Stock market returns and the content of annual report narratives

Abstract

This paper uses the tools of computational linguistics to analyze the qualitative part of annual reports of UK listed companies. More specifically, the frequency of words associated with different language indicators is 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 annual report narratives, as they contain valuable information that may not yet have been discounted in the prices.

JEL classification:

• M41
• G12
• G14

• Content analysis
• Annual reports
• Stock market returns

Notes

1 Companies are often challenged on their narrative reporting by the FRC team. The challenges may relate to the lack of understandability, inconsistency of the text with the financial statements or to the business review section that may not appear fair, balanced or comprehensive. Most of the questions put forward to the Boards by FRC are confidential, while other individual issues can be widely publicized. It is also worth noting that FRC issued guidance on some of the narrative parts, including directors’ and strategic reports.

2 Please see http://www.dictionsoftware.com/published-studies/.

3 The structure of annual report narratives for banks and financial institutions departs significantly from what is norm for a typical company. These entities have to comply with IAS30—Disclosures in the Financial Statements of Banks and Similar Financial Institutions and the Basel Accord, consequently devoting a lot of space to describing issues such as liquidity and risk management. Some of the other content analysis studies performed in the UK context also excluded financial intermediaries (see for instance Clatworthy & Jones, 2003; Schleicher & Walker, 2010).

4 These fees are not necessarily prohibitive. At the time of writing this paper, Diction was priced at USD 219 per copy for educational use and USD 269 for corporate use.