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Is AI cable news-based economic policy uncertainty predicting travel and leisure stock returns in the USA, EU, and China

Bibliographic Data

ID21699586
AuthorsYunqian Bai (0000-0003-3981-8574, Beijing City University), Ojonugwa Usman (0000-0002-6459-9898, Istanbul Ticaret University, corresponding author), Oktay Ozkan (0000-0001-9419-8115, Tokat Gaziosmanpaşa Üniversitesi)
Year2025
Volume28
Issue17
Pages2733-2743
Publication date2025-09-02
Open AccessNo
TypeARTICLE
VenueCurrent Issues in Tourism (JOURNAL)
Journal identifiersISSN: 1368-3500 • E-ISSN: 1747-7603
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/13683500.2024.2440089
OpenAlexW4405399030
LanguageEN
Citations received1
References cited11

We investigate the predictive content of AI cable news-based economic policy uncertainty (TVEPU) for travel and leisure stock returns in the USA, European Union, and China. Using the Rolling Windows Wavelet Quantile Granger Causality technique, we find that the predictive content of TVEPU varies across time, frequencies, and quantiles. When the travel and leisure stock market is bearish or bullish, the predictive content of TVEPU is stronger in the long run. However, when the travel and leisure stock market is normal, the predictability is stronger in the short run. These findings are supported by the outcomes of the network connectedness analysis

China · Econometrics · Economics · European union · Financial economics · Geography · Granger causality · International economics · Predictability · Quantile · Social connectedness · Stock market · Energy, Environment, and Transportation Policies · Energy, Environment, Economic Growth · Market Dynamics and Volatility

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Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

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