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Value of financial releases' textual content: Evidence from OMX NASDAQ Helsinki
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School of Business |
Master's thesis
Electronic archive copy is available via Aalto Thesis Database.
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en
Pages
61
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Abstract
OBJECTIVE OF THE STUDY:
In this thesis I analyze do annual statement releases of Finnish companies' include information about the value of a company's equity that the computational text analysis is able to extract. Furthermore, I investigate is this information immediately incorporated into the stock market prices or do markets under- or overreact to the information content of annual statement releases. The secondary focus is to analyze the readability of the annual statement releases' impact post-announcement period's market reaction.
DATA AND METHODOLOGY:
The study consists of 725 annual statement release from OMX NASDAQ Helsinki, which take place from 2007 to 2014. I use the dictionary approach and Loughran and McDonald -dictionaries to calculate positive and negative words. To determine the sentiment of the releases, I use proportional and "term-frequency - inverse document frequency" - word weights. To measure readability, I use the amount of words as a proxy. Finally, I calculate cumulative abnormal returns based on the market model and use the event study methodology to investigate sentiment's and readability's impact on cumulative abnormal returns.
FINDINGS OF THE STUDY:
At market-level, I find that the yearly annual statement releases' average sentiment correlates moderately with the changes in the market index. At firm-level, I find that increase of positive words are linked to the event day's positive shift in the abnormal returns and to the positive drift in the next five days. Furthermore, I find that negative words and "term-frequency - inverse document frequency" word weights are poor predictors of cumulative abnormal returns. Finally, I find no support for the hypothesis that the releases' length proxies readability and impact on post-event returns.