臺灣博碩士論文加值系統

摘要
為了研究市場投資者的意願和心理因素對外匯市場的影響，本文研究投機情緒指數、買賣訂單流量與匯率波動之關係，資料範圍自西元2003年1月1日至2006年12月31日的小時資料，以代表性的五大貨幣對(歐元/美元、英鎊/美元、美元/瑞朗、美元/加幣、美元/日幣)之匯率、訂單流量及投機情緒指數指標為研究變數，研究2003年與2006年四季之相關係數變化。
主要使用由2001年Engle提出之簡化條件共變異數矩陣估計的新多變量GARCH模型－動態條件條件相關模型（dynamic conditional correlation GARCH , DCC-GARCH)來描述大量隨時間而改變的條件共變異數矩陣，進而求出動態條件相關性。DCC模型可求出隨時間變化而不同的相關係數，允許條件平均數和條件變異數隨時間改變的可能性，可精確顯示時間序列資料的共移關係的可能改變之時點與性質。
歐元/美元2006年春季波動的持續性均為負相關，其餘皆為正值，在秋季出現較大數值，表示波動的持續性在秋季為正相關；英鎊/美元2006年在春季出現較高的正持續性，除了2003的冬季買賣訂單流量為負相關外，其餘均為正相關；美元/瑞朗全為正相關；美元/加幣2006年夏季波動的持續性均為負相關，投機情緒指數指標波動的持續性正相關較高值出現在春季；美元/日幣買賣訂單流量除了2006的春季為負相關外，其餘均為正，不論年份，較高的持續性出現在秋季，投機情緒指數指標波動的持續性均為正相關，且較高的持續性出現在春季。
歐元/美元在夏季有較高正相關的波動持續性，在2003年買賣訂單流量於夏季，投機情緒指數指標(價)於春季出現負相關之情形；英鎊/美元全為正相關的波動持續性；美元/瑞朗在2006年買賣訂單流量於冬季，投機情緒指數指標(價)於秋季出現負相關之情形，其餘皆為正相關；美元/加幣除2006年買賣訂單流量於春季出現負相關外，其餘皆為正相關；美元/日幣投機情緒指數指標(量)在2003年時於秋季出現負相關，2006年以春季出現負相關，其餘變數與年份均為正相關且於秋季有較高之持續性。
五大貨幣對的本期標準化誤差項之共變異受上期共變異的影響，在各貨幣對無論年份與變數的不同，數值均較小，多為0.05之下；表示受上期標準化誤差項的影響程度，在各貨幣對無論年份與變數的不同，數值均較大，多為0.5之上。上期標準化誤差項的影響程度除了數值較本期標準化誤差項之共變異受上期共變異的影響大之外，其顯著性較高之數值也較多。
單就買賣訂單流量或是投機情緒指數考慮對於匯率波動的影響，相關係數不高，僅就冬季時會出現持續性較強與相關係數較大的情形，若真要用以預測，唯有冬季有預測之空間，買賣訂單流量與投機情緒指數各有表現較佳之情況。

Abstract
It is important to find the high correlated exchange rate with other economy variables in forecasting. The Meese and Rogoff (1983a,b) use traditional exchange rate determination models to forecast exchange rate and they showed that the random walk model were better than others.
Evans and Lyons (2002a) wanted to “beating a random walk” in forecasting is too strong a criterion for accepting an exchange rate model. They provided a model which described order flow in determining exchange rates. Order flow is taken to be a variant of the more familiar concept of ‘net demand’ and measures the net of buyer-initiated orders and seller-initiated orders. Evans and Lyons provided evidence to show that order flow was a significant determinant of two major bilateral exchange rates at the daily frequency, obtaining coefficients of determination substantially were larger than the ones which usually obtained using standard macroeconomic models of nominal exchange rates. Compared with the above literature, we use SSI for our empirical study.
The Speculative Sentiment Index (SSI) is based on proprietary customer flow information and is designed to recognize price trend breaks and reversals in the four most popularly traded currency pairs. The absolute number of the ratio itself represents the amount by which longs exceed shorts or vice versa.
Both of foreign exchange rates on order flow and on Speculative Sentiment Index (SSI) are investigated for five major exchange rate pairs, EUR/USD, GBP/USD, USD/CAD, USD/CHF and USD/JPY, across sampling frequencies 1 hour during 2003 and 2006.In the paper we use the Dynamic Conditional Correlation (DCC) Model to check the relationship with order flow, SSI and exchange rate. Our results indicate order flow and SSI both has high correlation coefficient with exchange rate especially in “winter” period. The results are similar with five major exchange rate pairs.

目錄

第一章 前言 1
第二章 文獻回顧 6
第三章 研究方法 13
第四章 實證結果 24
第五章 結論 86
參考文獻 88

參考文獻
1.Allen,H. and Taylor, M.P.(1990)“Charts, Noise and Fundamentals in the London Foreign Exchange Market,”The Economic Journal, Vol.100,49-59.
2.Balassa, Bela(1964)“ The Purchasing Power Parity Doctrine: A Reappraisal,”Journal of Political Economy, Vol.72,584-896.
3.Bollerslev, T.(1986)“Generalized Autoregressive Conditional Heteroscedasticity,”Journal of Econometrics, Vol.31,307-327.
4.Bollerslev, T.,R.F. Engle, and J.M. Wooldridge(1988)“ A Capital Asset Pricing Model with Time-Varying Covariances,”Journal of Political Economy, Vol.96,116-131.
5.Chou, R. Y.(1988)“Volatility Persistence and Stock Valuations: Some Empirical Evidence Using GARCH,”Journal of Applied Econometrics, Vol.3,279-294.
6.Engle, R.F.(1982)“Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation,”Econometria, Vol.50,987-1007.
7.Evans, M.D.D., and Lyons R.K.(2002)“Order Flow and Exchange Rate Dynamics,” Journal of Political Economy, Vol.110,no.1.
8.Fama, E.(1965) “ The Behavior of Stock Market Prices,”The Journal of Business, Vol.38,34-105.
9.Engle,R. F., D.M. Lilien, and R.P. Robins (1987)“Estimating Time Varying Risk Premia in the Term Structure: The ARCH-M model,”Econometria, Vol.55,391-407.
10.Frankel, J.A. and Froot,K.A.(1990)“Chartists, Fundamentalists, and Trading in the Foreign Exchange Market,”The American Economic Review, Vol.80,181-185.
11.Hseich, David A.(1989)“ Testing for Nonlinear Dependence in Daily Foreign Exchange Rates,”The Journal of Business, Vol.62,339-368.
12.J’on Dan’ıelsson, Richard Payne and Jinhui Luo(2002)“Exchange Rate Determination and Inter–Market Order Flow Effects,” London School of Economics
13.Mandelbrot, B.(1963)“ The Variation of Certain Speculative Prices,”Journal of Business, Vol.36,394-419.
14.Mark, Nelson.C.(1995)“Exchange Rates and Fundamentals:Evidence on Long-Horizon Predictability,”The American Economic Review, Vol.85,201-218.
15.Martin D. D. Evans and Richard K. Lyons(2002) “Order Flow and Exchange Rate Dynamics,”Journal of Political Economy, Vol.110.
16.Meese,R. and Rogoff,K.(1983a)“Empirical Exchange Rate Models of Seventies: Do they Fit Our of Sample?” Journal of International Economics, Vol.14,3-24.
17.Morgan, I.G..(1976)“Stock prices and heteroscedasticity,”Journal of Business, Vol.49,496-508.