  Earnings calls influence stock prices and are traditionally analyzed using
sentiment and linguistic traces. Our research introduces a "Topic-Switching
Index," a novel metric quantified through the transformer model FinBERT, to
measure managerial evasion during Q$\&$A sessions in earnings calls. We find a
negative correlation between this index and subsequent stock prices, indicating
that investors penalize managerial evasiveness. This study is the first to
quantify such evasive tactics, adding a new dimension to how earnings calls are
understood and suggesting that topic shifting is an overlooked but significant
factor. We also show the predictability of the index under three different
classifier models and it stands out in all circumstances.
