• Stock market returns and the content of annual report narratives.

      Yekini, Liafisu Sina; Wisniewski, Tomasz; Coventry University; University of Leicester (Taylor & Francis, 2015-12-01)
      This paper uses the tools of computational linguistics to analyze the qualitative part of the annual reports of UK listed companies. More specifically, the frequency of words associated with different language indicators is measured and used to forecast future stock returns. We find that two of these indicators, capturing ‘activity’ and ‘realism’, predict subsequent price increases, even after controlling for a wide range of factors. Elevated values of these two linguistic variables, however, are not symptomatic of exacerbated risk. Consequently, investors are advised to peruse the annual report narratives, as they contains valuable information that may still not have been discounted in the prices.