臺灣博碩士論文加值系統

多數狀態轉換模型可提供相較於線性模型較佳的配適度，但樣本外預測能力
卻難以推翻Meese and Rogoff (1983) 指出名目匯率不可預測的結論，亦即名目匯
率呈現隨機漫步 (Random Walk) 走勢，且投資者無法在外匯市場賺取超額報酬。
文獻上衡量匯率模型的預測能力，大多建立在預測誤差等衡量指標，但較低的預
測誤差並不保證具有較高的收益性或經濟價值。因此，本研究認為狀態轉換模型
所提供的經濟價值是值得探討的議題。
本研究主要探討英鎊與日元等兌美元之報酬在1990 年至2005 年期間，應用
Teräsvirta and Anderson (1992) 與Granger and Teräsvirta (1993) 提出的STAR 族模
型線性檢定法，分別檢定貨幣基要 (monetary fundamentals; MF) 模型與時間序列
AR 模型是否存在STR 與STAR 的調整行為，並評估其預測誤差與經濟價值。實
證結果顯示，英鎊與日元等報酬率皆存在ST(A)R 模型的型式，分別為logistic 函
數與exponential 函數，且能提升線性模型的樣本內配適度，其中LSTAR 模型與
ESTAR 模型分別為90 年代期間英鎊與日元的最佳估計模型。樣本外預測結果則
顯示，ST(A)R 模型的預測誤差雖然無法完全優於Random Walk 模型或線性模型，
卻可提供較佳的擇時能力；對於Mean-Variance 投資者而言，ST(A)R 模型亦提供
相較於線性模型較佳的資產配置能力，且優於Random Walk 模型。其中STAR 模
型具有最佳的擇時能力與資產配置能力，並提供高報酬低風險的效率投資組合，
此結論隱含考量報酬率估計參數存在平滑式的狀態轉換，對於經濟價值具有提升
且較重要的影響程度。

Most regime switching models give good in-sample fits to exchange rate data but are usually outperformed by random walks model when out-of-sample forecasts. Prior research on the ability of exchange rate models to forecast exchange rates relies on statistical measures of forecast accuracy, but lower forecast error does not necessarily imply higher profitability or economic value.
The aim of this study is to test for and model nonlinearities in the USD/GBP and USD/JPY exchange rate returns. We apply the STAR family models (STAR; STR) used by Ter�鱷virta and Anderson (1992); Granger and Ter�鱷virta (1993), to test nonlinearities of monetary fundamentals (MF) model and AR model, and measure the economic value of predicting USD/GBP and USD/JPY exchange rate returns. Using monthly data from 1990 to 2005. Our tests rejects the linearity hypothesis for the USD/GBP and USD/JPY exchange rate returns during the 1990s, are classified as logistic ST(A)R and as exponential ST(A)R respectively. ST(A)R models all provide better good in-sample fits than linear models. We also compare forecast error, market timing ability, and asset allocation performance of out-of-sample forecasts. ST(A)R models can not beat random walk model and linear models of USD/JPY exchange rate returns MAE or RMSE forecasting, but they can provide more market timing ability and Mean-Variance asset allocation performance than linear models of USD/GBP and USD/JPY exchange rate returns forecasts. Furthermore, STAR models are best market timing and asset allocation models, and also provided most efficiency portfolio. These findings confirm the economic value importance of accounting for the presence of regimes in exchange rate returns.

摘要.................................................................................................................................I
Abstract ...........................................................................................................................II
誌謝辭........................................................................................................................... III
目錄...............................................................................................................................IV
表目錄...........................................................................................................................VI
圖目錄..........................................................................................................................VII
第一章 緒論.................................................................................................................1
第一節 研究背景與動機..........................................................................................1
第二節 研究目的與方法..........................................................................................3
第二章 文獻探討..........................................................................................................6
第一節 線性模型......................................................................................................6
第二節 狀態轉換模型..............................................................................................7
第三節 經濟價值.................................................................................................... 10
第三章 實證模型與研究方法.................................................................................... 13
第一節 線性匯率模型............................................................................................ 13
第二節 平滑轉換匯率模型.................................................................................... 16
第三節 外匯資產配置模型.................................................................................... 19
第四節 共整合檢定................................................................................................ 21
第五節 線性檢定與轉換函數選擇....................................................................... 21
第六節 樣本外預測能力之衡量............................................................................ 22
第四章 實證結果....................................................................................................... 25
第一節 資料說明.................................................................................................... 25
第二節 共整合檢定................................................................................................ 25
第三節 建立線性匯率模型.................................................................................... 29
第四節 線性檢定與轉換函數選擇....................................................................... 30
第五節 建立外匯資產配置模型............................................................................ 34
一、報酬率參數為固定之資產配置模型........................................................... 35
二、報酬率參數為平滑轉換之資產配置模型................................................... 37
三、報酬率參數為平滑轉換之調整過程........................................................... 40
第六節 樣本外預測與經濟價值............................................................................ 45
一、預測誤差績效............................................................................................... 46
二、擇時能力....................................................................................................... 47
三、資產配置績效............................................................................................... 51
第五章 結論與建議.................................................................................................. 53
參考文獻....................................................................................................................... 56
附錄............................................................................................................................... 60


表目錄
表 1 Engel and Granger兩階段共整合檢定............................................................ 26
表 2 Johansen共整合與係數檢定........................................................................... 27
表 3 MF模型估計結果............................................................................................ 29
表 4 AR模型估計結果............................................................................................ 30
表 5 線性檢定.......................................................................................................... 31
表 6 轉換函數型式之檢定...................................................................................... 32
表 7 STR-MF模型估計結果.................................................................................... 33
表 8 STAR模型估計結果........................................................................................ 34
表 9 MF/GARCH資產配置模型估計結果............................................................. 35
表 10 AR/GARCH資產配置模型估計結果............................................................. 36
表 11 STR-MF/GARCH資產配置模型估計結果.................................................... 38
表 12 STAR資產配置模型估計結果........................................................................ 39
表 13 樣本外預測誤差與擇時能力.......................................................................... 47
表 14 資產配置經濟價值.......................................................................................... 52
附表 1 各國變數之敍述統計量................................................................................ 64
附表 2 影響國際金融之重大事件表........................................................................ 65
附表 3 RW模型估計結果......................................................................................... 66
附表 4 RW資產配置模型估計結果......................................................................... 66
附表 5 擇時能力之平均報酬與風險........................................................................ 67
附表 6 資產配置之平均報酬與風險........................................................................ 67


圖目錄
圖 1 研究流程圖..........................................................................................................5
圖 2 名目匯率之報酬率與偏離貨幣基要走勢圖................................................... 28
圖 3 LSTR-MF/GARCH模型之轉換函數對應轉換變數....................................... 41
圖 4 ESTR-MF/GARCH模型之轉換函數對應轉換變數....................................... 43
圖 5 LSTAR模型之轉換函數對應轉換變數........................................................... 44
圖 6 ESTAR模型之轉換函數對應轉換變數........................................................... 45
圖 7 GBP之樣本外預測與方向準確率.................................................................... 49
圖 8 JPY之樣本外預測與方向準確率..................................................................... 50
附圖 1 各國變數走勢圖.......................................................................................... 68
附圖 2 樣本內移動式Chow檢定............................................................................ 69
附圖 3 轉換變數走勢圖.......................................................................................... 70
附圖 4 GBP貨幣基要資產配置模型之樣本內配適圖.......................................... 71
附圖 5 GBP時間序列資產配置模型之樣本內配適圖.......................................... 72
附圖 6 JPY貨幣基要資產配置模型之樣本內配適圖........................................... 73
附圖 7 JPY時間序列資產配置模型之樣本內配適圖........................................... 74
附圖 8 擇時能力之期末累積財富.......................................................................... 75
附圖 9 資產配置之最適JPY權重(A = 5) ................................................................ 76
附圖 10 資產配置之最適JPY權重(A = 10).............................................................. 77
附圖 11 資產配置之最適JPY權重(A = 15).............................................................. 78
附圖 12 資產配置之最適JPY權重(A = 20).............................................................. 79
附圖 13 資產配置之期末累積財富.......................................................................... 80

1.Abhyankar, A., Sarno, L., Valente, G., 2005. Exchange rates and fundamentals: evidence on the economic value of predictability. Journal of International Economics 66, 325-348.
2.Allen, H., Taylor, M.P., 1990. Charts, noise and fundamentals in the foreign exchange market.Economic Journal 100, 49-59.
3.Ang, A., Bekaert, G., 2002. International asset allocation with regime shifts. The Review of Financial Studies 15, 1137-1187.
4.Aslanidis, N., 2002. Smooth transition regression models in UK stock returns. Royal Economic Society Conference.
5.Barberis, N., 2000. Investing for the long run when returns are predictable. Journal of Finance 55, 225-264.
6.Berkowitz, J., Giorgianni, L., 2001. Long-horizon exchange rate predictability? Review of Economics and Statistics 83, 81-91.
7.Black, F., Litterman, R., 1992. Global portfolio optimization. Financial Analyst Journal 48, 28-43.
8.Bollerslev, T., 1990. Modeling the coherence in short-run nominal exchange rates: A multivariate generalized arch models. The Review of Economics and Statistics 72, 498-505
9.Brooks, C., 1996. Testing for nonlinearity in daily sterling exchange rates. Applied Financial Economics 6, 307-317.
10.Brooks, C., 1997. Linear and Nonlinear (non-)forecastability of high frequency exchange rate. Journal of Forecasting 16, 125-145.
11.Chen, S.L., Wu, J.L., 2000. A re-examination of purchasing power parity in Japan and Taiwan. Journal of Macroeconomics 22, 271-284.
12.Chinn, M.D., Meese, R.A., 1995. Banking on currency forecasts: how predictable is a change in money? Journal of International Economics 38, 161-178.
13.Chow, G.C., 1960. Testing for equality between sets of coefficients in two linear regression relationship over time. Econometrica 29, 591-605.
14.Clark, T.E., McCracken, M.W., 2001. Test of equal forecast accuracy and encompassing for nested models. Journal of Econometrics 105, 85-110.
15.Clarke, R.G., Silva, H., 1998. State dependent asset allocation. The Journal of Portfolio Management 24, 57-64.
16.Dacco, R., Satchell, S., 1999. Why do regime switching models forecast so badly? Journal of Forecasting 18, 1-16.
17.Diebold, F.X., Mariano, R., 1995. Comparing predictive accuracy. Journal of Business and Economic Statistics 13, 253-262.
18.Eitrheim, O., Ter�鱷virta, T., 1996. Testing the adequacy of smooth transition autoregressive models. Journal of Econometrics 74, 59-75.
19.Enders, W., 2004. Applied econometric time series. New York: John Wiley and Sons. Inc.
20.Engel, R.E., Granger, C.W.J., 1987. Cointegration and error-correction: Representation, estimation, and testing. Econometrica 55, 251-276.
21.Engel, C., 1994. Can the markov switching model forecast exchange rates? Journal of International Economics 36, 151-165.
22.Engel , C., 2000. Long-run PPP may not hold after all. Journal of International Economics 3, 123-192.
23.Engel, C., Hamilton, J.D., 1990. Long swings in the dollar: Are they in the data and do markets know it? The American Economic Review 80, 689-713.
24.Fern�鴨dez-Rodr�櫂uez, S., Sosvilla-Rivero., Andrada-F�翼ix., 2003. Technical analysis in foreign exchange markets: evidence from the EMS. Applied Financial Economics 13, 13-122.
25.Frankel, J.A., Froot, K.A., 1990. Chartists, fundamentalists and the demand for dollars. In:Courakis, A.S., Taylor, M.P. (Eds.), Private Behaviour and Government Policies in Interdependent Economies. Oxford University Press, Oxford, 79-126.
26.French, K.R., Poterba, J.M., 1991. Investor diversification and international equity markets. American Economic Review 81, 222-226.
27.Frenkel, J.A., 1981. Flexible exchange rates, prices, and the role of news: Lessons from the 1970’s. Journal of Political Economy 89, 665-705.
28.Granger, C.W.J., Newbold, P., 1974. Spurious regressions in econometrics. Journal of Econometrics 2, 111-120.
29.Granger, C.W.J., Ter�鱷virta, T., 1993. Modelling nonlinear economic relationships. Oxford University Press, Oxford.
30.Grauer, R.R., 1986. Normality, solverncy, and portfolio choice. The Journal of Financial and Quantitative Analysis 21, 265-278.
31.Groen, J.J.J., 2000. The monetary exchange rate model as a long-run phenomenon. Journal of International Economics 52, 299-319.
32.Guidolin, M., Timmermann, A., 2005. Strategic asset allocation and consumption decisions under multivariate regime switching. Working paper.
33.Hansen, B.E., 2001. The new econometrics of structural change: Dating breaks in U.S. labor productivity. Journal of Economic Perspectives 15, 117-128.
34.Johansen, S., Juselius, K., 1990. Maximum likelihood estimation and inference on cointegration with application to the demand for money. Bulletin of Economics and Statistics 52, 169-209.
35.Kandel, S., Stambaugh, R.F., 1996. On the predictability of stock returns: an asset-allocation perspective. Journal of Finance 51, 385-424.
36.Kilian, L., 1999. Exchange rates and monetary fundamentals: What do we learn from long-horizon regression? Journal of Econometrics 14, 491-510.
37.Kilian, L., Taylor, M.P., 2003. Why is it so difficult to beat the random walk forecast of exchange rates? Journal International Economics 60, 85-107.
38.Leitch, G.., Tanner, E., 1991. Economic forecast evaluation: profits versus the conventional error measures. The American Economic Review 81, 580-590.
39.Lin, C.F., Ter�鱷virta, T., 1994. Testing the constancy of regression parameters against continuous structural change. Journal of Econometrics 62, 211-228.
40.Mark, N.C., 1995. Exchange rates and fundamentals: evidence on long-horizon predictability. The American Economic Review 85, 201-218.
41.Mark, N.C., Sul, D., 2001. Nominal exchange rates and monetary fundamentals: evidence from a small Bretton Woods panel. Journal of International Economics 53, 29-52.
42.Markowitz, H.M., 1952. Portfolio selection. Journal of Finance 7, 77-91.
43.Marquering, W., Verbeek, M., 2003. The economic value of predicting stock index returns and volatility. (forthcoming Journal of Financial and Quantitative).
44.McMillian, D.G., 2001. Nonlinear predictability of stock market returns: evidence from nonparametric and threshold models. International Review of Economics and Finance 10, 353-368.
45.Meese, R., Rogoff, K., 1983. Empirical exchange rate models of the seventies: do they fit out of sample? Journal of International Economics 14, 3-24.
46.Michael, P., Nobay, A.R., Peel, D.A., 1997. Transactions costs and nonlinear adjustment in real exchange rates: an empirical investigation. The Journal of Political Economy 105, 862-879.
47.Mussa, M., 1979. Empirical regularities in the behavior of exchange rates and theories of the foreign exchange market, in: Karl Brunner and Allan H. Meltzer, eds., Policies for employment, prices and exchange rates, Carnegie-Rochester Coference 11 (North-Holland Amsterdam).
48.Neely, C.J., Sarno, L., 2002. How well do monetary fundamentals forecast exchange rates? Review-Federal Reserve Bank of St. Louis 84, 51-74.
49.Obstfeld, M., Rogoff, K., 2000. The six major puzzles in international macroeconomics: is there a common cause? In : Bernanke, B., Rogoff, K.(Eds.), NBER Macroeconomics Annual 2000. MIT Press, Cambridge, Mass, 339-390.
50.Pesaran, M.H., Timmermann, A., 1992. A simple non-parametric test of predictive performance. Journal of Business and Economic Statistics 10, 467-465.
51.Pesaran, M.H., Timmermann, A., 1995. Predictability of stock returns: robustness and economic significance. Journal of Finance 50, 1201-1228.
52.Pesaran, M.H., Timmermann, A., 2000. A recursive modeling approach to predicting UK stock returns. Economic Journal 110, 159-191.
53.�鉍al, N., Osborn, D.R., 2000. Business cycles non-linearities in UK consumption and production. Journal of Applied Econometrics 15, 27-43.
54.Qi, M., 1999. Nonlinear predictability of stock returns using financial and economic variables. Journal of Business and Economic Staatistics 17, 419-429.
55.Rapach, D.E., Wohar, M.E., 2002. Testing the monetary model of exchange rate determination: new evidence from a century of data. Jounal of International Economics 58, 359-385.
56.Rogoff, K., 1996. The purchasing power parity puzzle. Journal of Economic Literature 34, 647-668.
57.Sarantis, N., 1999. Modeling non-linearities in real effective exchange rates. Journal of International Money and Finance 18, 27-45.
58.Sarno, L., 1998. Adjustment costs and nonlinear dynamics in the demand for money: Italy, 1861-1991. Internationaal Journal of Finance and Economics 4, 155-177.
59.Sarno, L., Taylor, M.P., Peel, D.A., 2003. Nonlinear equilibrium correction in U.S. real money balances, 1869-1997. Journal of Money, Credit, and Banking 35, 787-799.
60.Sharpe, W.F., 1966. Mutual fund performance. Journal of Business 39, 119-138.
61.Satchell, S., Timmermann, A., 1995. An assessment of the economic value of nonlinear foreign exchange rates forecasts’. Journal of Forecasting 14, 477-498.
62.Skalin, J., Ter�鱷virta, T., 1999. Another look at Swedish business cycles. Journal of Applied Econometrics 14, 359-378.
63.Taylor, M.P., Peel, D.A. 2000. Nonlinear adjustment, long-run equilibrium and exchange rate fundamentals. Journal of International Money and Finance 19, 33-53.
64.Taylor, M.P., Peel, D. A., Sarno, L., 2001. Nonlinear mean-reversion in real exchange rates: towards a solution to the purchasing power parity puzzles. International Economic Review 42, 1015-1042
65.Ter�鱷virta, T., 1994. Specification, estimation and evaluation of smooth transition autoregressive models. Journal of the American Statistical Association 89, 208-218.
66.Ter�鱷virta, T., Anderson., 1992. Characterizing nonlinearities in business cycles using smooth transition autoregressive models. Journal of Applied Econometrics 7, 119-136.
67.Ter�鱷virta, T., Eliasson, A.C., 2001. Non-linear error correction and the UK demand for broad money, 1878-1993. Journal of Applied Econometrics 16, 277-288.
68.Ter�鱷virta, T., Van Dijk, D., Medeiros, C.M., 2004. Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: a re-examination. Working paper.
69.West, K.D., Edison, H.J., Cho, D., 1993. A utility-based comparison of some models of exchange rate volatility. Journal of International Economics 35, 23-45.
70.Yang, Y. N., 2002. Structural changes in US-Japan exchange rates- an application of the smooth transition regression model. Chung Yuan Journal 30, 453-459.