臺灣博碩士論文加值系統

本論文研究多元門檻向量自我迴歸(Vector Autoregressive) 具有多元GARCH-條件動態相關DCC (Dynamic Conditional Correlation)模型在財務上的應用。此模型結合了多元門檻不對稱性和多元GARCH 應用分析財務市場上均值和波動度的不對稱性。在此模型中，決定不同迴歸模型的門檻變數是由VAR 中的所有變數權重加總而成。同時，本論文亦利用馬可夫鏈蒙地卡羅法估計參數，利用貝氏方法比較不同模型，以及利用Quadratic and LINEX 兩種不同損失函數來評比不同模型的預測S&P500 和NASDAQ 的波動度及兩者的相關係數結果。然而，結果顯示出具有門檻的模型對於配適以及預測的結果會優於一般的線性模型。

CONTENTS

LIST OF TABLES V
1. INTRODUCTION 1
2. MODEL 4
3. BAYESIAN INFERENCE 8
3.1 PRIOR 9
3.2 POSTERIOR 11
3.3 LOSS FUNCTION 13
3.4 MODEL SELECTION 14
4. APPLICATION TO FINANCIAL MARKETS 16
4.1 DATA, MODEL DESCRIPTION 16
4.2 MODEL SELECTION AND ESTIMATION RESULTS 17
4.3 FORECAST EVALUATION 20
5. CONCLUSION 20

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