Investors’ sentiment and equity markets during COVID-19 period: a quantile regression approach and wavelet analysis

Abstract

The purpose of this study is to investigate the relationship between investor sentiment and leading equity market indices from the U.S., Europe, Asia, and globally between January 2020 and June 2022. The methodological approaches utilized are quantile regression and wavelet analysis. The results of quantile regression suggested that Google Search Volume (GSV) and Twitter-based Market Uncertainty Index (TMU) negatively influenced the equity indices at lower quantiles. The wavelet coherence analysis highlighted that, at lower frequency bands, GSV moves in sync with the S&P 500, NASDAQ Composite, Dow Jones Industrials, and FTSE 100 but not with the DAX, CAC 40, TOPIX, Nikkei 225, or MSCI. Nonetheless, when the TMU was used to measure investors’ sentiment, the results revealed that the whole series was out of phase.

Keywords

• investors’ sentiment
• equity markets
• COVID-19
• quantile regression
• wavelet coherence
• wavelet cross-correlation