • Carstensen, Kai
  • Demetrescu, Matei

Subjects

dc:subject × 5

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:macau.uni-kiel.de:macau_mods_00008038

Chain of custody

source
Harvested from
Christian-Albrechts Universität Kiel
Base URL
macau.uni-kiel.de/servlets/OAIDataProvider
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Okuneva, Mariia. Macroeconomic Forecasting and Market Analysis with Newspaper Articles. thesis.doctoral thesis, Christian-Albrechts-Universität zu Kiel, 2026. https://macau.uni-kiel.de/receive/macau_mods_00008038