Event Sentiment and Cross-Country Herding Spillover Effects Using Machine Learning

This research study investigates herding behaviour and its cross-country spillover effects in the UK, US, China, and Pakistan stock markets in the presence of event sentiment. We used three machine learning models for the empirical investigation: support vector regression, single-layer neural networks, and multi-layer neural networks. The daily data set of the listed stocks has been used. The results suggest a significant predictability of the Twitter sentiment of Brexit 2016 and COVID-19. Cross-country herding spillover is also evident from the UK to Pakistan and the US in the case of Brexit 2016. Similarly, there is a herding spillover effect from China to Pakistan and UK stock markets. The overall results of machine learning models are more significant than linear regression models. Furthermore, the event sentiment improves the performance of the machine learning models. The study provides a deep insight for individual and institutional investors to take care of unpredicted events while constructing their international portfolios in these stock markets.