創新效率對於股價報酬之影響 —以台灣電子工業上市櫃公司為例

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：102

、訪客IP：3.15.149.24

姓名

王瀚陞(Han-Sheng Wang) 查詢紙本館藏

畢業系所

產業經濟研究所

論文名稱

創新效率對於股價報酬之影響 —以台灣電子工業上市櫃公司為例

相關論文

★ 探討企業永續行為：從漂綠行為說起	★ 空氣汙染對臺灣太陽能發電之影響
★ 空氣汙染對於房價的影響-以桃園重劃區為例	★ 公司治理、創新與公司經營績效：台灣電子業之實證研究
★ 新冠肺炎與投保行為之研究-以S人壽保險公司之銀行保險通路為例	★ 公司產品多樣化對營運績效的影響:以台灣電子產業為例
★ 董事會性別組成比例與員工之關係：以台灣企業勞動訴訟為例子	★ 論我國破產免責制度-以消費者債務清理條例為研究核心
★ 董事會性別平衡對經營績效影響	★ 疫情、市場情緒、公司治理與股價波動度
★ 談台灣電子與非電子產業CSR行為與財務績效之關係 -以GRI資料進行分析	★ 國家財富、最適外匯儲備水準與主權基金
★ 成人參與數位學習與個人特徵之關聯性分析	★ 女性董事及研發投資比例對公司經營績效的影響
★ 延長道路交通安全講習時數政策對年輕新手機車騎士常見事故型態影響之研究	★ 董事會性別多元化對員工福祉的影響

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

本研究加入Hirshleifer et al.(2013)所提出之創新效率因子於三因子資產定價模型中，創新效率可同時描繪創新投入及創新產出，捕捉股票報酬之解釋力，藉以探討台灣電子工業上市櫃公司之創新效率對股票報酬之影響。研究採用追蹤資料進行分析，以單因子、三因子、以及四因子資產定價模型探討市場風險因子(〖MKT〗_t)、規模因子(〖SMB〗_t)、價值因子(〖HML〗_t)及創新效率因子(〖EMP〗_t)對電子工業上市櫃企業股票報酬於2010年7月至2021年6月期間之解釋能力。
實證結果顯示資本資產定價模型(Capital Asset Pricing Model, CAPM)模型之結果為顯著，台灣電子工業上市櫃企業市場組合月平均報酬率優於無風險資產月平均報酬率；而規模因子(〖SMB〗_t)、價值因子(〖HML〗_t)亦對股票橫斷面有顯著之解釋力。具體來說，小規模投資組合月平均報酬率會優於大規模投資組合月平均報酬率，而高帳面市值比因子投資組合月平均報酬率會優於低帳面市值比投資組合月平均報酬率，與Fama & French (1992)之發現相同。
而創新效率因子(〖EMP〗_t)亦對整體電子工業有一定之解釋力，與Hirshleifer et al. (2013)之發現相同，即創新效率高的股票相較於創新效率低的股票可獲得較高報酬；具體而言，高創新效率投資組合月平均年報酬率優於低創新效率投資組合月平均年報酬率為0.9642%。再進一步透過異質性分析發現創新效率因子(〖EMP〗_t)在光電業、通信網路業、電腦及周邊業較無解釋能力，於其他電子業在10%水準下顯著，電子通路業和電子零組件業在5%水準下顯著，而半導體產業在1%水準下顯著;說明了創新效果因應子產業之不同特性而有所迴異，由此建議基金經理人在選擇電子工業之標的和優化買賣時間時，充分考量創新活動對股票報酬的差異性影響。

摘要(英)

This study incorporates innovation efficiency factor proposed by Hirshleifer et al. (2013) into the three-factor asset pricing model to capture both input and output of innovation in boosting the explanatory power of how innovation efficiency affects the return of listed companies in the Taiwan electronics industry. Employing single-factor, three-factor, and four-factor asset pricing models, this study applies panel data analysis to investigate the effect of market risk factor (〖MKT〗_t) , size factor (〖SMB〗_t) , value factor (〖HML〗_t) , and innovation efficiency factor (〖EMP〗_t) on the stock returns of listed companies in the electronics industry from July 2010 to June 2021.
The empirical results show that the monthly average returns of a market portfolio comprised of listed companies in the electronics industry of Taiwan outperform those of risk-free assets, a finding that corroborates the Capital Asset Pricing Model (CAPM). Additionally, the size factor (SMB) and the value factor (〖HML〗_t) explain the cross-sectional stock returns well, where small-sized investment portfolios yield higher monthly average returns compared to large-sized investment portfolios, and investment portfolios with high book-to-market ratios deliver higher monthly average returns than those with lower book-to-market ratios, thus confirming the findings of Fama & French (1992).
Furthermore, innovation efficiency factor (〖EMP〗_t) also holds explanatory power for the overall electronics industry, consistent with the findings of Hirshleifer et al. (2013), suggesting that stocks with higher innovation efficiency tend to yield higher returns compared to those with lower innovation efficiency. Specifically, the high innovation efficiency investment portfolio′s monthly average annualized return outperforms the low innovation efficiency investment portfolio by 0.9642%. Further heterogeneity analysis reveals that the innovation efficiency factor (〖EMP〗_t) lacks explanatory power in the optoelectronics, telecommunications, and computer peripherals industries. However, it is significant at a 10% level in other electronic industries, at a 5% level in the electronic distribution and electronic components industry, and a 1% level in the semiconductor industry. This illustrates the varying degree of impact of innovation efficiency across sub-industries, thus calling for fund managers to thoroughly consider the differential impact of innovative activities on stock returns when selecting investment targets and optimizing the timing of buying and selling within the electronics industry.

關鍵字(中)

★ 電子工業
★ 創新效率
★ 資產報酬
★ 企業規模
★ 市場風險

關鍵字(英)

★ Electronics Industry
★ Innovative Efficiency
★ Asset Returns
★ Firm Size
★ Market Risk

論文目次

摘要……………………………….………………………………………………………….…i
Abstract………………………………….………………………………………………….….ii
致謝…………………………………………………………………………………………...iii
目錄………………………………………………..………………………………………..…iv
表目錄……………….……………………………………………………………………..…..v
第一章緒論……………………………..………………………………………………...…..1
1-1 研究背景與動機……………………...……………….………………………...…..1
1-2 研究目之與架構…………………………...……….…………………………...…..3
第二章文獻回顧…………..………………………………………..…………….……....…..5
2-1資產定價模型………………………………………………………….…….…...…..5
2-2創新效率因子………………………..………………………………...................…..6
第三章資料與實證模型………………………….…………………………..........................7
3-1資料來源………………………………………………………………………....…...7
3-2 衡量企業創新效率 (Innovative efficiency, IE) …………………………...…....…..8
3-3實證模型………………………………………………………………….……....…10
3-4風險因子………………………………………………………………………...…..11
第四章實證結果…………………………………………………………………………….14
4-1實證結果……………………………………………………………………….…....14
第五章結論………………………….……………………..………………………….…….20
參考文獻………………………………………………….…………………………….…….22

參考文獻

一、中文文獻
1. 王仁傑(2018)。台灣半導體科技之幕後推手與展望。國家實驗研究院科學發展，541，30-36。
2. 經濟部智慧財產局(2022)。專利 IPC 與我國行業統計分類關聯表及統計應用分析報告。https://www.tipo.gov.tw/tw/cp-85-909735-e908b-1.html
3. 劉清標(2019)。企業創新效率之六因子資產定價模型。商管科技季刊，20(1)，69-108。
4. 劉毓明(2013)。創新效率與台灣股票市場報酬。【碩士論文，國立政治大學財務管理研究所】。臺灣博碩士論文知識加值系統。https://hdl.handle.net/11296/7n96rf
二、英文文獻
1. Banz, R. W. (1981). The relationship between return and market value of common stocks. Journal of Financial Economics, 9(1), 3-18.
2. Basse Mama, H. (2018). Innovative efficiency and stock returns: Should we care about nonlinearity? Finance Research Letters, 24, 81-89.
3. Booth, R. (1998). The measurement of intellectual capital. Management Accounting, 76(10), 26-28.
4. De Bondt, W. F. M., & Thaler, R. (1985). Does the stock market overreact? The Journal of Finance, 40(3), 793-805.
5. Deng, Z., Lev, B., & Narin, F. (1999). Science and technology as predictors of stock performance. Financial Analysts Journal, 55(3), 20-32.
6. Dzinkowski, R. (2000). The measurement and management of intellectual capital: An introduction. International Management Accounting Study, 78(2), 32- 36.
7. Fama, E., & French, K. (1992). The cross-section of expected stock returns. The Journal of Finance, 47(2), 427-465.
8. Fama, E., & French, K. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56.
9. Fama, E., & French, K. (1996). Multifactor explanations of asset pricing anomalies. The Journal of Finance, 51(1), 55-84.
10. Fama, E., & MacBeth, J. (1973). Risk, return, and equilibrium: Empirical tests. Journal of Political Economy, 81(3), 607-636.
11. Gao, W., & Chou, J. (2015). Innovation efficiency, global diversification, and firm value. Journal of Corporate Finance, 30, 278-298.
12. Griliches, Z. (1990). Patent statistics as economic indicators: A survey. Journal of Economic Literature, 28(4), 1661-1707.
13. Hall, B.H., Jaffe, A., & Trajtenberg, M. (2001). The NBER patent citation data file: Lessons, insights and methodological tools. (NBER Working Paper No.8498.)
14. Hall, B.H., & Ziedonis, R.M. (2001). The patent paradox revisited: An emlirical study of patenting in the US semiconductor industry, 1979-1995. RAND Journal of Economics, 32(1), 101-128.
15. Hall, B.H. (2005). Exploring the patent explosion. The Journal of Technology Transfer, 30(1-2), 35-48
16. Hirshleifer, D., Hsu, P.-H., & Li, D. (2013). Innovative efficiency and stock returns. Journal of Financial Economics, 107(3), 632-654.
17. Hirshleifer, D., Lim, S. S., & Teoh, S. H. (2011). Limited investor attention and stock market misreactions to accounting information. The Review of Asset Pricing Studies, 1(1), 35-73.
18. Kothari, S. P., Shanken, J., & Sloan, R. G. (1995). Another look at the cross-section of expected stock returns. The Journal of Finance, 50(1), 185-224.
19. Lev, B., & Sougiannis, T. (1996). The capitalization, amortization, and value-relevance of R&D. Journal of Accounting and Economics, 21(1), 107-138.
20. Lev, B., & Sougiannis, T. (1999). Penetrating the book-to-market black box: The R&D effect. Journal of Business Finance and Accounting, 26(3-4), 419-449.
21. Lintner, J. (1965). The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. The Review of Economics and Statistics, 47(1), 13-37.
22. Peng, L., & Xiong, W. (2006). Investor attention, overconfidence and category learning. Journal of Financial Economics, 80(3), 563-602.
23. Rosenberg, B., Reid, K., & Lanstein, R. (1985). Persuasive evidence of market inefficiency. Journal of Portfolio Management, 11(3), 9-16.
24. Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425-442.
25. Wu, J. & Chen, P. (2006). Price indices and non-linear mean reversion of real exchange rates, Southern Economic Journal, 73(2), 461- 471.
三、其他參考資料
1. 林思宇(2022年10月16日)。我半導體產值年增率耀眼。經濟日報。
https://money.udn.com/money/story/8888/6689450
2. 國家發展委員會(2022年11月17日)。【台版晶片法草案通過】鞏固台灣先進製程優勢。https://www.ndc.gov.tw/nc_14813_36374

指導教授

蔡栢昇

審核日期

2024-1-26

推文