Decoding Relations between Geopolitical Risk and Financial Markets

This thesis examines the relationship between geopolitical risk and financial markets by analyzing two major geopolitical events: the Russia-Ukraine conflict and China-related tensions. Using Latent Dirichlet Allocation (LDA) topic modeling, it identifies key topics discussed in business media. Through ordinary least squares and quantile regression analyses, the thesis examines the relationship between topic sentiment (polarity) and hype (intensity), and financial market returns under different market conditions. For the Russia-Ukraine conflict, the study analyzes 11,929 Wall Street Journal articles published between 2014 and 2024, identifying 12 distinct topics. Among them, the Global Economy and Oil topics exhibit the strongest positive relation with oil returns in both sentiment and hype, particularly during bullish oil markets. Regarding China-related tensions, the thesis examines 13,784 Wall Street Journal articles from 2009 to 2024, uncovering 21 topics. The sentiment and hype associated with these topics demonstrate varying relationships with U.S. and Chinese stock market returns under different market conditions. This research provides valuable insights into the relationship between media discussions and market behavior during periods of geopolitical uncertainty.

Name thesis:degree_name

M.Sc. Management

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Faculty of Business

Department dc:contributor.department

Faculty of Business Programs

Grantor dc:publisher

Brock University

Year dc:date.issued

2025

Author dc:creator

• Babalola, Moyosore

Advisor dc:contributor.advisor

• Biktimirov, Ernest

• SOCIAL SCIENCES::Business and economics
• SOCIAL SCIENCES::Business and economics::Economics
• SOCIAL SCIENCES::Statistics, computer and systems science::Informatics, computer and systems science::Information and language technology
• SOCIAL SCIENCES::Business and economics::Business studies
• SOCIAL SCIENCES::Business and economics::Economics::Econometrics

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/10464/19388

OAI identifier oai:identifier

oai:brocku.scholaris.ca:10464/19388