Modelling Time-variant Dependence Structure by Regime-switching Copula Models
碩士 === 國立臺灣大學 === 經濟學研究所 === 92 === ABSTRACTS In this thesis, we explore the time-variant bivariate dependence structure by a class of regime switching copula models. We consider a dynamic mixed copula in which the parameters are governed by a hidden Markov chain. In our empirical study, we apply a...
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| Format: | Others |
| Language: | en_US |
| Published: |
2004
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| Online Access: | http://ndltd.ncl.edu.tw/handle/34864004876614342530 |
| Summary: | 碩士 === 國立臺灣大學 === 經濟學研究所 === 92 === ABSTRACTS
In this thesis, we explore the time-variant bivariate dependence structure by a class of regime switching copula models. We consider a dynamic mixed copula in which the parameters are governed by a hidden Markov chain. In our empirical study, we apply a number of MS-mixed copulae to explore bivariate dependence between the daily returns of DJIA and NASDAQ. The structural change analysis indicates that the concordant association between these two return series is time-variant. Markov switching mixed normal copula model is suitable for interpreting the bivariate dependence of DJIA and NASDAQ returns. This result implies that the dependence may switch between the low and high concordance states.
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