Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/20622
標題: The Structural Changes and Persistence of Implied Volatility of Main Foreign Exchange Returns In Taiwan-The Application of DSFM and ICSS Algorithm
台灣主要外幣匯率報酬率的波動結構性改變與波動持續性之研究-DSFM模型與ICSS演算法之應用
作者: 黃朝暐
Huang, Choa-Wei
關鍵字: 隱含波動度
Implied volatility
波動持續性
結構性改變
DSFM模型
ICSS
Persistence volatility
Structural changes
DSFM(Dynamic Single Factor Model)
ICSS algorithm(Iterated Cumulative Sums of Squares Algorithm)
出版社: 企業管理學系所
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摘要: The Structural Changes and Persistence of Implied Volatility of Main Foreign Exchange Returns In Taiwan–The Application of DSFM and ICSS Algorithm. Abstract Since the Bretton Woods System collapsed in 1973, the implied volatility of the return of the exchange rate has been an important issue in financial domain. Generally, it was considered that GARCH Model is the most representative quantitative method for analyzing the volatility of exchange rate returns. However, GARCH Model does not consider that unconditional variance would result into the multi-structural changes. Thus, while using GARCH Model to evaluate the return of financial assets, we found that it presented high persistence volatility. To avoid this disadvantage, this article used ICSS(Iterated Cumulative Sums of Squares)algorithm to test the points of structural changes and compare them with real economic events. And then, we verified the validity of ICSS algorithm. We found that if we set US dollar and Hong Kong currency which were got from the accumulation of dynamic multiplier via DSFM analying and the trades between these two companies as standards, we can discover that the persistence of the return of RMB (Renminbi) and JPY (Japanese Yen) are obviously decreased. This result provides evidence that the research which was analyzed by Time Series Analysis might overestimate the level of the persistence volatility. Keywords : implied volatility、persistence volatility、Structural changes、 DSFM(Dynamic Single Factor Model)、ICSS algorithm (Iterated Cumulative Sums of Squares Algorithm)
摘要 自從1973年The Bretton Woods System崩潰後,匯率報酬率隱含波動度(implied volatility)在財務領域上變成一個很重要的議題。一般學者們皆認為探討匯率報酬率之波動時,GARCH模型是最具代表性之計量方法,但是由於未考慮非條件變異數存在多重結構性改變之因素,導致使用GARCH模型估計金融資產報酬率呈現出高度波動持續性之現象。故本研究應用ICSS(Iterated Cumulative Sums of Squares)演算法,來檢定台灣主要外幣匯率報酬率結構性改變之時點並與真實經濟事件時點對比,驗證 ICSS的有效性,並將這些結構性改變時點以虛擬變數方式加入GARCH模型中進行實證分析,發現以雙邊貿易量大小為標準,選出人民幣、日圓兩種主要外幣與根據DSFM(Dynamic Single Factor Model)模型累積動態乘數所找出之美元及港幣的外幣匯率報酬率波動持續性明顯降低,這結果顯示先前許多使用時序資料之研究可能高估波動持續性的程度。 關鍵詞:隱含波動度、波動持續性、結構性改變、DSFM模型、ICSS 演算法
URI: http://hdl.handle.net/11455/20622
其他識別: U0005-0407200713512100
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