This study examines whether language disclosed in the Management Discussion and Analysis (MD&A) of US Real Estate Investment Trusts (REITs) provides signals regarding future firm performance and thus generates a market response.
This research conducts textual analysis on a sample of approximately 6,500 MD&As of US REITs filed by the SEC between 2003 and 2018. Specifically, the Loughran and Mcdonald (2011) financial dictionary, and a custom dictionary for the real estate industry created by Ruscheinsky et al. (2018), are employed to determine the inherent sentiment, that is, the level of pessimistic or optimistic language for each filing. Thereafter, a panel fixed-effects regression enables investigating the relationship between sentiment and future firm performance, as well as the markets’ reaction.
The empirical results suggest that higher levels of pessimistic (optimistic) language in the MD&A predict lower (higher) future firm performance. Hereby, the use of a domain-specific real estate dictionary, namely that developed by Ruscheinsky et al. (2018) leads to superior results. Corresponding to the notion that the human psyche is affected more strongly by negative than positive news (Rozin and Royzman, 2001), the market responds solely to pessimistic language in the MD&A.
The results suggest that the market can benefit from textual analysis, as investigating the language in the MD&A reduces information asymmetries between US REIT managers and investors.
This is the first study to analyze exclusively US REITs, whether language in the MD&A is predictive of future firm performance and whether the market responds to textual sentiment.
