專業人員應該在數據之外提供更多合理且具關鍵性的見解,這些知識和經驗法則對我們計量中的檢定式應該能有所幫助,
但是古典統計分析只能依據歷史資料來判斷問題,
而這種方式雖然較為客觀,但往往忽略合理的額外訊息,正因如此,本文以貝氏分析能納入主觀意志的特性,
藉以加入經驗法則研究外匯市場上的單根檢定問題;此外,資料分配的不同也可能直接影響我們一般所用的古典檢定式,如
Dickey-Fuller檢定和Phillips-Perron檢定等,也因此本文深入探索這個問題,不以一般常態分配干擾項假設為合理,
因為一些研究股票或投資標的等時間序列資料發現它們較可能有厚尾的分配,
因此在研究貝氏單根檢定問題時擬將以更一般化形式來分析,本文根據Schotman 和 Van Dijk (1991) 的模型,
並且假設干擾項為獨立的student-t分配,重新推導其單根檢定式,然後將其應用於外匯市場分析上。

There should be more interpretations which are derived from data, presented by those professional analysts.
The empirical rules and knowledge do help as making statistical inference in Econometrics.
The approaches from classical statistical analysis make judges simply resulting from historical data.
To be frank, the advantage of this analysis is the objectivity, but there is a fatal drawback. That is, it does not pay attention to some logically extra information.
This paper is born for the applications of Bayesian, which has the essential characteristic of accepting subjective outlook, applying empirical rules to study unit root test on exchange rate market.
Furthermore, the various distributions of data may have direct effect on the classical statistical inference we use, such as Dickey-Fuller and Phillips-Perron test. To take those defects into consideration, this paper tends not to take the assumption of disturbances in normal distribution as granted.
For instance, it is quite common for us to confront the heavy-tailed distribution when studying some data of time series related to stocks and targets of investment. Hence, we will apply more generalized model to do research on Bayesian unit root test.
Use the model of Schotman and Van Dijk (1991) and assuming disturbance shaped as independent student-t distribution to revise the unit root test, next, applying to exchange rate market. This is the motif of this paper.

1 緒論 1
1.1 研究動機與目的 .....................................1
1.2 論文結構............................................2
2 理論與文獻回顧 3
2.1 文獻回顧............................................3
2.2 貝氏單根檢定........................................5
2.3 Geweke的計量方法....................................8
2.4 數值積分方法.......................................13
3 計量方法與模型介紹 15
3.1 資料分配的檢定.....................................16
3.2 干擾項為t分配之單根檢定............................17
3.3 個參數的條件事後分配...............................19
3.4 型一誤差與檢定力...................................21
4 結果與分析 23
4.1 資料來源與原因.....................................23
4.2 單根檢定分析.......................................25
4.3 敏感度分析.........................................25
5 結論 32
6 參考文獻 33

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