Firm-level Business Uncertainty and the Predictability of the Aggregate U.S. Stock Market Volatility during the COVID-19 Pandemic

In this paper, we analyze the predictive role of firm-level business expectations and uncertainties derived from a panel survey of U.S. 1,750 business executives from 50 states for the realized variance (sum of daily squared log-returns over a month) of the S&P500 over the monthly period of September, 2016 to July, 2021. Unlike standard models, our predictive framework adopts a time-varying approach due to the existence of multiple structural breaks in the relationship between volatility and the predictors in the model, which in turn leads to statistically insignificant causal effects in a constant parameter set-up. Our time-varying results reveal the predictive power of firm-level business uncertainty is concentrated during the early part of the sample associated with the U.S.-China trade war, and towards the end of our data coverage in the wake of the outbreak of the COVID-19 pandemic. Since, in-sample predictability does not guarantee the same over an out-sample, we also conducted a full-fledged forecasting exercise to show that subjective expectations and uncertainties associated with sales growth rates and employment produces statistically significant predictability gains over January, 2020 to July, 2021, given an in-sample of September, 2016 to December, 2019. Our results suggest that subjective measures of business uncertainty at the firm-level indeed captures predictive information regarding aggregate stock market uncertainty which has important implications for investors and economic projections at the policy level.