臺灣博碩士論文加值系統

本研究以新台幣兌美元匯率為主要研究對象估算其風險值，並應用Bollerslev (1986) 提出的GARCH、Glosten,Jaganathan,and Runkle (1993) 提出GJR-GARCH、及Tse (1998) 提出的FIAPARCH模型來衡量新台幣兌美元匯率之報酬波動，並以GARCH (1,1) 為基礎，使用GJR-GARCH及FIAPARCH為擴展模型。為了更精確計算風險值故採用常態分配及t分配來做模型估計及風險值之計算，並進行回溯測試 (back testing)，比較各模型間估計績效。實證結果顯示ARMA (2,2) -FIAPARCH (1,d,1) -N為最佳估計風險值之模型。

This paper focus on the VaR of the exchange rate of NTD/USD. In addition to value the return volatility of the NTD/USD exchange rate by applying the Bollerslev’s (1986) GARCH model, Glosten, Jaganathan and Runkle’s (1993) GJR-GARCH model, and Tse’s (1998) FIAPARCH model, an extended GJR-GARCH and FIAPARCH model based on the GARCH (1,1) is used. Normal distribution and t-disruption are used to achieve higher accuracy of the estimation of VaR. The efficiency among different models are tested by a back testing. The result shows that the ARMA (2,2) -FIAPARCH (1,d,1) -N model is the best model to estimate the VaR.

目 錄
中文摘要 i
英文摘要 ii
致謝 iii
目錄 iv
表目錄 vi
圖目錄 vii
第一章 緒論 1
第一節 研究動機與目的 1
第二節 研究流程與架構 2
第二章 文獻探討 4
第一節 ARCH模型在VaR估計中之應用 4
第二節 GARCH (1,1) 為最適模型之實證文獻 4
第三節 GARCH模型在VaR之實證文獻 6
第三章 理論模型架構與研究方法 8
第一節 定態 (Stationary) 與單根檢定 (Unit Root Test) 8
一、定態 (Stationary) 8
二、單根檢定 (Unit Root Test) 9
第二節 選擇ARMA模型之準則 11
第三節 ARCH檢定與GARCH模型 12
一、ARCH檢定 13
二、GARCH模型 15
第四節 GJR-GARCH及FIAPARCH模型 16
一、GJR-GARCH模型 16
二、FIAPARCH模型 18
第五節 風險值 19
一、One-day-ahead風險值預測 19
二、風險值 19
三、參數VaR模型 19
四、非參數及半參數VaR模型 19
五、回溯測試應用於風險值 22
六、回溯測試之VaR在無條件覆蓋率方面 22
七、回溯測試之VaR在條件覆蓋率方面 23
八、VaR之損失函數 23
第六節 期望損失缺口 23
一、One-day-ahead期望損失缺口之預測 24
二、歷史模擬 (HS) 和過濾歷史模擬 (FHS) 之期望損失缺口 25
三、損失函數之期望損失缺口 25
第七節 One-Step-ahead風險值及期望損失缺口之預測 26
第四章 實證結果分析 27
第一節 實證樣本與資料處理 27
一、實證樣本 27
二、資料處理 27
三、基本統計量分析 29
第二節 風險值模型之樣本內參數估計 30
第三節 GARCH、GJR-GARCH、FIAPARCH模型之實證結果 33
第五章 結論 35
參考文獻 36

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