風險貼水與外匯市場效率性

Risk Premium and Foreign Exchange Market Efficiency

方文碩(Wen-Shwo Fang) ； 張倉耀(Tsang-Yao Chang)

《管理評論》 21卷2期 (2002/07) Pp. 27-51

https://doi.org/10.6656/MR.2002.21.2.CHI.27

摘要

本文使用1995年1月至1999年12月的日資料，實證探討台灣外匯市場即期匯率與10天期遠期匯率的市場效率性。Johansen共整合過程發現即期與遠期買進匯率存在長期均衡關係、遠期預測誤差為白噪音過程及遠期匯率為未來即期匯率不偏估計，買進匯率滿足簡單市場效率，不存在外匯投機、獲取超額報酬的機會。賣出匯率遠期預測誤差存在隨時間變動的風險貼水（GARCH-M效果），Johansen共整合分析建議風險貼水、即期與遠期匯率三變數間存在唯一長期均衡關係，且風險貼水在共整合向量中為顯著的解釋變數，在風險趨避投資人要求風險貼水補償前提下，遠期匯率仍為未來即期匯率不偏估計，外匯市場不存在獲取額外利潤、未加利用的訊息，賣出匯率滿足風險貼水市場效率。另外，證據顯示亞洲金融危機衝擊台灣外匯市場，增加市場波動與遠期匯率預測誤差。

關鍵字

外匯市場效率 ； 風險貼水 ； 亞洲金融危機 ； GARCH-M模型 ； 共整合分析

並列摘要

This paper investigates Taiwan foreign exchange market efficiency, using daily data of 10-day forward and spot exchange rates quoted in terms of the US dollar which spanned from January 1995 to December 1999 with 157 observations. Johansen cointegration procedures imply that spot and forward exchange rates of buying rates are cointegrated, forward forecast errors are white noise, and forward rates are unbiased predictors of future spot rates. This suggests that buying rates fulfill the simple market efficiency, meaning that there is no opportunity of the excess return to forward speculation. There exists a time-varying risk premium (GARCH-M effect) in forward forecast errors of selling rates. Furthermore, Johansen cointegration suggests there is a unique long-run equilibrium relation among risk premia, spot and forward rates. And the risk premium is a significant, explanatory variable in the cointegration vector. Under the condition of compensation required by risk-averse investors, forward rates are unbiased predictors of future spot rates. In the market of selling rates there exists no unexploited information for extra profits, the market is efficient. Additionally, evidence shows that Taiwan foreign exchange market had been influenced by the Asian financial crisis, leading to higher market volatility and forward forecast error.

並列關鍵字

foreign exchange market efficiency ； risk premium ； Asian financial crisis ； GARCH-M model ； cointegration analysis

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