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Dynamic Dependence Models Of Financial Assets And Its Empirical Research

Posted on:2010-04-15Degree:MasterType:Thesis
Country:ChinaCandidate:G ChenFull Text:PDF
GTID:2189360302959886Subject:Financial engineering
Abstract/Summary:PDF Full Text Request
The issue of dependence between financial assets is a foundational issue in modern financial theory and practice. In many applications related with assets of more than two, such as asset pricing, asset selection, volatility spillover and risk management, the measure of association between assets need to be taken into account. As we all know, financial markets are complicated dynamical systems. The dependence structure is impacted by lots of factors inside and outside the markets. It would be inappropriate to set the measure of association invariable. Therefore, when we deal with the measure of association between financial assets, the consideration of dynamic structure is meaningful.There are several different ways to describe the dynamic structure of the dependence. In this article, we have considered two description methods. One is the time-varying model; the measure of association is different at each time. The other is the regime switching model; the measure of association is constant within a regime but different across regimes. The transitions between the regimes are governed by a Markov chain.In the former kind of model, the Dynamic Conditional Correlation (DCC) model proposed by Engle is representative. The model describes the evolution path of the time-varying correlation with parsimonious parametric while providing a simple method of estimation. In this paper, we introduce the concept of Copula and point out that the DCC model is a particular case of multivariate Normal copula model, thus extend it to the general form. We use flexible marginal distribution to replace the normal distribution assumption, construct generalized DCC model under the multivariate Normal copula and the multivariate Student't copula (t-Copula). Empirical study on Chinese stock markets have shown that using the heavy-tailed distribution such as student(t) distribution and Generalized error distribution for the marginal distribution can measure the Value at risk (VaR) of the portfolio in the 99% confidence level better .In the latter kind of model, through introducing state variable into Copula, we build one regime switching Copula model. We discuss the general application under this model and analyze the features of the measure of association in this model. Empirical study on Chinese stock markets have shown that regime switching Copula model can be applied to explain the differences in the dependence between different market quotation .
Keywords/Search Tags:dynamic dependence, Copula, multivariate GARCH, time-varying, regime switching model, VaR
PDF Full Text Request
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