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系統識別號 U0026-0907201320445700
論文名稱(中文) 波動非對稱下之跳躍擴散模型與風險值應用
論文名稱(英文) Jump Diffusion Model with Asymmetry of Volatility for VaR
校院名稱 成功大學
系所名稱(中) 統計學系碩博士班
系所名稱(英) Department of Statistics
學年度 101
學期 2
出版年 102
研究生(中文) 蔡明軒
研究生(英文) Ming-Hsuan Tsai
電子信箱 s96210065@gmail.com
學號 R26001045
學位類別 碩士
語文別 英文
論文頁數 30頁
口試委員 指導教授-黃銘欽
口試委員-呂金河
口試委員-蘇永在
中文關鍵字 風險值  跳躍擴散模型  波動不對稱GARCH模型 
英文關鍵字 VaR  Jump Diffusion Model  Asymmetric Volatility GARCH Model 
學科別分類
中文摘要 金融資產報酬率具有高狹峰與偏態等特性,傳統的常態分配假設下之資產報酬率模型無法描述此現象;更甚者,資產報酬率常受到外在因素影響,導致資產價格呈現瞬間跳躍,跳躍擴散模型因此蓬勃發展。本研究修改Kou(Kou, 2002)之跳躍振幅為非對稱雙指數分配模型,並結合GJR-GARCH 模型,其結果與Kou(Kou, 2002)及Hanson和Westman(Hanson & Westman, 2002)之跳躍模型進行比較。實證結果顯示:應用在台灣加權指數方面,本研究所提出之模型得到較準確風險值評估。
英文摘要 Financial asset returns have some characteristics of leptokurticity and skewness. Traditional normality assumption of the return distribution couldn’t describe this phenomenon. What’s more, financial asset returns are often affected by external factors which lead to instant price jumps. Jump diffusion models therefore attract more and more attention. This thesis modifies the asymmetric double-exponential jump-amplitude model proposed by Kou(Kou, 2002) and combines it with the GJR-GARCH volatility model. The result of this research is compared with the Kou (Kou, 2002) and Hanson & Westman (Hanson & Westman, 2002) jump models. Our empirical study on TAIEX index data shows the proposed model gives more accurate VaR.
論文目次 Table of Contents
摘要 I
Abstract II
致謝 III
Table of Contents IV
Tables V
Figures V
Chapter 1 Introduction 1
1-1 Research Background and Motivation 1
1-2 Purpose of Research and Frameworks 2
Chapter 2 Literature Review 3
2-1 Value at Risk 3
2-2 Volatility Model 6
2-2-1 SMA and EWMA 7
2-2-2 GARCH Models 7
2-3 Back-Testing 8
2-3-1 Frequency of Losses 9
2-3-2 Root Mean Square Error (RMSE) 9
Chapter 3 Methodology 11
3-1 Jump Diffusion Stochastic Process 11
3-1-1 Diffusion Stochastic Process 12
3-1-2 Jump Diffusion Stochastic Process 12
3-2 Proposed model 14
3-2-1 Jump Amplitude 14
3-2-2 Parameter Estimation 17
3-2-3 Proposed Model with GJR-GARCH Volatility 18
Chapter 4 Empirical study 20
Chapter 5 Conclusion 25
References 26
Appendix 28
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