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  1. NTU Theses and Dissertations Repository
  2. 管理學院
  3. 國際企業學系
Please use this identifier to cite or link to this item: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/18070
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dc.contributor.advisor郭震坤
dc.contributor.authorTzu-Chiang Linen
dc.contributor.author林子強zh_TW
dc.date.accessioned2021-06-08T00:50:13Z-
dc.date.copyright2015-07-20
dc.date.issued2015
dc.date.submitted2015-07-07
dc.identifier.citation[1] Hull.J.C..Option,Futures and other Derivatives. Prentice-Hall.New Jersey.2006
[2] Anderson, T.G. , & Bollerslev, T. (1998). Answering the skeptics:Yes, Standard Volatility Models do Provide Accurate Forecasts. International Economic Review, 39, 885-905.
[3] Brooks, C., & S.P.Burke, (1998). Forecasting exchange rate volatility conditional variance models selected by information criteria. Economics Letters, 61, 273-278.
[4] Engel, Charles, & Kenneth, D., West, (2005). Exchange Rate and Fundamentals. Journal of Political Economy, 113(3), 485-517.
[5] Engel, R.F., & Ng, V.K. (1993). Measuring and testing the impact of news on volatility. Journal of Finance, 48,1749-1801.
[6] Fisher, Radovan, & Roman Horvath,(2010). Central Bank communication and Exchange Rate Volatility:A GARCH Analysis. Macroeconomics and Finance in Emerging Market Economics, 3(2), 25-31.
[7] Hamadu, Dallah, &Adeleke Ismaila, (2009). On Modeling the Nigerian Currency (naira) Exchange Rate against Major Regional and World Currencies. Journal of Business and Economics, 2, 42-52.
[8] Jorion, Philippe. (1995). Predicting volatility in the foreign exchange market. The Journal of Finance, 1, 507-528.
[9] Laakkonen, H. (2007). Impact of Macroeconomic News on Exchange Rate Volatility. Finnish Economic Papers, 20, 23-40.
[10] Lastrapes, William, D. (1989). Exchange rate volatility and U.S. monetary policy:An ARCH application. Journal of Money, Credit, and Banking, 21, 66-77.
[11] McKenzie, M.D. (1997). ARCH Modeling of Australian Bilateral Exchange Rate Data. Applied Financial Economics, 7, 147-164.
[12] Nelson, D.B. (1991). Conditional heteroscedasticity in asset returns:A new approach. Econometrica, 59, 347-370.
[13] Pesaran, B., & G. Robinson, (1993). The European exchange rate mechanism and the volatility of the sterling-deutschmark exchange rate. Economic Journal, 103, 1418-1431.
[14] Abdalla , Suliman Zakaria Suliman , (2012). Modeling Exchange Rate Volatility using GARCH Models:Empirical Evidence from Arab Countries. International Journal of Economics and Finance, Vol. 4, No. 3 ; March 2012.
[15] Poon, Ser-Huang, and Clive W.J. Granger. (2003). 'Forecasting Volatility in Financial Markets: A Review .' Journal of Economic Literature, 41(2): 478-539.
[16] B. B. Mandelbrot (1963) The variation of certain speculative prices, Journal of
Business, XXXVI (1963), pp. 392–417.
[17] Brooks, C; Burke, S. (1998). “Forecasting exchange rate volatility using conditional variance models selected by information criteria” Economics Letters 61, 273-278.
[18] Black, F. (1976), “Studies of Stock Price Volatility Changes”, Proceedings of the Business and Economics Section of the American Statistical Association , 177–181.
[19] Nelson, D.B. (1991), ”Conditional heteroskedasticity in asset returns: a new approach”, Econometrica 59, 347-370.
[20] Engle, R; Patton, A. (2001), ”What good is a volatility model?”, Research paper, Quantitative Finance, Volume 1, 237-245.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/18070-
dc.description.abstract本研究以GARCH模型以及E-GARCH模型建構G7貨幣之日報酬波動率模式,以台灣的直接報價匯率數據進行分析,並和Abdalla , Suliman Zakaria Suliman (2012)所研究的19種阿拉伯國家貨幣比較,實證結果顯示本研究探討的7種貨幣日報酬率的波動率皆有持續性,而Abdalla , Suliman Zakaria Suliman (2012)所研究的19種貨幣中的7種貨幣日報酬率的波動率具有持續性,顯示出已開發國家和開發中國家在貨幣日報酬率的顯著差異。zh_TW
dc.description.provenanceMade available in DSpace on 2021-06-08T00:50:13Z (GMT). No. of bitstreams: 1
ntu-104-R02724057-1.pdf: 2981561 bytes, checksum: bfc320b629803799ed6c3ad404b3a582 (MD5)
Previous issue date: 2015
en
dc.description.tableofcontents目錄
第一章 緒論及模型介紹 1
1.1、 研究動機與目的 1
1.2、 研究架構 2
第二章、文獻探討 3
2.1、介紹 3
2.1.1、波動率 3
2.1.2、波動率的特性 5
2.1.3、時間序列 7
2.2、論文回顧 11
2.2.1、文獻研究目的 11
2.2.2、文獻資料來源和模型建構 11
2.2.3、文獻研究成果 16
第三章 研究方法與模型分析 18
3.1、研究方法 18
3.2、資料及模型建構 18
3.3、G7貨幣報酬率統計量 20
3.4、GARCH模型檢定結果 24
3.5、E-GARCH模型檢定結果 27
第四章、結論 31
附錄 33
參考文獻 40
dc.language.isozh-TW
dc.title以GARCH模型建構外匯波動率模式:以G7貨幣為例zh_TW
dc.titleUsing GARCH Models to for modeling Exchange Rate Volatility:Empirical Evidence from G7 Currenciesen
dc.typeThesis
dc.date.schoolyear103-2
dc.description.degree碩士
dc.contributor.oralexamcommittee李志偉,李顯峰
dc.subject.keyword外匯波動率,GARCH,E-GARCH,zh_TW
dc.subject.keywordexchange rate volatility,GARCH,E-GARCH,en
dc.relation.page42
dc.rights.note未授權
dc.date.accepted2015-07-07
dc.contributor.author-college管理學院zh_TW
dc.contributor.author-dept國際企業學研究所zh_TW
Appears in Collections:國際企業學系

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