本文旨在分析化妝品產業的績效。化妝品涵蓋用於個人護理、美容和美化外觀的多種產品，與人們的身心健康和美麗密切相關，在現代經濟中佔有重要地位。化妝品產業被歸屬於防禦型股票，理論上景氣波動對其影響不大，但隨著外在環境的變動，尤其歷經俄烏戰爭及Covid-19期間的衝擊，消費者的行為及生活模式改變，化妝品個股的報酬與波動是值得重新被分析。本文使用2000年至2024年7月資料完整的16家化妝品上市公司資料，並依其主業區分為美妝、居家保健及清潔護理等三個區塊，採用 CAPM 資本資產定價模型、Fama and French 三因子及五因子模型分別進行靜態與動態的績效分析，並進一步檢視影響個別股票績效的因素。
實證結果顯示，在靜態模型下，所有公司靜態均無顯著異常報酬，且多數公司的市場風險因子多小於大盤。然而在動態估計下，則明顯觀察到各公司的漲跌起伏。清潔護理主業的公司不管在動態異常報酬或是動態市場風險因子都相對平穩，美妝及居家保健主業的公司隨時間變化的起伏相對明顯。俄烏戰爭對所有公司多呈現一致性的負向衝擊結果顯著，受到供應鏈等成本激增影響，異常報酬在戰爭後呈現顯著為負的情形，然而多數公司仍呈現低於或等於市場大盤波動的情形，顯示化妝品產業儘管受到成本壓力激增的經營現況，仍得以努力且良好的維持營運，降低公司負面衝擊，股價報酬波動並未因此大跌。相對而言，疫情所造成的衝擊則並不一致。居家保健主業的公司受益多，美妝及清潔護理用品主業的公司則呈現漲跌互見的情形，雖然如此，股價波動皆相對平穩。代表雖然公司雖受到封城及居家辦公形式衝擊，也都努力調整自身產品型態，使之符合市場需求。

The purpose of this article is to analyze the performance of the cosmetics industry. Cosmetics encompass a variety of products used for personal care, beauty, and enhancement of appearance, closely related to people's physical and mental health and beauty, and hold an important position in the modern economy. The cosmetics industry is classified as a defensive stock, theoretically not significantly affected by economic fluctuations. However, with changes in the external environment, especially the impacts of the Russia-Ukraine war and the Covid-19 pandemic, consumer behavior and lifestyle patterns have changed, making the returns and volatility of individual cosmetics stocks warrant re-examination. This article uses comprehensive data from 16 publicly listed cosmetics companies from 2000 to July 2024, categorized by their main sectors into beauty, home health care, and cleaning products, utilizing the CAPM capital asset pricing model, and the Fama and French three-factor and five-factor models for both static and dynamic performance analysis, further examining the factors influencing individual stock performance. 
The empirical results show that in the static model, all companies showed no significant abnormal returns, and most companies had a market risk factor smaller than the overall market. However, in the dynamic estimation, significant fluctuations in the stocks of each company were observed. Companies in the cleaning products sector are relatively stable in both dynamic abnormal returns and dynamic market risk factors, while those in beauty and home health care sectors show more pronounced fluctuations over time. The Russia-Ukraine war resulted in significant negative impacts on all companies, largely due to the surge in costs from supply chain issues, with abnormal returns being significantly negative after the war; however, most companies still exhibited volatility below or equal to the overall market, indicating that despite the increased cost pressures, the cosmetics industry has managed to operate effectively and reduce negative impacts, with stock price volatility not experiencing a major decline. In contrast, the impacts from the pandemic were inconsistent. Companies in the home health care sector benefited the most, while those in beauty and cleaning products experienced mixed performance, though stock price volatility remained relatively stable. This suggests that although companies faced challenges from lockdowns and telecommuting, they made efforts to adjust their product offerings to meet market demands.

第一章  緒論………..…………………………………...1
第一節 研究動機與目的………………………………..…………………1
第二節 研究架構……………………………………………..……………5
第二章  文獻回顧………..…………………………………...6
第一節 影響化妝品類股績效之因素…….…………………….6
第二節 資本資產定價模型……………………………………13
第三章  研究方法…………………………..……………….17
  第一節 績效評估………………………………….…………..17
       一、CAPM 資本資產定價模型………….………….…..17
       二、Fama and French (1993)三因子模型…..….………...17
       三、Fama and French (2015)五因子模型…………..…....18
      第二節 影響因素分析…………..…………….………...…....19
第四章  實證結果…………..………….……….………..….20
      第一節 樣本資料…………………………..…………….….....20
      第二節 敘述統計量……………………………..………....…..24
      第三節 靜態績效分析………………..…………………....…..33
      第四節 動態績效分析…………………………………………35
      第五節 動態超額報酬估計結果探討…………………….…...41
      第六節 動態風險係數估計結果探討………………………....44
      第七節 綜合討論…………………………………………..…..46
第五章  結論………..……………………………………….48
參考文獻……………………………………………………...50
中文文獻………………………………………………………………..50
英文文獻………………………………………………………………..52

表目錄
表 4 1 樣本資料介紹	22
表 4 1 樣本資料介紹 (續)	23
表 4 2 股價報酬敘述統計量	28
表 4 3 靜態估計結果	34
表4 4 影響動態異常報酬之因素分析……………………………………………43
表4 5 影響動態風險因子beta值之因素分析…………………………...…….45
表4 6 整合分析…………………………………………………………………..47
 

圖目錄
圖  4 1 美妝主業公司報酬趨勢	29
圖  4 2 居家保健主業公司報酬趨勢	30
圖  4 3 清潔護理主業公司報酬趨勢 	32
圖  4 4 美妝主業公司動態異常報酬(ALPHA)與市場風險因子(BETA)	36
圖  4 5 居家保健主業公司動態異常報酬(ALPHA)與市場風險因子(BETA)	38
圖  4 6 清潔護理主業公司動態異常報酬(ALPHA)與市場風險因子(BETA)	39

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