Market Downturns and Asymmetric Tail Risk Transmission Speed in the US: Evaluating Macroeconomic Policy Effectiveness during and after the COVID-19 Pandemic

Abstract

This study examines how US market downturns affect the asymmetry in tail risk information transmission speed. It also evaluates how monetary and fiscal policies help mitigate this asymmetry during and after the COVID-19 pandemic. Using model-free measures of bad (disaster risk) and good (swift recovery) tail risk derived from daily options data, we obtain forward-looking tail risk information. Based on the TENET model, we construct daily networks for bad and good tail risk spillovers. Empirical results show that market downturns increase the asymmetry in bad and good tail risk transmission speed. Rising market illiquidity in downturns causes negative tail risk information to transmit faster than positive signals, amplifying the asymmetry. Although fiscal and monetary policies show average mitigation effects across the sample, event analysis shows they consistently reduce this asymmetry during the early COVID-19 phase. This suggests that unconventional macroeconomic interventions during extreme downturns more effectively mitigate asymmetric information transmission.