Multi-regime Forecasting Model for the Impact of COVID-19 Pandemic on Volatility in Global Equity Markets

Abstract

Using a multi-regime forecasting model, we investigate the impact of COVID-19 pandemic on market volatility. We show that daily number of active cases and the Curvature are significant predictors of daily cross-section of both realized volatility and the GJR-GARCH volatility in global equity markets. We estimate realized volatilities using intraday 5-minute returns for 46 country specific ETFs and daily GARCH volatilities are estimated using the stock market indices of 88 countries around the world. We find that stricter policy responses by individual countries, measured by higher OxCGRT Stringency Index levels, result in lower stock market volatilities while increased negative managerial sentiment, extracted from earnings call transcripts, causes an increase in realized volatilities.

Keywords: Multi-regime forecasting, COVID-19, coronavirus pandemic, volatility, Stringency Index, earnings call transcripts, sentiment, curvature

JEL Classification: G01, G12, G15