Effects of COVID-Induced Public Anxiety on European Stock Markets: Evidence From a Fear-Based Algorithmic Trading System

Abstract

The effect of COVID-induced public anxiety on stock markets, particularly in European stock market returns, is examined in this research. The search volumes for the notion of COVID-19 gathered by Google Trends and Wikipedia were used as proxies for COVID-induced public anxiety. COVID-induced public anxiety was shown to be linked with negative returns in European stock markets when a panel data method was used to a sample of data from 14 European stock markets from January 2, 2020 to September 17, 2020. Using an automated trading system, we used this finding to suggest investment methods based on COVID-induced anxiety. The findings of back-testing indicate that these techniques have the potential to generate exceptional profits. These results have significant consequences for government officials, the media, and investors.

Air travel demand forecasting based on big data: A struggle against public anxiety

“…Baidu and Google generate search engine data of each keyword (i.e., Baidu Index and Google Trend) based on the search volume of hundreds of millions of users according to specific formulas, this is, the weighted sum of the search times of each keyword in their search engines ( Yao et al, 2021 ). Both the Baidu Index ( Liang et al, 2022 ) and Google Trend ( Sun et al, 2022 ) can reflect the potential demand and the current focus. Considering that this paper studies the forecast of air travel demand in China, Baidu Index is a better choice.…”