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題名 智慧型手機台灣供應鏈股價報酬率之預測性研究
作者 翁甄縈
貢獻者 顏錫銘
翁甄縈
關鍵詞 智慧型手機
供應鏈
概念股
資訊移轉
Smartphone
Supply Chain
Concept Stock
Information Transfer
日期 2011
上傳時間 10-Feb-2014 14:48:08 (UTC+8)
摘要 近年來，各智慧型手機的概念股經常成為證券分析師以及投顧公司報告中建議的投資標的，一般的新聞媒體、報章雜誌以及其他和投資相關的財經節目也常以智慧型手機相關類股作為節目討論主題，但是投資智慧型手機相關類股是否真的可以讓投資人從中獲得異常報酬，是本研究想知道的，因此本研究利用事件研究法做實證研究，以確認智慧型手機品牌大廠和其供應鏈公司股價間，真的有一定程度的相關性，並且觀察其影響的速度及程度，進而推測是否可利用智慧型手機品牌大廠之公司股價，直接對該供應鏈公司股價報酬作預測。
實證結果發現，Apple Inc.供應鏈公司股價和Apple Inc.公司股價無論是正事件日或負事件日當天皆為正相關，兩者間之連結最為緊密。而HTC供應鏈和Nokia供應鏈之公司股價，只有於正事件日當天和其智慧型手機品牌大廠之公司股價為正相關，並且只有HTC供應鏈的公司股價，可利用HTC公司股價作預測，而其影響對於供應鏈中屬於大型股或中小型股之供應商公司股價並沒有顯著差異。RIM供應鏈和Samsung供應鏈的公司股價則是於正事件日和負事件日當天和其智慧型手機品牌大廠之公司股價皆沒有明顯的相關性。而觀察台灣的智慧型手機市場以及查詢聯合知識庫可發現，Apple Inc.、HTC和Nokia較多人使用且為新聞報導中較常被提及的，其供應鏈也較常成為投資標的之建議，RIM鮮少被大眾媒體報導，而Samsung大部分手機零組件皆由其國內子公司自行生產，而且其產品非常多樣化，因此投資人要將Samsung和其台灣供應商作連結，相對來說較不容易。另外，在負事件當中只有Apple Inc.供應鏈之公司股價和Apple Inc.公司股價有正相關，其他智慧型手機品牌大廠皆沒有明顯相關性，本研究試著觀察是否因負面新聞種類的不同，而造成此實證結果，但並未得到理想的結果及解答。
In recent years, concept stocks of various Smartphone makers have often been the investment targets suggested by the securities analysts and in the reports of investment companies. The media and other financial programs related to investment usually tackle the Smartphone related stocks as newsworthy topics. This study wonders whether the investors can really obtain abnormal returns by investing into these stocks. Therefore, by conducting an empirical study using an event study approach, it validates the correlation to a certain extent between the stock prices of big Smartphone brand manufacturers and their supply chain companies, and observes the influence speed and degree. Furthermore, it speculates whether the stock price of the big Smartphone brand manufacturers can be used to make a direct prediction of the stock returns of the supply chain companies.
As shown in the empirical results, the stock prices of Apple Inc. and its supply chain companies are positively correlated whether on the positive event days or negative event days, indicating their close connection. However, the stock prices of HTC and Nokia supply chain companies only show a positive correlation with the corresponding Smartphone brand manufacturers in the positive event days. Moreover, only the stock price of HTC supply chain companies can be predicted by that of the HTC Company, while it doesn’t show any significant difference in terms of the influence on the stock prices of the large and small sized suppliers. As for the stock prices of RIM and Samsung companies, there is no significant correlation with the stock price of the Smartphone brand manufacturers with the positive and negative event days. By observing Taiwan’s Smartphone market and searching in UDN, it’s found that Apple Inc., HTC and Nokia are the most popular and frequently mentioned in the news reports, and their supply chains are often suggested as investment objects. RIM is rarely reported by mass media. When it comes to Samsung, most phone accessories are manufactured by its own subsidiaries in Korea, which manufacture diverse products. Therefore, it is not so easy for the investors to link Samsung with its suppliers in Taiwan. In addition, during the negative events, positive correlation only exists between the stock prices of Apple Inc. and its supply chain companies, which is not the case with other Smartphone brand manufacturers. This study attempts to observe whether the empirical result is derived from the difference among negative news types, but no desired results and answers are obtained.
參考文獻 一、中文文獻
1.沈中華，李建然，「台灣經濟新報文化事業公司事件研究法暨β 模組使用者操作手冊」。
2.范懷文，2001，「事件研究法：母數、無母數與拔靴複製法之比較」，國立中央大學財務管理研究所碩士論文。
3.施純協，2005，「手機同心工程四部曲（2）進皆篇：手機產業分析」，文笙書局股份有限公司。
4.徐雅君，1999，「電子業代工關係之股價反應研究」，國立中正大學財務金融研究所碩士論文。
5.劉玉潔，2009，「機構投資人交易行為與股票報酬橫斷面預測之研究：以跨國供應鏈為例」，國立成功大學會計學研究所碩士論文。
二、英文文獻
1.Ball, Ray, and Philip Brown, 1968, “An Empirical Evaluation of Accounting Income Numbers,” Journal of Accounting Research, Vol. 6, No. 2, 159-178.
2.Bernard, Victor L., and Jacob K. Thomas, 1989, “Post-Earnings-Announcement Drift: Delayed Price Response or Risk Premium?” Journal of Accounting Research, Vol. 27, 1-36.
3.Bliemel, Friedhelm, 1973, “Theil`s Forecast Accuracy Coefficient: A Clarification,” Journal of Marketing Research,Vol. 10, 444-446.
4.Boehme, Rodney D., and Sorin M. Sorescu, 2002, “The Long-run Performance Following Dividend Initiations and Resumptions: Underreaction or Product of Chance?” The Journal of Finance, Vol. 57, No. 2, 871-900.
5.Bowman, Robert G., 1983, “Understanding and Conducting Event Studies,” Journal of Business Finance & Accounting, Vol. 10, No. 4, 561-584.
6.Brown, S.J. and J.B. Warner, 1980, “Measuring Security Price Performance,” Journal of Financial Economics 8, 205-258.
7.Brown, S.J. and J. B. Warner, 1985, “Using Daily Stock Return: The Case of Event Studies,” Journal of Financial Economics 14, 3-31.
8.Cohen, Lauren, and Andrea Frazzini, 2008,“Economic Links and Predictable Returns,” The Journal of Finance, Vol. 63, No. 4 (August), 1977-2011.
9.Dyckman, T., D. Philbrick and J. Stephan, 1984, “A Comparison of Event Study Methodologies Using Daily Stock Returns: A Simulation Approach, ” Journal of Accounting Research (supplement) Vol. 22, 1-33.
10.Fama E. F., L. Fisher, M. C. Jensen and R. Roll, 1969, “The Adjustment of Stock Prices to New Information,” International Economic Review 10, 1-21.
11.Foster, G., 1981, “Intra-Industry Information Transfers Associated with Earnings Releases,” Journal of Accounting and Economics 3, 201-232.
12.Funke, Christian, Timo Gebken, Lutz Johanning, and Gaston Michel, 2010, “Is It Really There? Limited Attention and Predictability of Supplier Returns After Large Customer Price Changes,” working paper.
13.Ikenberry, David, Josef Lakonishok, and Theo Vermaelen, 1995, “Market Underreaction to Open Market Share Repurchases,” Journal of Financial Economics 39, 181-208.
14.Lindberg, Bertil C., 1982, “International Comparison of Growth in Demand for a New Durable Consumer Product,” Journal of Marketing Research, Vol. 19, 364-371.
15.Loughran, Tim, and Jay R. Ritter, 1995, “The New Issues Puzzle,” The Journal of Finance, Vol. 50, Issue 1, 23-51.
16.MacKinlay, A. Craig, 1997, “Event Studies in Economics and Finance,” Journal of Economic Literature, Vol. 35, No. 1, 13-39.
17.Menzly, Lior, and Oguzhan Ozbas, 2010, “Market Segmentation and Cross-predictability of Returns,” The Journal of Finance, Vol. 65, No. 4 (August), 1555-1580.
18.Olsen, C. and J. R. Dietrich, 1985, “Vertical Information Transfer：The Association Between Retailers’ Sales Announcements and Suppliers’ Security Returns,” Journal of Accounting Research, Vol. 23, 144-166.
19.Pritamani, Mahesh, and Vijay Singal, 2001, “Return Predictability Following Large Price Changes and Information Releases,” Journal of Banking & Finance 25, 631-656.
20.Ritter, Jay R., 1991, “The Long-Run Performance of Initial Public Offerings,” The Journal of Finance, Vol.46, No. 1, 3-27.
21.Schipper, Katherine, 1990, “Information Transfers,” Accounting Horizons, 97-107.
22.Shahrur,Husayn, Ying L. Becker, and Didier Rosenfeld, CFA, 2010, “Return Predictability along the Supply Chain: The International Evidence,” Financial Analysts Journal 25, 631-656.
23.Tashman, Leonard J., 2000, “Out-of-Sample Tests of Forecasting Accuracy: an Analysis and Review,” International Journal of Forecasting 16, 437-450.
24.Zhang, Hua, 2005, “Share Price Performance Following Actual Share Repurchases,” Journal of Banking & Finance 29, 1887-1901.
描述 碩士
國立政治大學
財務管理研究所
99357036
100
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0099357036
資料類型 thesis
dc.contributor.advisor 顏錫銘zh_TW
dc.contributor.author (Authors) 翁甄縈zh_TW
dc.creator (作者) 翁甄縈zh_TW
dc.date (日期) 2011en_US
dc.date.accessioned 10-Feb-2014 14:48:08 (UTC+8)-
dc.date.available 10-Feb-2014 14:48:08 (UTC+8)-
dc.date.issued (上傳時間) 10-Feb-2014 14:48:08 (UTC+8)-
dc.identifier (Other Identifiers) G0099357036en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/63648-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 財務管理研究所zh_TW
dc.description (描述) 99357036zh_TW
dc.description (描述) 100zh_TW
dc.description.abstract (摘要) 近年來，各智慧型手機的概念股經常成為證券分析師以及投顧公司報告中建議的投資標的，一般的新聞媒體、報章雜誌以及其他和投資相關的財經節目也常以智慧型手機相關類股作為節目討論主題，但是投資智慧型手機相關類股是否真的可以讓投資人從中獲得異常報酬，是本研究想知道的，因此本研究利用事件研究法做實證研究，以確認智慧型手機品牌大廠和其供應鏈公司股價間，真的有一定程度的相關性，並且觀察其影響的速度及程度，進而推測是否可利用智慧型手機品牌大廠之公司股價，直接對該供應鏈公司股價報酬作預測。
實證結果發現，Apple Inc.供應鏈公司股價和Apple Inc.公司股價無論是正事件日或負事件日當天皆為正相關，兩者間之連結最為緊密。而HTC供應鏈和Nokia供應鏈之公司股價，只有於正事件日當天和其智慧型手機品牌大廠之公司股價為正相關，並且只有HTC供應鏈的公司股價，可利用HTC公司股價作預測，而其影響對於供應鏈中屬於大型股或中小型股之供應商公司股價並沒有顯著差異。RIM供應鏈和Samsung供應鏈的公司股價則是於正事件日和負事件日當天和其智慧型手機品牌大廠之公司股價皆沒有明顯的相關性。而觀察台灣的智慧型手機市場以及查詢聯合知識庫可發現，Apple Inc.、HTC和Nokia較多人使用且為新聞報導中較常被提及的，其供應鏈也較常成為投資標的之建議，RIM鮮少被大眾媒體報導，而Samsung大部分手機零組件皆由其國內子公司自行生產，而且其產品非常多樣化，因此投資人要將Samsung和其台灣供應商作連結，相對來說較不容易。另外，在負事件當中只有Apple Inc.供應鏈之公司股價和Apple Inc.公司股價有正相關，其他智慧型手機品牌大廠皆沒有明顯相關性，本研究試著觀察是否因負面新聞種類的不同，而造成此實證結果，但並未得到理想的結果及解答。		zh_TW
dc.description.abstract (摘要) In recent years, concept stocks of various Smartphone makers have often been the investment targets suggested by the securities analysts and in the reports of investment companies. The media and other financial programs related to investment usually tackle the Smartphone related stocks as newsworthy topics. This study wonders whether the investors can really obtain abnormal returns by investing into these stocks. Therefore, by conducting an empirical study using an event study approach, it validates the correlation to a certain extent between the stock prices of big Smartphone brand manufacturers and their supply chain companies, and observes the influence speed and degree. Furthermore, it speculates whether the stock price of the big Smartphone brand manufacturers can be used to make a direct prediction of the stock returns of the supply chain companies.
As shown in the empirical results, the stock prices of Apple Inc. and its supply chain companies are positively correlated whether on the positive event days or negative event days, indicating their close connection. However, the stock prices of HTC and Nokia supply chain companies only show a positive correlation with the corresponding Smartphone brand manufacturers in the positive event days. Moreover, only the stock price of HTC supply chain companies can be predicted by that of the HTC Company, while it doesn’t show any significant difference in terms of the influence on the stock prices of the large and small sized suppliers. As for the stock prices of RIM and Samsung companies, there is no significant correlation with the stock price of the Smartphone brand manufacturers with the positive and negative event days. By observing Taiwan’s Smartphone market and searching in UDN, it’s found that Apple Inc., HTC and Nokia are the most popular and frequently mentioned in the news reports, and their supply chains are often suggested as investment objects. RIM is rarely reported by mass media. When it comes to Samsung, most phone accessories are manufactured by its own subsidiaries in Korea, which manufacture diverse products. Therefore, it is not so easy for the investors to link Samsung with its suppliers in Taiwan. In addition, during the negative events, positive correlation only exists between the stock prices of Apple Inc. and its supply chain companies, which is not the case with other Smartphone brand manufacturers. This study attempts to observe whether the empirical result is derived from the difference among negative news types, but no desired results and answers are obtained.		en_US
dc.description.tableofcontents 第一章 緒 論 1
第一節 研究動機與目的 1
第二節 研究架構 3
第二章 文獻探討 4
第一節 事件研究法 4
第二節 垂直資訊移轉效果與供應鏈股價報酬率之可預測性 8
第三章 研究設計 12
第一節 研究假說 12
第二節 研究對象 14
第三節 研究期間與資料來源 23
第四節 研究設計 24
第四章 實證結果與分析 36
第一節 供應鏈股價報酬之可預測性 37
第二節 股本大小與供應鏈股價報酬之可預測性 49
第三節 樣本外測試 61
第四節 樣本外交易策略 63
第五章 結論與限制 66
第一節 研究結論 66
第二節 研究限制 69
參考文獻 70		zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0099357036en_US
dc.subject (關鍵詞) 智慧型手機zh_TW
dc.subject (關鍵詞) 供應鏈zh_TW
dc.subject (關鍵詞) 概念股zh_TW
dc.subject (關鍵詞) 資訊移轉zh_TW
dc.subject (關鍵詞) Smartphoneen_US
dc.subject (關鍵詞) Supply Chainen_US
dc.subject (關鍵詞) Concept Stocken_US
dc.subject (關鍵詞) Information Transferen_US
dc.title (題名) 智慧型手機台灣供應鏈股價報酬率之預測性研究zh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 一、中文文獻
1.沈中華，李建然，「台灣經濟新報文化事業公司事件研究法暨β 模組使用者操作手冊」。
2.范懷文，2001，「事件研究法：母數、無母數與拔靴複製法之比較」，國立中央大學財務管理研究所碩士論文。
3.施純協，2005，「手機同心工程四部曲（2）進皆篇：手機產業分析」，文笙書局股份有限公司。
4.徐雅君，1999，「電子業代工關係之股價反應研究」，國立中正大學財務金融研究所碩士論文。
5.劉玉潔，2009，「機構投資人交易行為與股票報酬橫斷面預測之研究：以跨國供應鏈為例」，國立成功大學會計學研究所碩士論文。
二、英文文獻
1.Ball, Ray, and Philip Brown, 1968, “An Empirical Evaluation of Accounting Income Numbers,” Journal of Accounting Research, Vol. 6, No. 2, 159-178.
2.Bernard, Victor L., and Jacob K. Thomas, 1989, “Post-Earnings-Announcement Drift: Delayed Price Response or Risk Premium?” Journal of Accounting Research, Vol. 27, 1-36.
3.Bliemel, Friedhelm, 1973, “Theil`s Forecast Accuracy Coefficient: A Clarification,” Journal of Marketing Research,Vol. 10, 444-446.
4.Boehme, Rodney D., and Sorin M. Sorescu, 2002, “The Long-run Performance Following Dividend Initiations and Resumptions: Underreaction or Product of Chance?” The Journal of Finance, Vol. 57, No. 2, 871-900.
5.Bowman, Robert G., 1983, “Understanding and Conducting Event Studies,” Journal of Business Finance & Accounting, Vol. 10, No. 4, 561-584.
6.Brown, S.J. and J.B. Warner, 1980, “Measuring Security Price Performance,” Journal of Financial Economics 8, 205-258.
7.Brown, S.J. and J. B. Warner, 1985, “Using Daily Stock Return: The Case of Event Studies,” Journal of Financial Economics 14, 3-31.
8.Cohen, Lauren, and Andrea Frazzini, 2008,“Economic Links and Predictable Returns,” The Journal of Finance, Vol. 63, No. 4 (August), 1977-2011.
9.Dyckman, T., D. Philbrick and J. Stephan, 1984, “A Comparison of Event Study Methodologies Using Daily Stock Returns: A Simulation Approach, ” Journal of Accounting Research (supplement) Vol. 22, 1-33.
10.Fama E. F., L. Fisher, M. C. Jensen and R. Roll, 1969, “The Adjustment of Stock Prices to New Information,” International Economic Review 10, 1-21.
11.Foster, G., 1981, “Intra-Industry Information Transfers Associated with Earnings Releases,” Journal of Accounting and Economics 3, 201-232.
12.Funke, Christian, Timo Gebken, Lutz Johanning, and Gaston Michel, 2010, “Is It Really There? Limited Attention and Predictability of Supplier Returns After Large Customer Price Changes,” working paper.
13.Ikenberry, David, Josef Lakonishok, and Theo Vermaelen, 1995, “Market Underreaction to Open Market Share Repurchases,” Journal of Financial Economics 39, 181-208.
14.Lindberg, Bertil C., 1982, “International Comparison of Growth in Demand for a New Durable Consumer Product,” Journal of Marketing Research, Vol. 19, 364-371.
15.Loughran, Tim, and Jay R. Ritter, 1995, “The New Issues Puzzle,” The Journal of Finance, Vol. 50, Issue 1, 23-51.
16.MacKinlay, A. Craig, 1997, “Event Studies in Economics and Finance,” Journal of Economic Literature, Vol. 35, No. 1, 13-39.
17.Menzly, Lior, and Oguzhan Ozbas, 2010, “Market Segmentation and Cross-predictability of Returns,” The Journal of Finance, Vol. 65, No. 4 (August), 1555-1580.
18.Olsen, C. and J. R. Dietrich, 1985, “Vertical Information Transfer：The Association Between Retailers’ Sales Announcements and Suppliers’ Security Returns,” Journal of Accounting Research, Vol. 23, 144-166.
19.Pritamani, Mahesh, and Vijay Singal, 2001, “Return Predictability Following Large Price Changes and Information Releases,” Journal of Banking & Finance 25, 631-656.
20.Ritter, Jay R., 1991, “The Long-Run Performance of Initial Public Offerings,” The Journal of Finance, Vol.46, No. 1, 3-27.
21.Schipper, Katherine, 1990, “Information Transfers,” Accounting Horizons, 97-107.
22.Shahrur,Husayn, Ying L. Becker, and Didier Rosenfeld, CFA, 2010, “Return Predictability along the Supply Chain: The International Evidence,” Financial Analysts Journal 25, 631-656.
23.Tashman, Leonard J., 2000, “Out-of-Sample Tests of Forecasting Accuracy: an Analysis and Review,” International Journal of Forecasting 16, 437-450.
24.Zhang, Hua, 2005, “Share Price Performance Following Actual Share Repurchases,” Journal of Banking & Finance 29, 1887-1901.		zh_TW