Abstract
The original contribution of this paper is to empirically document the contagion of the Covid-19 on financial markets. We merge databases from Johns Hopkins Coronavirus Center, Oxford-Man Institute Realized Library, NYU Volatility Lab, and St-Louis Federal Reserve Board. We deploy three types of models throughout our experiments: (i) the Susceptible-Infective-Removed (SIR) that predicts the infections’ peak on 2020-03-27; (ii) volatility (GARCH), correlation (DCC), and risk-management (Value-at-Risk (VaR)) models that relate how bears painted Wall Street red; and, (iii) data-science trees algorithms with forward prunning, mosaic plots, and Pythagorean forests that crunch the data on confirmed, deaths, and recovered Covid-19 cases and then tie them to high-frequency data for 31 stock markets.
Highlights
The COVID-19 pandemic hit the world economy, without anyone knowing, at light-speed, leading to partial unemployment and factories’ shutdown around the globe, leaving doctors, policymakers, businessmen, operational managers, data scientists, and citizens alike in disarray
The image shows that, among the leading directories, the most meaningful parent-child relationships are to be found with the EURO STOXX 50 (Stoxx50E) in red color; the Amsterdam (AEX), Brussels (BFX), and Australian (AORD) stock markets in orange color; the French CAC 40 (FCHI) and Dow Jones Industrial Average (DJI) in light green color; and, the Nordic stock markets of Copenhagen, Helsinki, and Stockholm (OMXC20, OMXHPI, OMXSPI) in purple colors
COVID-19 is drowning the macro-financial environment into a recession that it is too early to foreshadow
Summary
The COVID-19 pandemic hit the world economy, without anyone knowing, at light-speed, leading to partial unemployment and factories’ shutdown around the globe, leaving doctors, policymakers, businessmen, operational managers, data scientists, and citizens alike in disarray. Stock markets plunged in March–April 2020, due to the shocking news of the virus spreading around the world. Sharif et al (2020b) analyze the connectedness between the recent spread of COVID-19, oil price volatility shock, the stock market, geopolitical risk, and economic policy uncertainty in the US within a time-frequency framework. We seek to analyze how the sanitary crisis impacted economic activity based on various methodological frameworks: a Susceptible-Infective-Removed model (epidemiology); GARCH, Dynamic Conditional Correlation, and Value-at-Risk (finance); Decision Tree Algorithm with Forward Pruning, Mosaic Plot, and Pythagorean Forest (data science). We show, using operational research models, that asset markets were linked to the spread of the COVID-19 stocks panic across the globe.
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