匯率因子與市場基要之預測表現

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姓名

劉曉齊(Hsiao-Chi Liu) 查詢紙本館藏

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經濟學系

論文名稱

匯率因子與市場基要之預測表現
(Market Fundamentals, Factor Model, and Exchange Rate Forecasting)

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摘要(中)

本研究利用因子模型結合傳統基本面模型(包含購買力評價模型、泰勒法則模型、貨幣模型以及未拋補利率評價模型), 利用樣本外預測之方式與拔靴法檢定, 發現基本面加入因子之模型能降低傳統基本面模型對匯率預測之RMSPE。相較於其他基本面加入因子之模型, 購買力評價結合因子模型之表現最佳。另外, 本研究檢視5 個範圍期間(h = 1, 4, 6, 8, 12), 並利用各種不同基本面加入因子模型, 在去除短期範圍期間(h = 1) 之下, 13個目標國家中, 加拿大、丹麥、歐盟、挪威、紐西蘭、韓國、新加坡以及英國, 皆曾出現過全數顯著之表現。最後, 若僅將範圍期間專注在中長期(h = 4, 6), 除了貨幣加入因子模型之外, 多數國家的基本面加入因子模型對匯率之預測表現優於隨機漫步模型。

摘要(英)

In this study, we combined factor models with traditional fundamental models (including purchasing power parity model, Taylor rule model, monetary model, uncovered interest parity model), using out of sample forecast and bootstrap test to find that RMSPE of exchange rate forecast for factors combined with fundamental models lower than traditional fundamental models. In particular, factors combined with purchasing power parity model outperform other factors combined with fundamental models. Moreover, this study examined five horizons (h = 1, 4, 6, 8, 12). Out of short horizon (h = 1), there are Canada, Denmark, Euro, Norway, New Zealand, South Korea, Singapore,and United Kingdom ever have significant forecast from our object countries. Finally, if we focused on middle horizon (h = 4, 6), out of factors combined with monetary model, there are more countries have evidence to support that forecast of exchange rate for factors combined with fundamental models outperform random walk model.

關鍵字(中)

★ 拔靴法
★ 樣本外預測
★ 因子模型
★ 匯率基要

關鍵字(英)

★ bootstrap
★ out of sample forecast
★ factor model
★ fundamental

論文目次

目錄
1 緒論1
2 文獻回顧4
2.1 匯率模型文獻4
2.2 因子模型文獻6
3 研究方法9
3.1 追蹤資料之迴歸模型 9
3.2 因子模型9
3.3 基本面模型設定11
3.4 樣本外預測14
3.5 模型檢定15
3.6 追蹤資料之拔靴法16
3.7 檢定方法18
4 實證分析19
4.1 資料介紹19
4.2 實證結果19
4.2.1 因子模型對匯率預測之表現20
4.2.2 市場基要加入因子對匯率預測之表現21
4.2.3 結合市場基要加入因子對匯率預測之表現24
4.2.4 加入因子與無因子對匯率預測之比較26
5 結論與未來研究方向28
5.1 結論28
5.2 未來研究方向29
參考文獻30
表目錄
1 決定資料生產過程落後期數之BIC 34
2 基本面變數對因子之配適度(R2) 34
3 一因子模型對匯率預測之表現 35
4 二因子模型對匯率預測之表現36
5 三因子模型對匯率預測之表現 37
6 購買力評價加入一因子模型對匯率預測之表現38
7 購買力評價加入二因子模型對匯率預測之表現 39
8 購買力評價加入三因子模型對匯率預測之表現 40
9 泰勒法則加入一因子模型對匯率預測之表現 41
10 泰勒法則加入二因子模型對匯率預測之表現42
11 泰勒法則加入三因子模型對匯率預測之表現 43
12 貨幣加入一因子模型對匯率預測之表現 44
13 貨幣加入二因子模型對匯率預測之表現 45
14 貨幣加入三因子模型對匯率預測之表現 46
15 未拋補利率評價加入一因子模型對匯率預測之表現47
16 未拋補利率評價加入二因子模型對匯率預測之表現48
17 未拋補利率評價加入三因子模型對匯率預測之表現49
18 結合購買力評價與泰勒法則加入一因子模型對匯率預測之表現50
19 結合購買力評價與泰勒法則加入二因子模型對匯率預測之表現51
20 結合購買力評價與泰勒法則加入三因子模型對匯率預測之表現52
21 結合全部基本面加入一因子模型對匯率預測之表現53
22 結合全部基本面加入二因子模型對匯率預測之表現54
23 結合全部基本面加入三因子模型對匯率預測之表現55
24 購買力評價加入二因子與無因子對匯率預測之比較 56
25 購買力評價加入三因子與無因子對匯率預測之比較57
26 泰勒法則加入二因子與無因子對匯率預測之比較58
27 泰勒法則加入三因子與無因子對匯率預測之比較59
28 貨幣加入二因子與無因子對匯率預測之比較60
29 貨幣加入三因子與無因子對匯率預測之比較61
30 未拋補利率評價加入二因子與無因子對匯率預測之比較62
31 未拋補利率評價加入三因子與無因子對匯率預測之比較63
32 結合購買力評價與泰勒法則加入二因子與無因子對匯率預測之比較64
33 結合購買力評價與泰勒法則加入三因子與無因子對匯率預測之比較65
34 結合全部基本面加入二因子與無因子對匯率預測之比較66
35 結合全部基本面加入三因子與無因子對匯率預測之比較67

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指導教授

徐之強(Chih-Chiang Hsu)

審核日期

2010-6-23

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