| dc.contributor.advisor | 屠美亞 | zh_TW |
| dc.contributor.advisor | Mia, Twu | en_US |
| dc.contributor.author (Authors) | 黃聖仁 | zh_TW |
| dc.contributor.author (Authors) | Huang, Sheng-Jen | en_US |
| dc.creator (作者) | 黃聖仁 | zh_TW |
| dc.creator (作者) | Huang, Sheng-Jen | en_US |
| dc.date (日期) | 2008 | en_US |
| dc.date.accessioned | 8-Dec-2010 15:42:55 (UTC+8) | - |
| dc.date.available | 8-Dec-2010 15:42:55 (UTC+8) | - |
| dc.date.issued (上傳時間) | 8-Dec-2010 15:42:55 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0096357002 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/49643 | - |
| 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) | 96357002 | zh_TW |
| dc.description (描述) | 97 | zh_TW |
| dc.description.abstract (摘要) | 本研究之宗旨在於探究中國大陸對亞洲區域內國家的金融市場影響程度之變化。由過去的各國股市日報酬率資料間相關程度與政策改變間的影響結果，來觀察是否未來在兩岸政策更開放下會使中國大陸對台灣的影響程度上升，進而使國際間投資組合的風險分散效果下降。本研究自DataStream選取台灣、香港、中國大陸、泰國、印尼、新加坡、馬來西亞、菲律賓、日本以及美國等十國的股價指數日資料，以對數轉換為日報酬率後年化加以分析。選取時間自1991年7月15日(中國大陸上海證券交易所股價指數公開後)至2008年12月31日。本研究選用的方法為使用風險值(VaR; Value at Risk)的概念來取代傳統的標準差，衡量以該十國所分別組成的各投資組合風險值變動情形；以及由風險值所衍生出的Diversification Benefit與Incremental VaR的結果。發現到僅由亞洲區域國家內組成的投資組合風險分散效果逐漸下降；且效果並不如有納入區域外國家(如美國)的投資組合。接著本研究將Gaussian Copula模型放入VaR中以增加對極端值的捕捉能力，結果發現本研究所選用的指數加權移動平均法所求得之相關係數已可有效反應出各國之間的相依程度，即加入Copula的效果有限。另外藉由Copula所求得之相關係數顯示，台灣、香港對中國大陸之間的相依程度已逐漸上升，並開始出現超越美國之現象，其中又以2005年為上升趨勢的起點。最後本研究以向量自我迴歸模型(VARs)來驗證2005年前後中國大陸股市對其他亞洲區域國家的影響力是否存在結構性的改變；並再佐以變異數拆解之方法來觀察2005年前後各國家之間自發性衝擊對彼此之間的影響程度變化。研究結果發現，透過VARs可證明中國大陸對亞洲區域各國的影響力在2005年後轉變為顯著；僅對美國不存在此一現象。另外變異數拆解的結果也顯示各國之間的相依程度在2005年後有明顯的上升，中國大陸對各國的影響程度亦然。透過本研究之結論，在未來兩岸將簽訂金融監理備忘錄使整合關係提升的環境下，需提醒投資人整合關係的上升將使得以之為標的之投資組合風險分散效果下降，需作為投資策略之考量。 | zh_TW |
| dc.description.abstract (摘要) | The object of this research is to find out the trend of dependence and correlation between China and other Asian countries. Based on past information about the relationship between equity markets’ correlation and changes in policies, this research can make suggestions to the foreseeable future of Taiwan and China whose relationship will be more solid due to new policy. The data of this research are gathered from DataStream, which includes Taiwan, Hong Kong, China, Thailand, Indonesia, Singapore, Malaysia, Philippines, Japan and United States. Selected from 1991/07/15 (when the Shanghai SE Composite went public) to 2008/12/31, this research calculates the annualized daily return using natural logarithms of two consecutive daily index prices. This research uses Value at Risk (VaR) to measure the risk exposure of portfolios formed by ten countries, and extends to the use of Diversification Benefit and Incremental VaR. The results found out that the diversification effects of portfolio which includes only Asian countries are decreasing and inferior to the effects when cross region countries are included. The second study of this research is to combine Gaussian Copula Model with VaR to capture the effects of extreme values. Empirical results found out that the VaR using Exponentially Weighted Moving Average method is good enough for analyzing Asian stock markets. The correlation in Copula model suggests that the dependence between Taiwan and China had increased since 2005 and has the increasing trend which might overwhelm the dependence between Taiwan and United States. Final research is about using Vector Autoregressions Model (VARs) to testify is there exist any structural change of dependence before and after 2005, and using Variance Decomposition to observe the relationships between these ten countries. The results found out that there exist structural change in 2005, the post-2005 periods shows that for Asian countries the effect from China are significant and greater than pre-2005 periods. | en_US |
| dc.description.tableofcontents | 第壹章 緒論.................................................7第一節 研究背景與動機........................................7第二節 研究目的.............................................9第三節 研究資料範圍、來源及期間..............................11第四節 研究架構與流程.......................................12第貳章 文獻探討............................................15第一節 國際風險分散研究之相關文獻............................15第二節 風險值(VaR)之相關文獻................................17第三節 Copula模型之相關文獻.................................19第叄章 研究設計與方法.......................................21第一節 風險值(VaR).........................................21第二節 Gaussian Copula Model..............................25第三節 單根檢定(Unit Root Test)............................29第四節 向量自我迴歸模型(VARs)...............................31第五節 變異數拆解(Variance Decomposition)...................32第肆章 實證結果與分析.......................................33第一節 資料描述............................................33第二節 風險值(VaR)結果分析..................................35第三節 Gaussian Copula模型結果分析..........................46第四節 向量自我迴歸模型(VARs)結果分析........................54第伍章 結論與建議...........................................65第一節 結論................................................65第二節 對後續研究之建議.....................................69參考文獻...................................................70 | zh_TW |
| dc.format.extent | 329755 bytes | - |
| dc.format.extent | 157186 bytes | - |
| dc.format.extent | 331627 bytes | - |
| dc.format.extent | 426387 bytes | - |
| dc.format.extent | 349655 bytes | - |
| dc.format.extent | 338133 bytes | - |
| dc.format.extent | 492810 bytes | - |
| dc.format.extent | 1036628 bytes | - |
| dc.format.extent | 343803 bytes | - |
| dc.format.extent | 366537 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0096357002 | en_US |
| dc.subject (關鍵詞) | 風險分散 | zh_TW |
| dc.subject (關鍵詞) | 投資組合策略 | zh_TW |
| dc.subject (關鍵詞) | 亞洲 | zh_TW |
| dc.subject (關鍵詞) | 中國大陸 | zh_TW |
| dc.subject (關鍵詞) | 風險值 | zh_TW |
| dc.subject (關鍵詞) | Copula | zh_TW |
| dc.subject (關鍵詞) | 向量自我迴歸模型 | zh_TW |
| dc.subject (關鍵詞) | 變異數拆解 | zh_TW |
| dc.subject (關鍵詞) | Risk Diversification | en_US |
| dc.subject (關鍵詞) | Portfolio Strategy | en_US |
| dc.subject (關鍵詞) | Asia | en_US |
| dc.subject (關鍵詞) | China | en_US |
| dc.subject (關鍵詞) | VaR | en_US |
| dc.subject (關鍵詞) | Value at Risk | en_US |
| dc.subject (關鍵詞) | Copula | en_US |
| dc.subject (關鍵詞) | VARs | en_US |
| dc.subject (關鍵詞) | Vector Autoregressions Model | en_US |
| dc.subject (關鍵詞) | Variance Decomposition | en_US |
| dc.title (題名) | 亞洲金融市場整合與其對投資組合策略影響之研究—中國大陸之影響 | zh_TW |
| dc.title (題名) | Asian Financial Market Integration and Its Effects on Portfolio Strategy— Mainland China`s Impacts | en_US |
| dc.type (資料類型) | thesis | en |
| dc.relation.reference (參考文獻) | 中文文獻： | zh_TW |
| dc.relation.reference (參考文獻) | 1. 花文妤，民國96年，「Copula模式之下雙變元存活資料之統計推論」，國立交通大學統計學研究所碩士論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 2. 林志坤，民國95年，「VaR-x在股票、外匯及投資組合之應用」，國立政治大學財政系研究所碩士論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 3. 林進益，民國96年，「美股報酬率會影響亞洲股市報酬率嗎？以亞洲四小龍實證為例」，國立中山大學財務管理學系研究所博士論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 4. 林淑蓉，民國95年，「風險值與風險管理策略之研究」，國立中央大學財務金融研究所碩士論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 5. 林勝宏，民國93年，「國際股市關聯性結構之研究—Copula模型之應用」，國立臺灣科技大學資訊管理系研究所碩士論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 6. 馬其明，民國96年，「匯率風險值衡量之實證研究—以新台幣、日圓、英鎊、歐元匯率為例」， 國立中央大學財務金融學系碩士在職專班論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 7. 陳凱音，民國95年，「固定收益證券之巿場風險管理—風險值之應用」，國立中央大學財務金融學系碩士在職專班論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 8. 許玲真，民國95年，「不同風險值模型在亞洲金融市場之應用」，國立臺灣大學財務金融學研究所碩士論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 9. 盛曉青，民國87年，「東南亞金融風暴期間亞洲各國股市之共整合關係與變異數分解之研究」，東吳大學企業管理學系研究所碩士論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 10. 劉哲誠，民國96年，「Copula應用在CDO定價之研究」，東吳大學商用數學系碩士論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 11. 龍湘霖，民國94年，“Dependence Structure Between the Twin Crisis: A Copula Analysis.”，國立中正大學國際經濟研究所碩士論文。 | zh_TW |
| dc.relation.reference (參考文獻) | 12. Liu, M. Y., C. Y. Wu, and H. F. Lee, 2008, “VaR Evaluation with Power EWMA Model－Conservativeness, Accuracy and Efficiency.” Soochow University, Working Paper. | zh_TW |
| dc.relation.reference (參考文獻) | 外文文獻： | zh_TW |
| dc.relation.reference (參考文獻) | 1. Alper, O., and C. Atilla, 2007, “Portfolio Value-at-Risk with Time-Varying Copula: Evidence from the Americas.” Marmara University, Working Paper. | zh_TW |
| dc.relation.reference (參考文獻) | 2. Bartram, S. M., S. J. Taylor, and Y. H. Wang, 2005, “The Euro and European Financial Market Integration.” Journal of Banking and Finance. | zh_TW |
| dc.relation.reference (參考文獻) | 3. Chatterjee, A., O. F. Ayadi, and B. Maniam, 2003/4/29, “Asian Financial Crisis: The Pre- and Post-Crisis Analysis of Asian Equity Markets.” Managerial Finance, ABI/INFORM Global pg. 62. | zh_TW |
| dc.relation.reference (參考文獻) | 4. Cheng, H., 2000, “Cointegration Test for Equity Market Integration: The Case of the Great China Economic Area (Mainland China, Hong Kong, and Taiwan), Japan and the United States.” Ph.D. Thesis, The George Washington University. | zh_TW |
| dc.relation.reference (參考文獻) | 5. Chiang, K. C. H., and C. Leonhard, 2007/1/16, “International Diversification: The Within- and Between-Region Effects.” Journal of Investing, 51. | zh_TW |
| dc.relation.reference (參考文獻) | 6. Christoffersen, P.F., 1998, “Evaluating Interval Forecasts.” International Economic Review, 39, 841-862. | zh_TW |
| dc.relation.reference (參考文獻) | 7. Dickey, David, and W. A. Fuller, July 1981, “Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root”, Econometrica, Vol.49, pp.1057-1072. | zh_TW |
| dc.relation.reference (參考文獻) | 8. Heatter, C., and D. Remstein, June 2008 - March 2009, “Investment Analytics and Consulting Newsletter.” J.P. Morgan World Wide Securities Services. | zh_TW |
| dc.relation.reference (參考文獻) | 9. Hendricks, D., 1996, “Evaluation of Value-at-risk Models Using Historical Data” Economic Policy Review, Federal Reserve Bank of New York, 2, 39-69. | zh_TW |
| dc.relation.reference (參考文獻) | 10. Jorion, P., 2000, “Value at Risk—The New Benchmark for Managing Financial Risk, Second Edition.” McGraw-Hill. | zh_TW |
| dc.relation.reference (參考文獻) | 11. Malevergne, Y., and D. Sornette, 2003, “Testing the Gaussian Copula Hypothesis for Financial Assets Dependences.” Quantitative Finance, 3, 231-250. | zh_TW |
| dc.relation.reference (參考文獻) | 12. Patton, A. J., 2006, “Estimation of Multivariate Models for Time Series of Possibly Different Lengths.” Journal of Applied Econometrics, 21: 147–173. | zh_TW |
| dc.relation.reference (參考文獻) | 13. Patton, A. J., May 2006, “Modelling Asymmetric Exchange Rate Dependence.” International Economic Review, Vol. 47, No. 2. | zh_TW |
| dc.relation.reference (參考文獻) | 14. Sklar, A., 1959, ”Fonctions de re’partition a"n dimensions et leurs marges.” Publications de l’Institut Statistique de l’Universite’ de Paris, 8, 229–231. | zh_TW |
