研究生: |
何東霖 He, Tung-Lin |
---|---|
論文名稱: |
OpenAI產品發布對臺灣AI概念股股價的影響 The Impact of OpenAI Product Releases on the Stock Prices of Taiwan's AI Related Stocks |
指導教授: |
周德瑋
Chou, De-Wai |
口試委員: |
周德瑋
Chou,De-Wai 陳達新 Chen, Dar-Hsin 陳勝源 Chen, Shen-Yuan |
口試日期: | 2024/06/18 |
學位類別: |
碩士 Master |
系所名稱: |
管理研究所 Graduate Institute of Management |
論文出版年: | 2024 |
畢業學年度: | 112 |
語文別: | 中文 |
論文頁數: | 79 |
中文關鍵詞: | OpenAI 、GPT系列 、AI概念股 、事件研究法 、異常報酬 |
英文關鍵詞: | OpenAI, GPT series, AI-related stocks, event study, abnormal returns |
研究方法: | 次級資料分析 、 個案研究法 、 主題分析 、 事件研究法 |
DOI URL: | http://doi.org/10.6345/NTNU202400856 |
論文種類: | 學術論文 |
相關次數: | 點閱:193 下載:0 |
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本研究探討OpenAI產品發布對台灣AI概念股股價的影響,研究採用事件研究法,以GPT-1至GPT-4及ChatGPT的發布為事件,分析台灣55家台灣上市櫃AI概念股在事件日的標準化平均異常報酬(SAR)和標準化累積平均異常報酬(SCAR)。結果顯示OpenAI產品發布顯著影響相關概念股的股價,尤其在GPT-3、ChatGPT及GPT-4發布日當天之標準化異常報酬皆顯著異於零。在標準化累積異常報酬的事件窗口分析方面,GPT-1、GPT-2、GPT-3及GPT-4在發布日前20天至後1天最為顯著,說明這三個GPT系列產品可能反應投資人可利用內線交易獲取超額報酬之情形。同時,本研究利用ANOVA單因子變異數檢測五項GPT系列產品的標準化累積異常報酬之間是否存在差異,結果顯示GPT-2及GPT-4這兩項產品與其他系列產品相比顯著不同。
此外,本研究通過多元迴歸分析,主要探討產品原創性、研發經費比率、股東權益報酬率、營收成長率、負債比率、現金流量比率和應收帳款週轉率對標準化累積平均異常報酬率的影響。結果表明,產品原創性對股價的異常報酬有顯著影響,並且在短期效果上股東權益報酬率、營收成長率、公司年限及淨值市價比也對股價的累積異常報酬產生顯著影響。本研究進一步將55家AI概念股分為四個產業類別,並對標準化累積異常報酬進行分析,研究顯示資訊服務產業對標準化累積異常報酬的影響尤為顯著。本研究為投資者和企業提供了理解科技創新對資本市場影響的重要參考,並建議企業在新產品開發中注重研發投入和創新性,從而提升市場競爭力和投資回報,同時為投資者的標的選擇提供有價值的分析。
This study investigates the impact of OpenAI product releases on the stock prices of AI-related stocks in Taiwan. Using the event study method, it analyzes the standardized average abnormal returns (SAR) and standardized cumulative average abnormal returns (SCAR) of 55 listed AI-related stocks around the release dates of GPT-1, GPT-2, GPT-3, GPT-4, and ChatGPT. The results demonstrate that these releases significantly affect stock prices, with GPT-3, ChatGPT, and GPT-4 showing particularly notable SAR on their release days. The SCAR analysis indicates significant effects from 20 days before to one day after the release for GPT-1, GPT-2, GPT-3, and GPT-4, suggesting potential insider trading advantages.
ANOVA analysis reveals significant differences in SCAR among the GPT series, with GPT-2 and GPT-4 showing significant deviations compared to other products. Multiple regression analysis identifies product originality, return on equity, revenue growth rate, company age, and net worth to market value ratio as significant factors influencing SCAR. The study also finds that the information services industry exerts a particularly significant impact on SCAR.
This research provides valuable insights for investors and enterprises, emphasizing the importance of R&D investment and innovation in enhancing market competitiveness and investment returns. It suggests that companies should focus on these areas to improve their market position and provide investors with a detailed analysis for better decision-making.
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