This study introduces a novel index based on expectations concordance for explaining stock-price volatility when historically unique events cause unforeseeable change and Knightian uncertainty in the process driving outcomes. Expectations concordance measures the degree to which non-repetitive events are associated with directionally similar expectations of future returns. Narrative analytics of daily news reports allow for assessment of bullish versus bearish views in the stock market. Increases in expectations concordance across all KU events leads to reinforcing effects and an increase in stock market volatility. Lower expectations concordance produces a stabilizing effect wherein the offsetting views reduce market volatility. The empirical findings hold for ex-post and ex-ante measures of volatility and for OLS and GARCH estimates.