Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/118788| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 徐士勛 | zh_TW |
| dc.contributor.author | 陳如忻 | zh_TW |
| dc.contributor.author | Chen, Ju-Hsin | en_US |
| dc.creator | 陳如忻 | zh_TW |
| dc.creator | Chen, Ju-Hsin | en_US |
| dc.date | 2018 | en_US |
| dc.date.accessioned | 2018-07-20T10:16:19Z | - |
| dc.date.available | 2018-07-20T10:16:19Z | - |
| dc.date.issued | 2018-07-20T10:16:19Z | - |
| dc.identifier | G0105258026 | en_US |
| dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/118788 | - |
| 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 | 105258026 | zh_TW |
| dc.description.abstract | 近年來由於亞洲區經貿整合更為緊密，彼此間的貿易及貨幣相互影響力大為提升，因此我們採用Engel、Mark and West (2014,Econometric Reviews)所提出之因子模型，並分別比較了以全球匯率以及單以亞洲匯率資料所萃取出之因子結合其他匯率理論模型，探討各模型對亞洲匯率之預測能力。我們採用遞迴法對樣本外資料進行短至長期不同區間的預測，並使用Theil`s U比例及Clark and West之檢定評估模型表現。實證結果顯示，與隨機漫步模型預測相比，各模型在長期預測下皆有較佳的預測表現。其中，相較於亞洲因子，全球因子對於亞洲匯率有較好的預測能力；台幣、港幣及韓元在利用全球因子的模型下有較優良之預測表現，但日圓則以亞洲因子結合購買力平價模型表現為最好。此結果顯示各幣別皆有其適合的因子樣本及預測模型。\n整體而言，因子結合購買力平價模型表現為最佳，而在考慮近期樣本的表現中，因子結合泰勒法則模型之預測表現則優於隨機漫步模型。 | zh_TW |
| dc.description.tableofcontents | 1 緒論 1\n2 計量模型 4\n2.1 因子模型 4\n2.2 因子結合其他匯率預測模型 5\n2.2.1 泰勒法則模型 5\n2.2.2 購買力平價模型 7\n2.2.3 貨幣學派模型 7\n2.2.4 未拋補利率平價模型 8\n3 實證方法 10\n3.1 資料說明 10\n3.2 資料期間內各國貨幣走勢 13\n3.2.1 美元指數2008:09-2017:08期間走勢 13\n3.2.2 OECD主要貨幣2008:09-2017:08期間走勢 14\n3.2.3 亞洲區主要貨幣2008:09-2017:08期間走勢 17\n3.3 研究方法 20\n3.4 預測表現評估與檢定 20\n3.4.1 Theil`s U檢定 20\n3.4.2 Clark and West檢定 21\n4 實證結果 22\n4.1 全球因子對匯率之預測表現 22\n4.2 亞洲因子對匯率之預測表現 24\n4.3 以全球及亞洲因子對亞洲匯率之預測表現 26\n4.4 亞洲國家個別表現 27\n4.5 樣本外不同區間內之預測表現 30\n5 結論 33 | zh_TW |
| dc.format.extent | 954290 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.source.uri | http://thesis.lib.nccu.edu.tw/record/#G0105258026 | en_US |
| dc.subject | 因子模型 | zh_TW |
| dc.subject | 樣本外預測 | zh_TW |
| dc.subject | 遞迴法 | zh_TW |
| dc.title | 以匯率因子模型為基礎的亞洲各國匯率預測 | zh_TW |
| dc.title | Asian Exchange Rate Forecasts Based on Exchange Rate Factor Model | en_US |
| dc.type | thesis | en_US |
| dc.relation.reference | 林聖智 (2007). “總體經濟基本面是否有助於匯率的預測”. 未出版之碩士論文, 國立中央大學經濟學研究所, 桃園縣。\nBerkowitz, J. and Giorgianni, L. (2001). “Long-horizon Exchange Rate Predictability?” Review of Economics and Statistics, 83, 81-91.\nCorte, P. D., Sarno, L. and Tsiakas, I. (2011). “Spot and forward volatility in foreign exchange.” Journal of Financial Economics, 100, 496-513.\nEngel, C., Mark, N. C. and West, K. D. (2015). “Factor model forecasts of exchange rates.” Econometric Reviews, 34, 32-55.\nFrenkel, J. A. (1976). “A monetary approach to the exchange rate.” Scandinavian J. Econ. 78, no.2, 200-224.\nGroen, J. J. J. (2005). “Exchange rate predictability and monetary fundamentals in a small multi-country panel.” Journal of Money, Credit and Banking, 37, 495-516.\nGroen, J. J. J. (2006). “Fundamentals based exchange rate prediction revisited.” Manuscript, Bank of England.\nHodrick, R. J. and Prescott, E. C. (1981). “Post-war U.S. business cycles: an empirical investigation.” Journal of Money, Credit and Banking, Vol. 29, No.1, 1-16.\nMark, N. C. (1995). “Exchange rate and fundamentals: evidence on long-horizon predictability.” American Economic Review, 85, 201-218.\nMark, N. C. and Sul, D. (2001). “Nominal exchange rates and monetary fundamentals: Evidence from a small post-Bretton Woods sample.” Journal of International Economics, 53, 29-52.\nMeese, R. A. and Rogoff, K. (1983). “Empirical exchange rate models of the seventies:do they fit out of sample.” Journal of International Economics, 14, 3-24.\nPincheira, P. and Gatty, A. (2014). “Forecasting chilean inflation with international factors.” Working Paper 723, Central Bank of Chille.\nRapach, D. E. and Wohar, M. E. (2004). “Testing the monetary model of exchange rate determination: A closer look at panels.” Journal of International Money and Finance, 23(6), 841-865.\nStock, J. H. and Watson, M. W. (2002). “Macroeconomic forecasting using diffusion indexes.” Journal of Business and Economic Statistics, 20, 147-162.\nStock, J. H. and Watson, M. W. (2006). “Forecasting with many predictors.” ch.6 in Handbook of Economic Forecasting, ed. by Elliott, G., Granger, C. and Timmerman A. Elsevier, 515-554.\nWest, K. D. and Wong, K. F. (2014). “A factor model for co-movements of commodity prices.” Journal of International Money and Finance, 42, 289-309. | zh_TW |
| dc.identifier.doi | 10.6814/THE.NCCU.ECONO.011.2018.F06 | - |
| item.fulltext | With Fulltext | - |
| item.grantfulltext | open | - |
| item.cerifentitytype | Publications | - |
| item.openairecristype | http://purl.org/coar/resource_type/c_46ec | - |
| item.openairetype | thesis | - |
| Appears in Collections: | 學位論文 | |
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| 802601.pdf | 931.92 kB | Adobe PDF2 | View/Open |
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