Quantifying the impact of COVID-19 on the US stock market: An analysis from multi-source information

08/25/2020
by   Asim Kumer Dey, et al.
0

We develop a novel temporal complex network approach to quantify the US county level spread dynamics of COVID-19. The objective is to study the effects of the local spread dynamics, COVID-19 cases and death, and Google search activities on the US stock market. We use both conventional econometric and Machine Learning (ML) models. The results suggest that COVID-19 cases and deaths, its local spread, and Google searches have impacts on abnormal stock prices between January 2020 to May 2020. In addition, incorporating information about local spread significantly improves the performance of forecasting models of the abnormal stock prices at longer forecasting horizons. On the other hand, although a few COVID-19 related variables, e.g., US total deaths and US new cases exhibit causal relationships on price volatility, COVID-19 cases and deaths, local spread of COVID-19, and Google search activities do not have impacts on price volatility.

READ FULL TEXT

page 1

page 2

page 3

page 4

12/25/2018

Multimodal deep learning for short-term stock volatility prediction

Stock market volatility forecasting is a task relevant to assessing mark...
12/13/2021

COVID-19 Forecasts via Stock Market Indicators

Reliable short term forecasting can provide potentially lifesaving insig...
10/01/2021

The Impacts of Mobility on Covid-19 Dynamics: Using Soft and Hard Data

This paper has the goal of evaluating how changes in mobility has affect...
10/02/2020

Commuting Network Spillovers and COVID-19 Deaths Across US Counties

This study explored how population mobility flows form commuting network...
09/28/2020

Modeling and analysis of the effect of COVID-19 on the stock price: V and L-shape recovery

The emergence of the COVID-19 pandemic, a new and novel risk factors, le...
01/02/2021

COVID19-HPSMP: COVID-19 Adopted Hybrid and Parallel Deep Information Fusion Framework for Stock Price Movement Prediction

The novel of coronavirus (COVID-19) has suddenly and abruptly changed th...