MD&A Disclosure and Performance of U.S. REITs: The Information Content of Textual Tone

Textual sentiment analysis provides an increasingly important approach to address many pivotal questions in behavioral finance. Not least because in today’s world a huge amount of information is stored as text instead of numeric data (Nasukawa and Nagano, 2001). As an example, Chen et al. (2014) analyzes articles published on Seeking Alpha and finds the fraction of negative words to be correlated with contemporaneous and subsequent stock returns. Tetlock (2007) emphasizes that high values of media pessimism induce downward pressure on market prices. Moreover, Li (2010) and Davis et al. (2012) investigate corporate disclosures such as earnings press releases or annual and quarterly reports and find disclosure tone to be associated with future firm performance. Sentiment analysis has also garnered increased attention in related real estate research in recent years. For example, Ruscheinsky et al. (forthcoming) extract sentiment from newspaper articles and analyze the relationship between measures of sentiment and US REIT prices. However, sentiment analysis in real estate still lacks behind. Whereas related research in accounting and finance investigates multiple disclosure outlets like news media, public corporate disclosures, analyst reports, and internet postings, real estate literature only covers a limited spectrum. Although, corporate disclosures are a natural source of textual sentiment for researchers since they are official releases that come from insiders who have better knowledge of the firm than outsiders (e.g. media-persons) they have not yet been analyzed in a real estate context (Kearney and Liu, 2014). By observing annual and quarterly reports of U.S. REITs present in the NAREIT over a 15-year timespan (2003 - 2017), this study examines whether the information disclosed in the Management’s Discussion and Analysis (MD&A) of U.S. REITs is associated with future firm performance and generates a market response. The MD&A is particularly suitable for the analysis because the U.S. Securities and Exchange Commission (SEC) mandates publicly traded firms to signal expectations regarding future firm performance in this section (SEC, 2003). To assess the tone of the MD&A, the Loughran and McDonald (2011) financial dictionary as well as a machine learning approach are employed. In order to allow a deeper understanding of disclosure practices, the study also observes readability of the MD&A and topics discussed in this section to examine whether those aspects are linked to either disclosure tone or future firm performance. To the best of my knowledge, this is the first study to analyze exclusively for REITs whether language in the MD&A is associated with future firm performance and if the market responds to unexpected levels of sentiment.