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Can Textual Analysis solve the Underpricing Puzzle? A US REIT Study

Author

Listed:
  • Nino Paulus
  • Marina Koelbl
  • Wolfgang Schäfers

Abstract

Although many theories aim to explain IPO underpricing, initial-day returns of US REIT IPOs remain a “puzzle”. Considering equity offerings, literature provides several theories for the occurrence of underpricing. Theories on asymmetric information and value uncertainty based on Rock’s “winner’s curse” (1986) and Beatty and Ritter (1986) were among the first. Since then, the literature on REIT IPOs has focused on indirect respectively quantitative proxies for information asymmetries between REITs and investors to determine IPO underpricing. This study, however, proposes textual analysis to exploit the qualitative information, revealed through one of the most important documents during the IPO process – Form S-11, as a direct measure of information asymmetries. To our knowledge, this is the first study which applies textual analysis to corporate disclosures of US REITs in order to explain IPO underpricing. Specifically, we determine the level of uncertain language in the prospectus, as well as its similarity to recently filed registration statements, to assess whether textual features can solve the underpricing puzzle. To do so, we have gathered all prospects and data regarding firm characteristics, offering characteristics, third-party certification and market conditions for US equity REIT IPOs from January 1996 to December 2019. Our overall sample includes 114 IPOs for which we first clean the prospects to reduce linguistic complexity and facilitate the textual analysis procedure. Afterwards the level of uncertainty is derived using the Loughran and McDonald (2011) sentiment wordlist for uncertainty and the similarity is calculated by mapping the documents onto a vector space model which enables us to measure the similarity between two vectors using cosine similarity (Hanley and Hoberg, 2010; Brown and Tucker, 2013). In accordance with Ferris et al. (2013), we assume that uncertain language makes it more difficult for potential investors to price the issue and thus increases underpricing. Furthermore, it is hypothesized that a higher similarity to previous filings indicates that the prospectus provides little useful information and thus does not resolve existing information asymmetries, leading to increased underpricing. Incorporating these measures into an OLS, contrary to expectations, we do not find a statistically significant association between uncertain language in Form S-11 and initial-day returns. This result is interpreted as suggesting that uncertain language in the prospectus does not reflect the issuer's expectations about the company's future prospects, but rather is necessary because of forecasting difficulties and litigation risk. Analyzing disclosure similarity instead, this study finds a statistically and economically significant impact of qualitative information on initial-day returns. Thus, REIT managers may reduce underpricing by voluntarily providing more information to potential investors in Form S-11. This demonstrates that textual analysis can in fact help to explain underpricing of US REIT IPOs, as qualitative information in Forms S-11 decreases information asymmetries between US REIT managers and investors, thus reducing underpricing. Consequently, REIT managers are incentivized to provide as much information as possible to reduce underpricing building (Sherman and Titman, 2002), while investors could use textual analysis to identify offerings that promise the highest returns.

Suggested Citation

  • Nino Paulus & Marina Koelbl & Wolfgang Schäfers, 2022. "Can Textual Analysis solve the Underpricing Puzzle? A US REIT Study," ERES 2022_45, European Real Estate Society (ERES).
  • Handle: RePEc:arz:wpaper:2022_45
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    Keywords

    Information Asymmetry; Initial public offering; Textual Analysis; Underpricing;
    All these keywords.

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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