Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/131181
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dc.contributor.advisor徐士勛zh_TW
dc.contributor.advisorHsu, Shih-Hsunen_US
dc.contributor.author王羿婷zh_TW
dc.contributor.authorWang, Yi-Tingen_US
dc.creator王羿婷zh_TW
dc.creatorWang, Yi-Tingen_US
dc.date2020en_US
dc.date.accessioned2020-08-03T10:11:55Z-
dc.date.available2020-08-03T10:11:55Z-
dc.date.issued2020-08-03T10:11:55Z-
dc.identifierG0107258022en_US
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/131181-
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.description107258022zh_TW
dc.description.abstract本文藉由時域架構下的 Granger 因果關係檢定及 Breitung & Candelon提出之頻域架構下的因果關係檢定,來探討台灣股市報酬與經濟活動間的因果關係,並進一步了解該因果關係是否因為存在於不同頻率下而有所改變,亦即該因果關係是否存在於不同週期之下。\n當我們在時域架構上來觀察台灣股市與經濟活動間的因果關係,可以發現當尚未加入控制變數時,兩變數間存在股市價格影響經濟活動之單向因果關係;一旦加入控制變數後,則兩個影響方向皆不存在因果關係。\n本研究額外進行頻域因果關係檢定後,能更進一步說明,該因果關係在 不同頻率間是否存在。唯有無條件模型下該單向因果關係存在於短期及中長期之下;然而,在有條件模型中該單向因果關係皆僅存在於中期及中長期之下,亦即台灣股市報酬到經濟活動之單向因果關係主要存在於低頻時,其餘頻率之間沒有任何明顯的因果關係。zh_TW
dc.description.tableofcontents1 前言 1\n1.1 研究動機與目的 ........................1\n1.2 研究架構............................ 2\n2 文獻回顧 3\n3 研究方法 7\n3.1 單根檢定............................ 8\n3.2 Grangercausality....................... 9\n3.3 頻域因果關係檢定....................... 10\n4 資料 14\n4.1 資料來源............................ 14\n4.2 資料說明............................ 15\n5 模型結果 21\n5.1 時域因果關係模型研究結果.................. 21\n5.2 頻域因果關係模型研究結果.................. 23\n5.2.1 雙變量無條件模型 .................. 23\n5.2.2 雙變量有條件模型 .................. 25\n5.3 不同架構下之因果關係模型結果 ............... 29\n5.4 更新資料至 2020 年 2 月與原資料期間之頻域因果關係模\n型結果比較........................... 31\n6 結論與建議 34\n附錄 36\n參考文獻 37\n\n圖目錄\n1 原始資料之時間趨勢圖 .................... 16\n2 一階差分後之時間趨勢圖................... 20\n3 應變數為 IIP 且自變數為 SP 之雙變量無條件模型的 F 檢\n定結果 ............................. 24\n4 應變數為 SP 且自變數為 IIP 之雙變量無條件模型的 F 檢\n定結果 ............................. 24\n5 應變數為 IIP 且自變數為 SP 並考慮當期控制變數之有條\n件模型的F檢定結果 ..................... 26\n6 應變數為 SP 且自變數為 IIP 並考慮當期控制變數之有條\n件模型的F檢定結果 ..................... 26\n7 應變數為 IIP 且自變數為 SP 並考慮落後一期控制變數之 有條件模型的F檢定結果................... 28\n8 應變數為 SP 且自變數為 IIP 並考慮落後一期控制變數之 有條件模型的F檢定結果.................. . 28\n\n表目錄\n1 敘述統計量.......................... . 17\n2 原始資料之無截距項無時間趨勢項 ADF 檢定結果 . . . . . 18\n3 一階差分後資料之無截距項無時間趨勢項 ADF 檢定結果 . 19\n4 Unconditional VAR Granger causality 之檢定結果 . . . . . 22\n5 Conditional VAR Granger causality 之檢定結果 . . . . . . 22\n6 時域及頻域因果關係檢定結果之整理 ............ 32\n7 更新資料與原資料期間之頻域因果關係模型結果比較 . . . 33zh_TW
dc.format.extent929686 bytes-
dc.format.mimetypeapplication/pdf-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0107258022en_US
dc.subject股市報酬zh_TW
dc.subject頻域因果關係zh_TW
dc.subjectGranger因果關係檢定zh_TW
dc.title台灣股市報酬與經濟活動之頻域因果關係zh_TW
dc.typethesisen_US
dc.relation.reference[1] 姜文怡 (2000),「股票報酬預測產出之不對稱性效果」,碩士論文, 淡江大學,財務金融研究所。\n[2] 董澍琦,楊聲勇與藍淑鳳 (2005),「股票報酬與經濟成長–亞太新興 國家之實證研究」,東海管理評論,7,285–304。\n[3] Breitung, J. and B. Candelon (2006), “Testing for short- and long- run causality: a frequency-domain approach,”Journal of Economet- rics, 132, 363–378.\n[4] Dickey, D.A. and W.A. Fuller (1981), “Likelihood ratio statistics for autoregressive time series with a unit root,”Econometrica: journal of the Econometric Society, 49,1057–1072.\n[5] Dufour,J.M.andE.Renault(1998),“ShortRunandLongRunCausal- ity in Time Series:Theory,”Econometrica, 66, 1099–1125.\n[6] Fama, E. F.(1990), “Stock returns, expected returns, and real activ- ity,”The Journal of Finance, 45, 1089-1108.\n[7] Geweke, J. (1982), “Measurement of linear dependence and feedback between multiple time series,” Journal of the American Statistical As- sociation, 77, 304–313.\n[8] Granger, C.W.J. (1969), “Investigating causal relations by economet- ric models and cross-spectral methods,”Econometrica: journal of the Econometric Society, 37, 424–438.\n[9] Hosoya, Y. (1991), “The decomposition and measurement of the in- terdependence between second-order stationary process,”Probability Theory and Related Fields, 88, 429–444.\n[10] Hou, H. and S.Y. Cheng (2010), “The roles of stock market in the finance-growth nexus: time series cointegration and causality evi- dence from Taiwan,”Applied Financial Economics, 20, 975-981.\n[11] Huang, B.N. and C.W. Yang (2004), “Industrial Output and Stock Price Revisited: An Application of the Multivariate Indirect Causal- ity Model,”The Manchester School, 72, 347-362.\n[12] Ibrahim, H.M. (1999), “Macroeconomic variables and stock prices in Malaysia: an empirical analysis,”Asian Economic Journal, 13, 219– 231.\n[13] Kaplan, M. (2008), “The impact of stock market on real economic ac- tivity: evidence from Turkey,”Journal of Applied Sciences, 8, 374– 378.\n[14] Pearce, D.K. (1983), “Stock prices and the economy,” Federal reserve bank of Kansas city economic review, 68, 7–22.\n[15] Singh, D. (2010), “Causal relationship between macro-economic vari- ables and stock market: A case study for India,”Pakistan Journal of Social Sciences, 30, 263–274.\n[16] Thach, N.N., L.H. Anh and H.T.N. Phuong (2019), “Frequency Do- main Causality Analysis of Stock Market and Economic Activites in Vietnam,” In: Kreinovich V., Sriboonchitta S. (eds) Structural Changes and their Econometric Modeling. TES 2019. Studies in Com- putational Intelligence, 808. Springer, Cham\n[17] Tiwari, A. K., M. I. Mutascu, C. T. Albulescu and P. Kyophilavong (2015), “Frequency domain causality analysis of stock market and eco- nomic activity in India,”International Review of Economics and Fi- nance, 39, 224 - 238.zh_TW
dc.identifier.doi10.6814/NCCU202000664en_US
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