This paper identifies robust determinants of US stock price movements in the economic shadow of the COVID-19 crisis and in the presence of model uncertainty, using several influential factors highlighted in relevant research. Our investigation performs an extreme bounds analysis (EBA), a global sensitivity framework capable of handling the problem of model uncertainty. We document that excess market returns, term spread, implied volatility, oil, Twitter-based economic uncertainty, and European and Chinese stock returns are the only variables that are robust to all possible variations in the condition set of information. The results also reveal the irrelevance of newly reported COVID-19 cases and deaths as novel drivers that contribute to the formation stock prices, thus lending support to the "psychophysical numbing" phenomenon.Copyright (c) 2022 Borsa Istanbul Anonim S , irketi. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).