Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/140685| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 徐士勛 | zh_TW |
| dc.contributor.advisor | Hsu, Shih-Hsun | en_US |
| dc.contributor.author | 張竣凱 | zh_TW |
| dc.contributor.author | Chang, Chun-Kai | en_US |
| dc.creator | 張竣凱 | zh_TW |
| dc.creator | Chang, Chun-Kai | en_US |
| dc.date | 2022 | en_US |
| dc.date.accessioned | 2022-07-01T08:26:14Z | - |
| dc.date.available | 2022-07-01T08:26:14Z | - |
| dc.date.issued | 2022-07-01T08:26:14Z | - |
| dc.identifier | G0109258003 | en_US |
| dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/140685 | - |
| dc.description | 碩士 | zh_TW |
| dc.description | 國立政治大學 | zh_TW |
| dc.description | 經濟學系 | zh_TW |
| dc.description | 109258003 | zh_TW |
| dc.description.abstract | 本研究使用 Shi, Phillips and Hurn (2018) 提出的遞迴演進窗口法，探討台灣股市與國際股市之間隨時間改變的領先落後關係。我們選定1997年1月至2021年12月的台灣加權股價指數以及8個已開發國家股票市場大盤指數作為分析資料，並建置未控制美國股市影響下之雙變量模型以及控制美國股市影響之三變量模型進行實證分析。研究結果顯示，在未控制美國股市影響下，台灣股市曾單向領先日本股市，韓國股市也曾單向領先台灣股市，但中國股市與台灣股市於任何時點皆不存在領先落後關係，而香港股市與台灣股市曾存在雙向領先落後關係；整體而言，亞洲各國股市與台灣股市的領先落後關係時期存在較大差異。相較之下，英國、德國、法國股市與台灣股市都曾存在雙向領先落後關係，且歐洲各國股市與台灣股市的領先落後關係時期較為一致。當控制美國股市的影響後，亞洲各國股市與台灣股市的領先落後關係時點依然迥異，且歐洲各國股市與台灣股市的領先落後關係時期也產生顯著變化，驗證了美國股市確實對各國股市具有相當影響力。 | zh_TW |
| dc.description.abstract | This study uses the recursive evolving window method proposed by Shi, Phillips and Hurn (2018) to explore the time-varying lead-lag relationship between Taiwan and international stock markets. We select Taiwan`s weighted stock price index from January 1997 to December 2021 and the stock market index of 8 developed countries as the analysis data, and build the bivariate model and the trivariate model which controls for the influence of US stock market in particular for the empirical analysis. The results of bivariate models show that, Taiwan stock market once led Japanese stock market, and South Korean stock market once led Taiwan stock market, but Chinese and Taiwan stock market did not have a lead-lag relationship at any time. Besides, there was a bidirectional lead-lag relationship between Hong Kong and Taiwan stock market; on the whole, there is a big difference in the period of the lead-lag relationship between Asian and Taiwan stock market. In contrast, UK, German and French stock markets and Taiwan stock markets all had a bidirectional lead-lag relationship once, and the period of the lead-lag relationship between European and Taiwan stock market are relatively consistent. After controlling for the influence of U.S. stock market, the period of the lead-lag relationship between Asian and Taiwan stock market is still very different, and the period of the lead-lag relationship between European and Taiwan stock market also changed significantly, which proves that U.S. stock market does have a considerable impact on the stock markets of various countries. | en_US |
| dc.description.tableofcontents | 1 緒論 1\n2 文獻回顧 2\n3 研究方法 5\n3.1 單根檢定 6\n3.2 格蘭傑因果關係 8\n3.3 時變因果關係模型 9\n3.3.1 向前擴張窗口法 11\n3.3.2 滾動窗口法 12\n3.3.3 遞迴演進窗口法 13\n3.4 拔靴法估計模型臨界值 14\n4 資料說明與實證模型 17\n4.1 資料說明與敘述統計 17\n4.2 實證模型 26\n5 實證結果 28\n5.1 遞迴演進窗口法雙變量模型 28\n5.2 遞迴演進窗口法三變量模型 43\n6 結論 55\n7 參考文獻 57\n\n圖目錄\n1 向前擴張窗口法過程示意圖 12\n2 滾動窗口法過程示意圖 13\n3 遞迴演進窗口法過程示意圖 14\n4 台灣加權股價指數價格序列 23\n5 台灣加權股價指數報酬率序列 23\n6 美國道瓊工業指數價格序列 23\n7 美國道瓊工業指數報酬率序列 23\n8 日本日經225指數價格序列 23\n9 日本日經225指數報酬率序列 23\n10 韓國綜合股價指數價格序列 24\n11 韓國綜合股價指數報酬率序列 24\n12 中國深圳綜合指數價格序列 24\n13 中國深圳綜合指數報酬率序列 24\n14 香港恆生指數價格序列 24\n15 香港恆生指數報酬率序列 24\n16 英國FTSE 100指數價格序列 25\n17 英國FTSE 100指數報酬率序列 25\n18 德國DAX 30指數價格序列 25\n19 德國 DAX 30 指數報酬率序列 25\n20 法國 CAC 40 指數價格序列 25\n21 法國 CAC 40 指數報酬率序列 25\n22 美國領先台灣之雙變量模型檢定結果 29\n23 台灣領先美國之雙變量模型檢定結果 29\n24 日本領先台灣之雙變量模型檢定結果 31\n25 台灣領先日本之雙變量模型檢定結果 31\n26 韓國領先台灣之雙變量模型檢定結果 33\n27 台灣領先韓國之雙變量模型檢定結果 33\n28 中國領先台灣之雙變量模型檢定結果 35\n29 台灣領先中國之雙變量模型檢定結果 35\n30 香港領先台灣之雙變量模型檢定結果 36\n31 台灣領先香港之雙變量模型檢定結果 36\n32 英國領先台灣之雙變量模型檢定結果 38\n33 台灣領先英國之雙變量模型檢定結果 38\n34 德國領先台灣之雙變量模型檢定結果 40\n35 台灣領先德國之雙變量模型檢定結果 40\n36 法國領先台灣之雙變量模型檢定結果 41\n37 台灣領先法國之雙變量模型檢定結果 41\n38 雙變量模型檢定結果統整 42\n39 日本領先台灣之三變量模型檢定結果 44\n40 台灣領先日本之三變量模型檢定結果 44\n41 韓國領先台灣之三變量模型檢定結果 46\n42 台灣領先韓國之三變量模型檢定結果 46\n43 中國領先台灣之三變量模型檢定結果 47\n44 台灣領先中國之三變量模型檢定結果 47\n45 香港領先台灣之三變量模型檢定結果 49\n46 台灣領先香港之三變量模型檢定結果 49\n47 英國領先台灣之三變量模型檢定結果 50\n48 台灣領先英國之三變量模型檢定結果 50\n49 德國領先台灣之三變量模型檢定結果 52\n50 台灣領先德國之三變量模型檢定結果 52\n51 法國領先台灣之三變量模型檢定結果 53\n52 台灣領先法國之三變量模型檢定結果 53\n53 三變量模型檢定結果統整 54\n\n表目錄\n1 各國大盤股價指數 18\n2 各國股市大盤報酬率序列敘述統計量 20\n3 各國股市大盤報酬率序列單根檢定 26 | zh_TW |
| dc.format.extent | 1488045 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.source.uri | http://thesis.lib.nccu.edu.tw/record/#G0109258003 | en_US |
| dc.subject | 遞迴演進窗口法 | zh_TW |
| dc.subject | 時變因果關係 | zh_TW |
| dc.subject | 股市領先落後關係 | zh_TW |
| dc.subject | Recursive evolving window approach | en_US |
| dc.subject | Time-varying causality | en_US |
| dc.subject | Stock market lead-lag relationship | en_US |
| dc.title | 台灣股市與國際股市之時變領先落後連動性研究 - 遞迴演進窗口法之應用 | zh_TW |
| dc.title | Time-varying Lead-lag Movement between Taiwan and International Stock Markets: An Application of Recursive Evolving Window Approach | en_US |
| dc.type | thesis | en_US |
| dc.relation.reference | Cagli, E. C. (2019). The Causal Relationship between Returns and Trading Volume in Cryptocurrency Markets: Recursive Evolving Approach. Blockchain Economics and Financial Market Innovation, 167–190.\nCagli, E. C. (2019). The Causality between Consumer Confidence Index and Stock Returns: Evidence from Recursive Evolving Granger Causality Test. Journal of Yasar University, 14, 164–172.\nDe Gooijer, J. G. and Sivarajasingham, S. (2008). Parametric and Nonparametric Granger Causality Testing: Linkages between International Stock Markets. Physica A, 387, 2547–2560.\nEmirmahmutoglu, F., Denaux Z., and Topcu, M. (2021). Time-varying Causality between Renewable and Non-renewable Energy Consumption and Real Output: Sectoral Evidence from the United States. Renewable and Sustainable Energy Reviews, 149, 111326.\nGharib, C., Mefteh-Wali, S., and Jabeur, S. B. (2021). The Bubble Contagion Effect of COVID-19 Outbreak: Evidence from Crude Oil and Gold Markets. Finance Research Letters, 38, 101703.\nGkillas, K., Tsagkanosa, A., and Vortelinos, D. I. (2019). Integration and Risk Contagion in Financial Crises: Evidence from International Stock Markets. Journal of Business Research, 104, 350–365.\nHammoudeh, S., Ajmi, A. N., and Mokni, K. (2020). Relationship between Green Bonds and Financial and Environmental Variables: A Novel Time-varying Causality. Energy Economics, 92, 104941.\nJiang, Y., Yu, M., and Hashmi, S. M. (2017). The Financial Crisis and Comovement of Global Stock Markets - A Case of Six Major Economies. Sustainability, 9(2), 260.\nMerica, I., Kim J. H., Gongc L., and Meric G. (2012). Co-movements of and Linkages between Asian Stock Markets. Business and Economics Research Journal, 3(1), 1–15.\nPapana, A., Kyrtsou, C., Kugiumtzis, D., and Diks, C. (2017). Financial Networks Based on Granger Causality: A Case Study. Physica A, 2017, 65–73.\nShi, S., Phillips, P. C. B., and Hurn, S. (2018). Change Detection and the Causal Impact of the Yield Curve. Journal of Time Series Analysis, 39, 966–987.\nShi, S., Hurn, S., and Phillips, P. C. B. (2019). Causal Change Detection in Possibly Integrated Systems: Revisiting the Money-income Relationship. Journal of Financial Econometrics, 18(1), 158–180.\nSwanson N. R. (1998). Money and Output Viewed through a Rolling Window. Journal of Monetary Economics, 41(3), 455 474.\nTang, Y., Xiong, J. J., Luo, Y., and Zhang, Y. C. (2019). How Do the Global Stock Markets Influence One Another? Evidence from Finance Big Data and Granger Causality Directed Network. International Journal\nof Electronic Commerce, 23(1), 85–109.\nThoma M. A. (1994). Subsample Instability and Asymmetries in Moneyincome Causality. Journal of Econometrics, 64(1-2), 279–306.\nZheng, Q. and Song, L. (2018). Dynamic Contagion of Systemic Risks on Global Main Equity Markets Based on Granger Causality Networks. Discrete Dynamics in Nature and Society, 2018, 9461870. | zh_TW |
| dc.identifier.doi | 10.6814/NCCU202200553 | en_US |
| item.openairecristype | http://purl.org/coar/resource_type/c_46ec | - |
| item.fulltext | With Fulltext | - |
| item.openairetype | thesis | - |
| item.grantfulltext | embargo_20250620 | - |
| item.cerifentitytype | Publications | - |
| Appears in Collections: | 學位論文 | |
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