本文探討上證指數、恆生國企股指數與恆生國企股期貨指數之間在次級房貸事件與金融海嘯期間波動性與相關性行程的變動過程，文中發現對三種指數而言，分析其報酬率的互動情形時，VEC GJR-GARCH 模型優於單純的向量誤差修正 (VEC) 模型。而利用Inclan and Tiao (1994) 之ICSS 法，可協助發現多重波動性結構改變的時點，正是次貸危機時期與全球金融海嘯時期。在VEC DCC GJR-GARCH 模型的分析之下，研究發現次貸危機與全球金融海嘯事件對上海與恆生股票市場波動性都產生增強的效果，另外就相關性而言，僅金融海嘯事件對於市場間的相關性有顯著且正向的影響，至於次貸危機事件，雖亦造成市場間相關性增加，但並不具統計顯著性。換言之，個別市場波動性對外在環境的改變較為敏感，而市場間的相關性變化，主要取決於二市場間的交互作用變化，雖也會受外在重大事件的影響，但仍須視外在事件之重要程度而定。

This study discusses the dynamical volatility and correlation relationships among SSE Composite Index, Hang Seng China Enterprises Index and Hang Seng China Enterprises Futures Index under the crisis of subprime mortgage and global financial tsunami. Based on the empirical study, we find the VEC GJR-GARCH model is better than pure Vector error correction(VEC) approach when analyzing the interactions of these returns structure. By using ICSS method which proposed by Inclan and Tiao(1994), we can catch up the structure change points for variance processes. The variance structure change periods just correspond to the event of subprime mortgage and financial tsunami events. Under the method of VEC DCC GJR-GARCH model, we also find these crisis events will boost the level of volatility to respective financial market. As to the impact for the correlation structure created from the crisis events among these target markets, the influence from the financial tsunami event is stronger than the subprime mortgage event from the viewpoints of statistics significance.