Modeling Dependence and Tails of Financial Time Series

By Thomas Mikosch. 2003

104 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/50d620aebc0fbcdd4b74fd726a8a797eabdc9a68

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In Economics and Econometrics

Citations in the corpus

Multivariate extremes, aggregation and dependence in elliptical distributions (2002, background): “For more on multivariate regular variation see [11] and [10].”
Multivariate extremes and the aggregation of dependent risks: examples and counter-examples (2009, unknown): “A brief and very readable introduction to the field is found in Mikosch (2004).”
Break detection in the covariance structure of multivariate time series models (2009, background): “Manifold estimation procedures are well-developed and tests assessing the structural stability and the goodness of fit are widely available (see, among many others, [9, 16, 18, 39, 40, 48] and the references therein).”
On the foundations of multivariate heavy-tail analysis (2004, background): “Useful surveys by Mikosch [35] and Resnick [42] appear in the SemStat volume [26].”
On the estimation and application of max-stable processes (2010, background): “Lee and Hansen (1994) discussed maximum likelihood estimation of GARCH model with weak stationary residuals; Mikosch (2003) gave a very thorough study of GARCH modeling of dependence and tails of financial time series.”
Stable limits of martingale transforms with application to the estimation of garch parameters (2006, background): “Then,in particular,the m arginaldistribution ofthe G ARCH process has in nite fourth m om ent and standard asym ptotic theory with norm allim its and p n-rates breaks down.”
Regularly varying functions (2006, background): “For example, this is the case for a strictly stationary GARCH(p, q) process, see e.g. Mikosch [39].”