Can Optimism in Press Releases Increase Abnormal Stock Returns? - An Event Study and Text-Analysis of Press Releases Issued by FinTech Companies under IFRS and US GAAP

Abstract

Purpose The purpose of our study is to investigate and compare the level of optimism in press releases regarding R&D operations for FinTech companies under US GAAP and IFRS and how it affects abnormal stock returns under these two accounting standards. Research Design In order to conduct this study, an event study is used with 3, 5 and 11-days event windows, a 30-days estimation window and a gap of 10 trading days. The market model is assumed. As independent variable, optimism scores are applied, calculated by the text-analysis tool DICTION from each press release. These are then regressed against the cumulative abnormal return from each observation. The sample is divided into two groups; (i) FinTech companies under IFRS and (ii) FinTech companies under US GAAP. The IFRS group has 233 press releases and the US GAAP group has 234 press releases and thus the total sample is 467. Findings Our study finds that press releases by IFRS firms experience negative abnormal returns while press releases by US GAAP firms experience positive abnormal returns, when capturing the level of optimism by DICTION. Our results are significant on 10% confidence level for our 3- day event window. Therefore, the opposite reactions are explained by higher stock price informativeness in R&D capitalisation under IFRS relation to an expensing requirement under US GAAP. Additional information from FinTech companies under IFRS could be seen as superfluous as the relevance of financial statements is high, and thus stock market participants will question the underlying reason for the announcement. For FinTech companies under US GAAP, additional information will reduce asymmetric information and thus provide value. Conclusion and Implications Optimism in business communication such as press releases has an effect on abnormal stock return in FinTech companies under US GAAP (positive) and IFRS (negative). However, a study with a bigger sample would make results more generalisable.