Since the Bretton Woods System collapsed, the volatility of the exchange rate return has been an important and concerned issue in financial domain. The purpose of this paper is to investigate the empirical relevance of stricture breaks for the volatility of the exchange rate return, and we use both in-sample and out-of-sample tests. GARCH(1,1) Model is considered to be the representative quantitative method for analyzing the volatility of asset returns, as a result, we picked GARCH(1,1) as natural benchmarks in this article. In addition, we cogitated the structure breaks in this paper, and used ICSS(Iterated Cumulative Sums of Squares) algorithm to test the points of structural breaks. The results of empirical analysis show that there are significant evidences of structural breaks in the unconditional variance for six of eight US exchange rate return series, which implying unstable GARCH processes for these exchange rates. We also find those competing models that accommodating structural breaks will have higher predictive ability. Pooling forecasts from different models that allow for structural breaks in volatility appears to offer a reliable method for improving volatility forecast accuracy given the uncertainty surrounding the timing and size of the structural breaks.
Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0625110-101419 |
Date | 25 June 2010 |
Creators | Zeng, Han-jun |
Contributors | Jyh-Lin Wu, Ching-Nun Lee, Yu-Hau Hu |
Publisher | NSYSU |
Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
Language | Cholon |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0625110-101419 |
Rights | campus_withheld, Copyright information available at source archive |
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