上市櫃公司每月營收宣告對股價之影響

本研究採用事件研究法，觀察2015年1月至2019年12月間，台股市場中32種產業共1,470檔上市櫃個股，在月營收宣告期間，公司營收變動對於股價報酬所帶來的影響。首先，為了確認各個產業的營收宣告事件的確對股價造成波動，採用t檢定檢驗事件期間每日的異常報酬與累積異常報酬數據，證實每個產業於宣告日當日或是前後日，皆有正負與大小不等的異常報酬或是累積異常報酬存在的現象。其次，為瞭解未預期營收與股價報酬間的關聯程度，復採簡單迴歸模型，以未預期營收為自變數，而累積異常報酬為應變數，實證結果顯示：化學工業、水泥工業、半導體、光電業、存託憑證、汽車工業、其他、其他電子業、金融業、玻璃陶瓷、食品工業、紡織纖維、航運業、通信網路業、造紙工業、貿易百貨、塑膠工業、資訊服務業、農業科技、電子通路業、電子零組件、電器電纜、電機機械、橡膠工業、鋼鐵工業等共25種產業，未預期營收會對股價報酬帶來同向影響；然而，觀光事業之未預期營收會對股價報酬帶來反向影響；此外，文化創意業、生技醫療業、油電燃氣、建材營造、電子商務以及電腦及週邊等共6種產業，未預期營收會對股價報酬帶來的影響並不顯著。

關鍵字

營收宣告；累積異常報酬；事件研究法；資訊內涵

並列摘要

This thesis utilizes the event study approach to show the effect on the rate of return affected by the monthly revenue announcement with the data from Taiwan’s stock market. The sample period is from January 2015 to December 2019, and I collect 1,470 companies’ data within 32 industries publicly traded on Taiwan Stock Exchange (TWSE) and Taipei Exchange (TPEx). Firstly, in order to confirm that monthly revenue announcement events certainly affect the stock price. I utilize t-test to examine the daily data of abnormal returns (ARs) and cumulative abnormal returns (CARs) in announcement periods, and it proves that ARs and CARs exist. Secondly, in order to know the correlation between unexpected revenues and stock returns, I utilize linear regression to model the relationship between unexpected revenues (as independent variables) and CARs (as dependent variables), and the results are as below: 1. Positive effect on 25 industries, including: Chemical Industry, Cement Industry, Semiconductor Industry, Optoelectronic Industry, TDR, Automobile Industry, Others, Other Electronic Industry, Financial Industry, Glass and Ceramic Industry, Food Industry, Textile Industry, Shipping and Transportation Industry, Communications and Internet Industry, Paper and Pulp Industry, Trading and Consumers' Goods Industry, Plastic Industry, Information Service Industry, Agricultural Technology Industry, Electronic Products Distribution Industry, Electronic Parts & Components Industry, Electrical and Cable Industry, Electric Machinery Industry, Rubber Industry, Iron and Steel Industry. 2. Insignificant effect on 6 industries, including: Cultural and Creative Industry, Biotechnology and Medical Care Industry, Oil, Gas and Electricity Industry, Building Material and Construction Industry, Electronic Commerce Industry, Computer and Peripheral Equipment Industry. 3. Negative effect on Tourism Industry.