Soft information in public firms’ quarterly earnings calls: Isolating the effects of value-relevant information and linguistic tone in financial text

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Volume Title
School of Business | Master's thesis
Date
2023
Major/Subject
Mcode
Degree programme
Finance
Language
en
Pages
82 + 4
Series
Abstract
In this thesis, I study the effects that the soft information in public firms’ quarterly earnings call transcripts have on stock returns. More specifically, I measure both the value-relevant information (sentiment) communicated in the earnings calls as well as the linguistic tone of the statements, by studying firms’ cumulative abnormal returns following quarterly earnings calls, both on portfolio-level and with a regression analysis on earnings call -level. My findings can be divided into methodological contributions and the uncovered financial phenomena. Firstly, I provide strong evidence in support of utilizing large language model -based solutions in extracting sentiment information from financial texts, as opposed to the dictionary-based methods that have been predominant in the financial academic literature so far. Furthermore, I show that using a tool like this together with a dictionary-based method that is designed to measure the linguistic tone of financial text makes it possible to isolate the two effects. Leveraging these benefits of my approach, I recognize three distinct stock return phenomena related to either earnings call sentiment or tone. Firstly, I find a strong positive relation between the sentiment of an earnings call Q&A session and the cumulative abnormal returns for that firm. Moreover, unlike some of the previous studies, I find that this stock price impact is nowadays practically immediate, with this information being incorporated into stock prices in the initial reaction period. Secondly, I find evidence that the sentiment information in the calls’ presentation section leads to a relatively similar immediate stock price reaction, but then to a subsequent reversal, that makes the long-term informational value in this section non-significant. Finally, I find that when controlling for the value-relevant information, a higher linguistic tone of the call’s presentation section predicts lower abnormal returns, in line with the theory of strategic communication, which states that managers use of a more positive tone constitutes bad news due to their incentives to downplay negative news. I find this negative stock price reaction to be immediate only for firms that reported a negative earnings surprise, whereas firms that reported positive earnings surprise this effect takes longer to be incorporated into share prices.
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Thesis advisor
Knüpfer, Samuli
Keywords
earnings call, sentiment analysis, linguistic tone, abnormal returns
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