本研究以2006年至2018年間臺灣初次上市公司進行研究，探討媒體情緒對首次公開發行（IPO）首日報酬折價的影響。在公司公開發行的過程中，媒體扮演著傳遞訊息的重要角色，透過媒體報導，投資人可以獲得公司相關資訊，並進行投資決策。由於市場上之散戶投資人通常皆缺乏專業知識，投資時大多倚靠媒體所傳播之大眾化資訊進行決策，因此我們認為媒體新聞中所隱含之情緒會影響投資者的信念，進而會影響投資者對IPO股票之需求。本研究使用深度學習提取新聞文章中的情感，將媒體情緒作為投資人情緒之代理變數，探討媒體情緒與文章語氣與IPO首日報酬之關聯性。本研究實證結果顯示，新聞報導中的情緒向度和語氣與IPO首日報酬呈現正向相關，表示媒體情緒越正向，IPO首日報酬折價現象越明顯。

This study empirically investigates the effect of media sentiment on initial public offering (IPO) underpricing. Media plays a critical role in conveying information. During the IPO process, the issuers become visible to the potential investors in the market through information reported by media. We consider that media news will affect the beliefs of investors, which in turn will have an impact on the investor demand for IPO shares. In this study, we use a deep learning framework to extract the sentiment in news articles. Using a sample of 151 issuing firms listed on the Taiwan Stock Exchange (TWSE) from 2006 to 2018, we find that positive tone and strong modals included in news articles exert positive impacts on IPO first-day returns, which provides some information supporting the conjecture that sentiments in news article can affect investor beliefs.

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