The Effect of Issuer Conservatism on IPO Pricing and Performance*

Abstract

Based on a textual analysis of IPO prospectuses, we obtain a number of important findings regarding the relation between the conservatism in prospectuses, IPO pricing, and subsequent operating and stock return performance. First, prospectus conservatism is positively related to underpricing, with the relation more pronounced for technology than non-technology firms. Second, for non-technology IPOs, prospectus conservatism is able to predict the firm's post-IPO operating performance. Specifically, we find that conservatism is inversely related to the firm's operating performance for the three years following the IPO. However, this predictability is limited to non-technology IPOs. Finally, we find some evidence that for non-technology IPOs conservatism is inversely related to the firm's post-IPO abnormal stock return. We conclude that the conservatism contained in an IPO's prospectus contains useful information about pricing and subsequent operating and stock return performance. Moreover, prospectus conservatism for nontechnology IPOs deserves more attention from investors.

CEO-Speeches and Stock Returns

“…To assess the quality of their dictionary, the authors show that 73.8% of the General Inquirer dictionary's negative words do not have a negative meaning in financial documents and, in later work, demonstrate that none of the most frequently occurring negative words in the 10-K disclosures are included in the Henry (2008) dictionary (Loughran & McDonald, 2015). Due to its comprehensiveness and its appropriateness for financial documents, the LM dictionary has become the most widely used dictionary in business research and has been used to assess the textual sentiment of 10-K filings (Loughran & McDonald, 2011), earnings conference calls (Davis et al, 2015), news articles (García, 2013), or IPO prospectuses (Ferris et al, 2013;Jegadeesh & Wu, 2013 Kearney and Liu (2014) and Loughran and McDonald (2016).…”

“…Early content analyses of financial texts Davis & TamaSweet, 2012;Feldman et al, 2008;Ferris et al, 2013;Henry & Leone, 2016;Kothari et al, 2009;Larcker & Zakolyukina, 2012;Tetlock, 2007;Tetlock et al, 2008) utilized general English dictionaries such as the Harvard University's General Inquirer IV-4 4 dictionary, the dictionaries included in the Diction 5 software, or the Linguistic Inquiry Word Count 6 software. Henry (2008) is the first to compose a dictionary explicitly designed to examine the tone of financial documents.…”

“…Recent research has acknowledged the value not only of quantitative data disclosures but also of qualitative information, predominantly in the form of the textual sentiment of business communication. Sentiment is typically examined via content analyses which have been applied on several types of business communication such as annual reports (Feldman et al, 2008;Jegadeesh & Wu, 2013;Loughran & McDonald, 2011, 2015, earnings press releases Davis & Tama-Sweet, 2012;Henry, 2008;Henry & Leone, 2016;Huang et al, 2014), IPO prospectuses (Demers & Vega, 2008;Ferris et al, 2013;Jegadeesh & Wu, 2013), CEO letters (Boudt & Thewissen, 2016), and earnings conference calls (Davis et al, 2015;Doran et al, 2012;Larcker & Zakolyukina, 2012;Price et al, 2012). In general, these studies find that qualitative information is indeed processed by investors and helps to predict future accounting returns, stock returns, stock volatility, and stock trading volume.…”

Negation scope detection in sentiment analysis: Decision support for news-driven trading

“…In Ref. [26], the authors hand-checked a small set of negation scopes, arguing that the denial component is irrelevant when studying filings from initial public offerings (IPO). Finally, we note that negation scope detection is also a frequent research topic (e.g.…”

“…A principal advantage of discriminative models is that they allow for the inclusion of overlapping features of the input sequence, since each feature function can depend on observations from any iteration and more than one can be active. Dadvar et al [22] Not, *n't No, rather, hardly 5 Ferris et al [26] Not, *n't Nothing, nobody, none Nor, nay 7 Jia et al [19], Hogenboom et al [20] Not, *n't No, hardly, less, rarely, barely, never without 9…”