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題名 探討外匯市場匯率波動不對稱性─以美元及日圓兌台幣為例
作者 廖怡婷
貢獻者 饒秀華
廖怡婷
關鍵詞 匯率波動不對稱效果
指數型GARCH模型(EGARCH)
門檻型GARCH模型(TGARCH, GJR GARCH)
異質自我相關迴歸模型(HAR-RV)
異質市場假說
日期 2009
上傳時間 9-五月-2016 14:53:16 (UTC+8)
摘要 近年來，金融資產報酬波動的推估一直是重要的研究課題。然而，過去的波動不對稱研究均集中在股票市場，探討外匯市場波動不對稱性的實證研究並不多，但若忽略其不對稱效果將影響未來波動預測的正確性。因此，本研究利用近十六年來美元及日圓兌台幣匯率日資料，以傳統的波動不對稱性指數型GARCH模型(EGARCH Model)、門檻型GARCH模型(TGARCH, GJR GARCH Model)，亦延用異質自我相關迴歸模型(HAR-RV Model)及修正型異質自我相關迴歸模型(Modified HAR-RV Model)分別探討美元及日圓兌台幣匯率波動是否存在不對稱現象及其不對稱程度，並加以分析。實證研究中，上述四種模型均顯示美元及日圓兌台幣匯率波動的確具有不對稱效果；美元兌台幣匯率波動，與股票市場一致，報酬率與波動度間呈負向關係，當台幣相對美元升值時，波動度較高；而日圓兌台幣匯率波動，與美元匯率變動方向相反，報酬率與波動度間呈正向關係，當台幣相對日圓貶值時，波動度較高。此外，以異質自我相關迴歸模型實證分析中，日波動落後項的影響力明顯大於週、月、季波動落後項，與Muller, et al. (1997)、Corsi (2004)及Andersen, et al. (2005)實證研究結果類似。
參考文獻 英文部份
     [1] Adler, M. and R. Qi (2003), ”Mexico’s Integration into the North American Capital Market”, Emerging Markets Review, Vol.4, pages 91-120.
     [2] Andersen, T. G., T. Bollerslev, F. X. Diebold and P. Labys (2001), “The Distribution of Realized Exchange Rate Volatility”, Journal of the American Statistical Association,Vol.96, pages 42-55.
     [3] Andersen, T. G., T. Bollerslev, F. X. Diebold and P. Labys (2003), ”Modeling and Forecasting Realized Volatility”, Econometrica, Vol. 71, pages 579-625.
     [4] Andersen, T. G., T. Bollerslev, F. X. Diebold (2005), “Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility”, Review of Economics and Statistics, Vol. 89, pages 701-720.
     [5] Avramov, D., T. Chordia and A. Goyal (2006), ”The Impact of Trades on Daily Volatility”, Review of Financial Studies, Vol. 19, pages 1241-1277.
     [6] Ben Bernanke (2004), “Irreversible Decisions and Record-Setting News Principles”, Journal of American Economic Review, Vol. 94, pages 557-568.
     [7] Black, F. (1976), “Studies of Stock Price Volatility Changes”, Proceedings of the 1976 Meetings of the Business and Economics and Statistics Section, American Statistical Association, pages 177-181.
     [8] Bollerslev, T. (1986), “Generalized Autoregressive Conditional Heteroskedasticity”, Journal of Econometrics, Vol. 31, pages 307-327.
     [9] Bollerslev, T. and R. F. Engle (1986), “Modeling the Persistence of Conditional Variances”, Econometric Reviews, Vol. 5, pages 1-50.
     [10] Bollerslev, T., R. F. Engle and J. M. Wooldridge (1988), “A Capital Asset Pricing Model with Time-Varying Covariances”, Econometrica, Vol. 96, pages 116-131.
     [11] Bollerslev, T., R. Y. Chou and K. F. Kroner (1992), “ARCH Modelling in Finance: A Review of the Theory and Empirical Evidence”, Journal of Econometrics, Vol. 52, pages 5-59.
     [12] Bollerslev, T., R. F. Engle and Nelson (1994), “ARCH Models,” in Engle, R. F. and D. McFadden, editors, Handbook of Econometrics, Vol. 4, Chapter 49, Elsevier Science B.V., Amsterdam, the Netherlands.
     [13] Byers, J. D. and D. A. Peel (1995), ”Evidence on Volatility Spillovers in the Interwar Floating Exchange Rate Period Based on High/Low Prices”, Applied Economics Letters 2, pages 394-396.
     [14] Campbell, J. and L. Hentschel (1992), “No News is good news: An Asymmetric Model of Changing Volatility in Stock Returns”, Journal of Financial Economics, Vol. 31, pages 281-318.
     [15] Carpenter, A. and J. Wang (2006), ”Herding and the Information Content of Trades in the Australian Dollar Market”, Pacific-Basin Finance Journal, Vol. 15, pages 173-194.
     [16] Christie, A. (1982),”The Stochastic Behavior of Common Stock Variances: Value, Leverage and Interest Rate Effects”, Journal of Financial Economics, Vol. 10, pages 407-432.
     [17] Connolly, R. and Stivers, C. (1999), “Conditional Return Autocorrelation and Price Formation: Evidence from Six Major Equity Markets”, Working Paper, University of Georgia and the University of North Carolina at Chapel Hill.
     [18] Dickey, D. A. and W. A. Fuller (1979), ”Distribution of the Estimators for Autoregressive Time Series With a Unit Root”, Journal of the American Statistical Association, Vol. 74, pages 427-431.
     [19] Ederington, L. H. and W. Guan (2005), “Forecasting Volatility”, Journal of Futures Markets, Vol. 25, pages 465-490.
     [20] Edgar E. Peters (1994), “Fractal Market Analysis: Applying Chaos Theory to Investment and Economics”, John Wiley and Sons New York.
     [21] Engle, R. F. (1982), ”Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation”, Econometrica, Vol. 50, pages 987-1007.
     [22] Engle, R. F. and V. K. Ng (1993), “Measuring and Testing the Impact of News on Volatility”, Journal of Finance, Vol. 48, pages 1749-1778.
     [23] Fama, E. F. (1965), ”The Behavior of Stock Market Prices”, Journal of Business, Vol. 38, pages34-105.
     [24] Fulvio Corsi (2004), “A Simple Long Memory Model of Realized Volatility”, University of Lugano and Swiss Finance Institute.
     [25] Gencay, R., M. Dacorogna, R. Olsen and O. Pictet (2003), “Foreign Exchange Trading Models and Market Behavior”, Journal of Economic Dynamics and Control, Vol. 27, pages 909-935.
     [26] Glosten, L., R. Jagannathan, and D. Runkle (1993), “”On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks”, Journal of Finance, Vol. 48, pages 1779-1801.
     [27] Granger, C. W. J. and P. Newbold (1974), “Spurious Regressions in Econometrics”, Journal of Econometrics, Vol. 4 ,pages 111-120.
     [28] Guillaume, D. M., M. M. Dacorogna, R. D. Davé, U. A. Müller, R. B. Olsen, and O. V. Pictet (1997), “From the Bird`s Eye to the Microscope: A Survey of New Stylized Facts of the Intra-daily Foreign Exchange Markets”, Finance and Stochastics, Vol. 1, pages 95-129.
     [29] Hafner, C. M. (1998), “Estimating High-frequency Foreign Exchange Rate Volatility with Nonparametric ARCH Models”, Journal of Statistical Planning and Inference, Vol. 68, pages 247-269.
     [30] Hogan, Jr. K. C. and M. T. Melvin (1994), “Sources of Meteor Showers and Heat Waves in the Foreign Exchange Market”, Journal of International Economics, Vol. 37, pages 239-247.
     [31] Hu, M. Y., C. X. Jiang and C. Tsoukalas (1997), “The European Exchange Rates Before and After the Establishment of the European Monetary System”, Journal of International Financial Markets, Institutions and Money, Vol. 7, pages 235-253.
     [32] Laopodis, N. T. (1997), “U.S. Dollar Asymmetry and Exchange Rate Volatility”, Journal of Applied Business Research, Vol. 13, pages 1-8.
     [33] Lobo, B. J. and D. Tufte (1998), “Exchange Rate Volatility: Does Politics Matter?”, Journal of Macroeconomics, Vol. 20, pages 351-365.
     [34] Mandelbrot, B. (1963), ”The Variation of Certain Speculative Prices”, Journal of Business, Vol. 36, pages 394-419.
     [35] McKenzie, M. D. (2002), “The Economics of Exchange Rate Volatility Asymmetry”, International Journal of Finance and Economics, Vol.7, pages 247-260.
     [36] Michael McAleer and Marcelo C. Medeiros (2008), “A multiple regime smooth transition heterogeneous autoregressive model for long memory and asymmetries”, Journal of Econometrics, Volume 147, Issue 1, November 2008, pages 104-119.
     [37] Michel M. Dacorogna, Ulrich A. Müller, Olivier V. Pictet, Richard B. Olsen (1997), “Modelling Short-Term Volatility with GARCH and HARCH Models”, Published in “Nonlinear Modelling of High Frequency Financial Time Series”, by Christian Dunis, Bin Zhou, John Wiley and Sons New York.
     [38] Müller, U. A., M. M. Dacorogna, R. D. Davé, O. V. Pictet, R. B. Olsen, and J. R. Ward (1993), “Fractals and Intrinsic Time - A Challenge to Econometricians,” Presented in an opening lecture at the XXXIXth International Conference of the Applied Econometrics Association (AEA), Real Time Econometrics - Submonthly Time Series, 14-15th Oct. 1993, in Luxembourg, and at the 4th International PASE Workshop, 22-26th Nov 1993, in Ascona (Switzerland).
     [39] Müller, U. A., M. M. Dacorogna, R. D. Davé, O. V. Pictet and J. E. Weizsäcker (1997), “Volatilities of Different Time Resolutions – Analyzing the Dynamics of Market Components,” Journal of Empirical Finance Vol. 4, pages 213-239.
     [40] Nelson, D. B. (1991), ”Conditional Heteroskedasticity in Asset Returns: A New Approach”, Econometrica, Vol. 59, pages 347-370.
     [41] Said, S. E. and D. A. Dickey (1984), “Testing for Unit Roots in Autoregressive-moving Average Models of Unknown Order”, Biometrika, Vol. 71, pages 599-607.
     [42] Schwert, G. W. (1989), “Why Does Stock Market Volatility Change Over Time?”, Journal of Finance, Vol.44, pages 1115-1153.
     [43] Sentana, E. and S. Wadhwani (1992), “Feedback Traders and Stock Return Autocorrelations: Evidence from A Century of Daily Data”, Economic Journal,Vol.102, pages 415-425.
     [44] Torben G. Andersen, Tim Bollerslev, Francis X. Diebold and Paul Labys (2000), “Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian”, Multinational Finance Journal, Vol. 4, pages 159-179.
     [45] Tse, Y. K. and K. C. Tsui (1997), “Conditional Volatility in Foreign Exchange Rates: Evidence from the Malaysian Ringgit and Singapore Dollar”, Pacific-Basin Finance Journal, Vol. 5, pages 345-356.
     [46] Wang Jianxin and Yang Minxian (2006), “Asymmetric Volatility in the Foreign Exchange Markets”.
     
     中文部分
     [1] 杜化宇，2006 [民95]，「資產波動對市場訊息反應不對稱之探討：NIC曲線之應用與外幣選擇權市場的證據」，國立政治大學財務金融學系，行政院國家科學委員會專題研究計畫成果報告。
     [2] 李晏均，2005 [民94]，「外匯市場波動性不對稱均數返還現象之硏究」，國立台北大學企業管理硏究所碩士論文。
     [3] 林怡昭，2008 [民97]，「影響亞洲國家匯率變動因素之研究」，國立政治大學經營管理碩士學程碩士論文。
     [4] 林淑瑜，2009 [民98]，「不對稱條件共變異數矩陣對資產配置與風險控管的意涵」，國立中山大學財務管理研究所博士論文。
     [5] 陳盈之，2003 [民92]，「市場訊息變動對外匯波動之不對稱影響與其反轉特性：選擇權市場的證據」，國立政治大學財務管理研究所碩士論文。
     [6] 許碧純，2001 [民90]，「台灣地區貨幣需求再研究─金融性風險之實證分析」，國立中央大學產業經濟研究所碩士論文。
     [7] 楊踐為、胥愛琦、吳清豐，2005 [民94]，「亞洲金融危機前後匯率波動不對稱現象之比較與政策意涵」，台灣管理學刊第5卷第2期，頁187-208。
     [8] 謝孟錡，2005 [民94]，「實質匯率波動之因素─區域性之比較分析」，國立中山大學中山學術研究所碩士論文。
     [9] 闕河士、楊德源，2005 [民94]，「股價指數期貨到期日效應之實證：以台灣股票市場為例」，Journal of Financial Studies Vol.13 No.2 August 2005，頁71-96。
描述 碩士
國立政治大學
國際經營與貿易學系
96351029
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0096351029
資料類型 thesis
dc.contributor.advisor 饒秀華zh_TW
dc.contributor.author (作者) 廖怡婷zh_TW
dc.creator (作者) 廖怡婷zh_TW
dc.date (日期) 2009en_US
dc.date.accessioned 9-五月-2016 14:53:16 (UTC+8)-
dc.date.available 9-五月-2016 14:53:16 (UTC+8)-
dc.date.issued (上傳時間) 9-五月-2016 14:53:16 (UTC+8)-
dc.identifier (其他 識別碼) G0096351029en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/95062-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 國際經營與貿易學系zh_TW
dc.description (描述) 96351029zh_TW
dc.description.abstract (摘要) 近年來，金融資產報酬波動的推估一直是重要的研究課題。然而，過去的波動不對稱研究均集中在股票市場，探討外匯市場波動不對稱性的實證研究並不多，但若忽略其不對稱效果將影響未來波動預測的正確性。因此，本研究利用近十六年來美元及日圓兌台幣匯率日資料，以傳統的波動不對稱性指數型GARCH模型(EGARCH Model)、門檻型GARCH模型(TGARCH, GJR GARCH Model)，亦延用異質自我相關迴歸模型(HAR-RV Model)及修正型異質自我相關迴歸模型(Modified HAR-RV Model)分別探討美元及日圓兌台幣匯率波動是否存在不對稱現象及其不對稱程度，並加以分析。實證研究中，上述四種模型均顯示美元及日圓兌台幣匯率波動的確具有不對稱效果；美元兌台幣匯率波動，與股票市場一致，報酬率與波動度間呈負向關係，當台幣相對美元升值時，波動度較高；而日圓兌台幣匯率波動，與美元匯率變動方向相反，報酬率與波動度間呈正向關係，當台幣相對日圓貶值時，波動度較高。此外，以異質自我相關迴歸模型實證分析中，日波動落後項的影響力明顯大於週、月、季波動落後項，與Muller, et al. (1997)、Corsi (2004)及Andersen, et al. (2005)實證研究結果類似。zh_TW
dc.description.tableofcontents 第一章 緒論 1
     1.1研究背景與動機 1
     1.2研究目的 1
     1.3論文架構 2
     第二章 文獻探討 4
     2.1利用時間序列方法實證研究波動度之相關文獻 4
     2.1.1波動度特性之相關文獻 4
     2.1.2股票市場波動不對稱效果之相關文獻 5
     2.1.3不對稱性GARCH模型之相關文獻 6
     2.1.4外匯市場波動不對稱效果之相關文獻 7
     2.2異質市場假說(Heterogeneous Market Hypothesis) 10
     2.2.1異質市場假說及其經濟意涵 10
     2.2.2異質市場假說之應用 11
     第三章 研究方法 13
     3.1異質自我相關迴歸模型(HAR-RV Model) 13
     3.2修正型異質自我相關迴歸模型(Modified HAR-RV Model) 14
     第四章 實證分析 16
     4.1資料說明與處理 16
     4.2資料初步分析 16
     4.2.1資料散佈圖 16
     4.2.2單根檢定及其結果 20
     4.2.3資料初步分析結果 22
     4.2.4 GARCH(1,1)模型 23
     4.3波動不對稱性檢定 26
     4.3.1 EGARCH(1,1)模型 26
     4.3.2 TGARCH(1,1)模型 29
     4.3.3異質自我相關迴歸模型(HAR-RV模型) 32
     4.3.4修正型異質自我相關迴歸模型(Modified HAR-RV模型) 36
     第五章 結論與建議 42
     5.1結論 42
     5.2後續研究建議 43
     參考文獻 44
     圖目錄
     圖4-1：美元兌台幣匯率日報酬率 17
     圖4-2：美元兌台幣匯率日報酬率平方項 17
     圖4-3：日圓兌台幣匯率日報酬率 18
     圖4-4：日圓兌台幣匯率日報酬率平方項 18
     圖4-5：美元兌台幣匯率日報酬率ACF圖 19
     圖4-6：美元兌台幣匯率日報酬率平方項PACF圖 19
     圖4-7：日圓兌台幣匯率日報酬率ACF圖 20
     圖4-8：日圓兌台幣匯率日報酬率平方項PACF圖 20
     
     表目錄
     表4-1：美元及日圓兌台幣匯率日報酬率單根檢定結果 22
     表4-2：美元及日圓兌台幣匯率日報酬率敘述統計表 23
     表4-3：美元兌台幣匯率日報酬率之AR(5)-GARCH(1,1)模型檢定結果 24
     表4-4：日圓兌台幣匯率日報酬率之GARCH(1,1)模型檢定結果 25
     表4-5：美元及日圓匯率之GARCH(1,1)模型─標準化殘差統計檢定量 25
     表4-6：美元兌台幣匯率日報酬率之AR(5)-EGARCH(1,1)模型檢定結果 27
     表4-7：日圓兌台幣匯率日報酬率之EGARCH(1,1)模型檢定結果 28
     表4-8：美元及日圓匯率之EGARCH(1,1)模型─標準化殘差統計檢定量 29
     表4-9：美元兌台幣匯率日報酬率之AR(5)-TGARCH(1,1)模型檢定結果 30
     表4-10：日圓兌台幣匯率日報酬率之TGARCH(1,1)模型檢定結果 31
     表4-11：美元及日圓匯率之TGARCH(1,1)模型─標準化殘差統計檢定量 32
     表4-12美元兌台幣匯率日波動度之HAR-RV模型檢定結果 33
     表4-13：日圓兌台幣匯率日波動度之HAR-RV模型檢定結果 34
     表4-14：美元及日圓匯率之HAR-RV模型─標準化殘差統計檢定量 35
     表4-15：美元兌台幣匯率日波動度之修正型HAR-RV模型檢定結果 37
     表4-16：日圓兌台幣匯率日波動度之修正型HAR-RV模型檢定結果 38
     表4-17：美元及日圓匯率之修正型HAR-RV模型─標準化殘差統計檢定量 39
     表4-18：所應用波動模型的優點與缺失之綜合整理 40
     表4-19：四種波動不對稱模型的實證結果之綜合整理 41		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0096351029en_US
dc.subject (關鍵詞) 匯率波動不對稱效果zh_TW
dc.subject (關鍵詞) 指數型GARCH模型(EGARCH)zh_TW
dc.subject (關鍵詞) 門檻型GARCH模型(TGARCH, GJR GARCH)zh_TW
dc.subject (關鍵詞) 異質自我相關迴歸模型(HAR-RV)zh_TW
dc.subject (關鍵詞) 異質市場假說zh_TW
dc.title (題名) 探討外匯市場匯率波動不對稱性─以美元及日圓兌台幣為例zh_TW
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 英文部份
     [1] Adler, M. and R. Qi (2003), ”Mexico’s Integration into the North American Capital Market”, Emerging Markets Review, Vol.4, pages 91-120.
     [2] Andersen, T. G., T. Bollerslev, F. X. Diebold and P. Labys (2001), “The Distribution of Realized Exchange Rate Volatility”, Journal of the American Statistical Association,Vol.96, pages 42-55.
     [3] Andersen, T. G., T. Bollerslev, F. X. Diebold and P. Labys (2003), ”Modeling and Forecasting Realized Volatility”, Econometrica, Vol. 71, pages 579-625.
     [4] Andersen, T. G., T. Bollerslev, F. X. Diebold (2005), “Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility”, Review of Economics and Statistics, Vol. 89, pages 701-720.
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     中文部分
     [1] 杜化宇，2006 [民95]，「資產波動對市場訊息反應不對稱之探討：NIC曲線之應用與外幣選擇權市場的證據」，國立政治大學財務金融學系，行政院國家科學委員會專題研究計畫成果報告。
     [2] 李晏均，2005 [民94]，「外匯市場波動性不對稱均數返還現象之硏究」，國立台北大學企業管理硏究所碩士論文。
     [3] 林怡昭，2008 [民97]，「影響亞洲國家匯率變動因素之研究」，國立政治大學經營管理碩士學程碩士論文。
     [4] 林淑瑜，2009 [民98]，「不對稱條件共變異數矩陣對資產配置與風險控管的意涵」，國立中山大學財務管理研究所博士論文。
     [5] 陳盈之，2003 [民92]，「市場訊息變動對外匯波動之不對稱影響與其反轉特性：選擇權市場的證據」，國立政治大學財務管理研究所碩士論文。
     [6] 許碧純，2001 [民90]，「台灣地區貨幣需求再研究─金融性風險之實證分析」，國立中央大學產業經濟研究所碩士論文。
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     [8] 謝孟錡，2005 [民94]，「實質匯率波動之因素─區域性之比較分析」，國立中山大學中山學術研究所碩士論文。
     [9] 闕河士、楊德源，2005 [民94]，「股價指數期貨到期日效應之實證：以台灣股票市場為例」，Journal of Financial Studies Vol.13 No.2 August 2005，頁71-96。		zh_TW