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題名 標的股票與ADR錯價關係之研究－以台積電和聯電COVID-19疫情前後為例
A study on mispricing between underlying stock and its ADR – Comparing COVID-19 impacts on TSMC and UMC作者 游季婕
Yu, Chi-Chieh貢獻者 王信實
Wang, Shinn-Shyr
游季婕
Yu, Chi-Chieh關鍵詞 ADR
錯價
COVID-19
單變量GARCH模型
DCC模型
CCC模型
ADR
Mispricing
COVID-19
Univariate GARCH model
DCC model
CCC model日期 2022 上傳時間 2-Sep-2022 15:27:13 (UTC+8) 摘要 本文利用GARCH模型 (generalized autoregressive conditional heteroskedasticity model) 探討標的股票與ADR (American Depositary Receipt) 之間錯價 (mispricing) 關係，了解兩者間是否有套利空間。本研究將COVID-19疫情衝擊納入考量，以台積電和聯電作為研究標的，發現錯價主要受美國市場影響，且在疫情過後美國市場的影響有顯著增加。模型中也加入錯價自身落遲項以了解收斂速度，研究發現聯電收斂的時間和幅度都大於台積電，受疫情的程度也台積電大。除了利用單變量GARCH模型分析錯價走勢外，本文也使用雙變量GARCH中的DCC 模型(dynamic conditional correlation model) 探討標的股票和ADR相關性的變化，結果顯示台積電較適合使用CCC模型 (constant conditional correlation model)，其標的股票和ADR之間的關係較穩定。
This paper studies the mispricing relationship between the underlying stock and ADR (American Depositary Receipt) and investigates whether there exists an arbitrage opportunity between them by the GARCH model (generalized autoregressive conditional heteroskedasticity model). Taking TSMC and UMC as examples, we found that the mispricing is mainly affected by the US market, and the impact of the US market has increased significantly after the COVID-19 pandemic. Furthermore, the time and amplitude of the convergence of UMC are greater than that of TSMC, and the pandemic has more impacts on UMC than on TSMC. In addition to the univariate GARCH model, this paper also adopts the DCC model (dynamic conditional correlation model) in the bivariate GARCH to explore the changes in the correlation between the underlying stock and ADR. The results show that the CCC model (constant conditional correlation model) fits better for TSMC and its relationship is more stable between the underlying stock and ADR.參考文獻 中文部分1.王凱立、陳美玲（2003），「亞洲金融風暴發生前後美國與台灣股市動態關聯之進一步研究」，經濟論文叢刊，第31期，頁191-252。2.陳旭昇（2003）。《時間序列分析－總體經濟與財務金融之應用》。 臺北：東華書局。3.黃營杉、李銘章（2005），「台灣母公司股票報酬與其ADR報酬間資訊傳遞之研究」，東吳經濟商學學報，第48期，頁1-32。4.張光亮、黃宗佑（2010），「美國存託憑證與母國股票報酬間之動態關聯性－極端尾部相依性以及Kendall’s tau之研究」，經濟研究，47卷2期頁305-356。5.楊奕農（2017）。《時間序列分析－經濟與財務上之應用》。臺北：雙葉書廊。6.聶建中、高友笙、楊超翔（2011），「次級房貸危機前後美股對亞股的不對稱性蔓延效果」，中原企管評論，第9期，頁25-52。英文部分1.Alhaj-Yassen, Y.S., Ladd, D. (2019), “Which sentiments do US investors follow when trading ADRs?”, Journal of Economics and Finance, 43, 506-527.2.Bollerslev, T., Engle, R.F., Wooldridge, J.M. (1998), “A capital asset pricing model with time varying covariances.”, Journal of Political Economy, 96, 116-131.3.Bollerslev, T. (1986), “Generalized Autoregressive Conditional Heteroskedasticity.”, Journal of Econometrics, 31, 307-327.4.Baker, M., Stein, J. (2004), “Market liquidity as a sentiment indicator.”, Journal of Financial Markets, 7, 271–299 .5.Esqueda, O.A., Luo, Y., Jackson, D.O. (2013), “The linkage between the U.S. “fear index” and ADR premiums under non-frictionless stock markets.”, Journal of Economics and Finance, 39, 541-556.6.Engle, R.F., Kroner, K.F. (1995), “Multivariate simultaneous generalized ARCH.”, Econometric Theory, 11, 122-150.7.Engle, R.F. (2002), “Dynamic conditional correlation-a sample class of multivariate GARCH models.”, Journal of Business and Economic Statistics, 20, 339-350.8.Engle, R.F., Kroner, K.F. (1995), “Multivariate Simultaneous Generalized Arch.”, Econometric Theory, 11(1) 122-150.9.Glosten, L.R., Jagannathan, R., Runkle, D.E. (1993), “On the Relation between the Expected value and the volatility of the Nominal Excess Return on Stocks.”, Journal of Finance, 48, 1779-1801.10.Gagnon, L., Karolyi, G.A. (2010), “Multi-market trading and arbitrage.”, Journal of Financial Economics, 97, 53-80.11.Grossmann, A., Ngo, N. (2020), “Economic policy uncertainty and ADR mispricing.”, Journal of Multinational Financial Management, 55, 1-19.12.Grossmann, A., Ngo, N., Simpson M.W. (2017), “The asymmetric impact of currency purchasing power imparities on ADR mispricing.”, 42, 74-94.13.Jiang, C.X. (1998), “Diversification with American Depositary Receipts: The Dynamics and the Pricing Factors.”, Journal of Business Finance and Accounting, 25, 683-699.14.Jondeau, E., Rockinger, M. (2006), “The Copula-GARCH Model of Conditional Dependencies: An International Stock Market Application.”, Journal of International Money and Finance, 25, 827-853.15.Nelson, D.B. (1991), “Conditional Heteroskedasticity in Asset Returns: A New Approach.”, Econometrica, 59, 347-370.16.Pontiff, J. (2007), “Costly arbitrage: evidence from closed-end funds.”, Quarterly Journal of Economics, 111, 1135-1151.17.Poshakwale, S.S., Aquino, K.P. (2008), “The dynamics of volatility transmission and information flow between ADRs and their underlying stocks.”, Global Finance Journal, 19, 187-201.18.Shu, J. (2003), “ADRs and U.S. Market sentiment.”, Journal of Investing Winter 12, 87-95.19.Vaira, T.A., Ramaprasad, B. (2002), “Information and volatility linkage under external shocks Evidence from dually listed Australian stocks.”, International Review of Financial Analysis, 11, 59-71. 描述 碩士
國立政治大學
經濟學系
109258037資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109258037 資料類型 thesis dc.contributor.advisor 王信實 zh_TW dc.contributor.advisor Wang, Shinn-Shyr en_US dc.contributor.author (Authors) 游季婕 zh_TW dc.contributor.author (Authors) Yu, Chi-Chieh en_US dc.creator (作者) 游季婕 zh_TW dc.creator (作者) Yu, Chi-Chieh en_US dc.date (日期) 2022 en_US dc.date.accessioned 2-Sep-2022 15:27:13 (UTC+8) - dc.date.available 2-Sep-2022 15:27:13 (UTC+8) - dc.date.issued (上傳時間) 2-Sep-2022 15:27:13 (UTC+8) - dc.identifier (Other Identifiers) G0109258037 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/141745 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 經濟學系 zh_TW dc.description (描述) 109258037 zh_TW dc.description.abstract (摘要) 本文利用GARCH模型 (generalized autoregressive conditional heteroskedasticity model) 探討標的股票與ADR (American Depositary Receipt) 之間錯價 (mispricing) 關係，了解兩者間是否有套利空間。本研究將COVID-19疫情衝擊納入考量，以台積電和聯電作為研究標的，發現錯價主要受美國市場影響，且在疫情過後美國市場的影響有顯著增加。模型中也加入錯價自身落遲項以了解收斂速度，研究發現聯電收斂的時間和幅度都大於台積電，受疫情的程度也台積電大。除了利用單變量GARCH模型分析錯價走勢外，本文也使用雙變量GARCH中的DCC 模型(dynamic conditional correlation model) 探討標的股票和ADR相關性的變化，結果顯示台積電較適合使用CCC模型 (constant conditional correlation model)，其標的股票和ADR之間的關係較穩定。 zh_TW dc.description.abstract (摘要) This paper studies the mispricing relationship between the underlying stock and ADR (American Depositary Receipt) and investigates whether there exists an arbitrage opportunity between them by the GARCH model (generalized autoregressive conditional heteroskedasticity model). Taking TSMC and UMC as examples, we found that the mispricing is mainly affected by the US market, and the impact of the US market has increased significantly after the COVID-19 pandemic. Furthermore, the time and amplitude of the convergence of UMC are greater than that of TSMC, and the pandemic has more impacts on UMC than on TSMC. In addition to the univariate GARCH model, this paper also adopts the DCC model (dynamic conditional correlation model) in the bivariate GARCH to explore the changes in the correlation between the underlying stock and ADR. The results show that the CCC model (constant conditional correlation model) fits better for TSMC and its relationship is more stable between the underlying stock and ADR. en_US dc.description.tableofcontents 壹、前言 1貳、文獻回顧 3第一節 標的股票與ADR之間訊息傳遞 3第二節 標的股票與ADR之間錯價原因 4第三節 經濟衝擊對台股和美股市場之影響 5參、變數定義與研究方法 6第一節 變數定義 6第二節 資料檢定 8第三節 GARCH模型 10肆、實證分析 15第一節 資料趨勢圖 15第二節 資料描述 17第三節 單根檢定 22第四節 GARCH模型 23伍、結論與建議 41參考文獻 46 zh_TW dc.format.extent 6159384 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109258037 en_US dc.subject (關鍵詞) ADR zh_TW dc.subject (關鍵詞) 錯價 zh_TW dc.subject (關鍵詞) COVID-19 zh_TW dc.subject (關鍵詞) 單變量GARCH模型 zh_TW dc.subject (關鍵詞) DCC模型 zh_TW dc.subject (關鍵詞) CCC模型 zh_TW dc.subject (關鍵詞) ADR en_US dc.subject (關鍵詞) Mispricing en_US dc.subject (關鍵詞) COVID-19 en_US dc.subject (關鍵詞) Univariate GARCH model en_US dc.subject (關鍵詞) DCC model en_US dc.subject (關鍵詞) CCC model en_US dc.title (題名) 標的股票與ADR錯價關係之研究－以台積電和聯電COVID-19疫情前後為例 zh_TW dc.title (題名) A study on mispricing between underlying stock and its ADR – Comparing COVID-19 impacts on TSMC and UMC en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 中文部分1.王凱立、陳美玲（2003），「亞洲金融風暴發生前後美國與台灣股市動態關聯之進一步研究」，經濟論文叢刊，第31期，頁191-252。2.陳旭昇（2003）。《時間序列分析－總體經濟與財務金融之應用》。 臺北：東華書局。3.黃營杉、李銘章（2005），「台灣母公司股票報酬與其ADR報酬間資訊傳遞之研究」，東吳經濟商學學報，第48期，頁1-32。4.張光亮、黃宗佑（2010），「美國存託憑證與母國股票報酬間之動態關聯性－極端尾部相依性以及Kendall’s tau之研究」，經濟研究，47卷2期頁305-356。5.楊奕農（2017）。《時間序列分析－經濟與財務上之應用》。臺北：雙葉書廊。6.聶建中、高友笙、楊超翔（2011），「次級房貸危機前後美股對亞股的不對稱性蔓延效果」，中原企管評論，第9期，頁25-52。英文部分1.Alhaj-Yassen, Y.S., Ladd, D. (2019), “Which sentiments do US investors follow when trading ADRs?”, Journal of Economics and Finance, 43, 506-527.2.Bollerslev, T., Engle, R.F., Wooldridge, J.M. (1998), “A capital asset pricing model with time varying covariances.”, Journal of Political Economy, 96, 116-131.3.Bollerslev, T. (1986), “Generalized Autoregressive Conditional Heteroskedasticity.”, Journal of Econometrics, 31, 307-327.4.Baker, M., Stein, J. (2004), “Market liquidity as a sentiment indicator.”, Journal of Financial Markets, 7, 271–299 .5.Esqueda, O.A., Luo, Y., Jackson, D.O. (2013), “The linkage between the U.S. “fear index” and ADR premiums under non-frictionless stock markets.”, Journal of Economics and Finance, 39, 541-556.6.Engle, R.F., Kroner, K.F. (1995), “Multivariate simultaneous generalized ARCH.”, Econometric Theory, 11, 122-150.7.Engle, R.F. (2002), “Dynamic conditional correlation-a sample class of multivariate GARCH models.”, Journal of Business and Economic Statistics, 20, 339-350.8.Engle, R.F., Kroner, K.F. (1995), “Multivariate Simultaneous Generalized Arch.”, Econometric Theory, 11(1) 122-150.9.Glosten, L.R., Jagannathan, R., Runkle, D.E. (1993), “On the Relation between the Expected value and the volatility of the Nominal Excess Return on Stocks.”, Journal of Finance, 48, 1779-1801.10.Gagnon, L., Karolyi, G.A. (2010), “Multi-market trading and arbitrage.”, Journal of Financial Economics, 97, 53-80.11.Grossmann, A., Ngo, N. (2020), “Economic policy uncertainty and ADR mispricing.”, Journal of Multinational Financial Management, 55, 1-19.12.Grossmann, A., Ngo, N., Simpson M.W. (2017), “The asymmetric impact of currency purchasing power imparities on ADR mispricing.”, 42, 74-94.13.Jiang, C.X. (1998), “Diversification with American Depositary Receipts: The Dynamics and the Pricing Factors.”, Journal of Business Finance and Accounting, 25, 683-699.14.Jondeau, E., Rockinger, M. (2006), “The Copula-GARCH Model of Conditional Dependencies: An International Stock Market Application.”, Journal of International Money and Finance, 25, 827-853.15.Nelson, D.B. (1991), “Conditional Heteroskedasticity in Asset Returns: A New Approach.”, Econometrica, 59, 347-370.16.Pontiff, J. (2007), “Costly arbitrage: evidence from closed-end funds.”, Quarterly Journal of Economics, 111, 1135-1151.17.Poshakwale, S.S., Aquino, K.P. (2008), “The dynamics of volatility transmission and information flow between ADRs and their underlying stocks.”, Global Finance Journal, 19, 187-201.18.Shu, J. (2003), “ADRs and U.S. Market sentiment.”, Journal of Investing Winter 12, 87-95.19.Vaira, T.A., Ramaprasad, B. (2002), “Information and volatility linkage under external shocks Evidence from dually listed Australian stocks.”, International Review of Financial Analysis, 11, 59-71. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202201396 en_US
