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Title: Recursive estimation of multivariate GARCH processes Authors:  Radek Hendrych - Charles University (Czech Republic) [presenting]
Abstract: Recursive estimation methods suitable for univariate GARCH models have been recently studied in the literature. They undoubtedly represent attractive alternatives to the standard non-recursive estimation procedures with many practical applications (especially in the context of high-frequency financial data). It might be truly advantageous to adopt numerically effective techniques that can estimate, monitor, and control such models in real time. The aim is to extend this methodology to multivariate GARCH processes by applying general recursive estimation instruments. In particular, the suggested approach seems to be useful for various multivariate financial time series with (conditionally) correlated components. Monte Carlo experiments are performed in order to investigate the proposed algorithms. Moreover, real data examples are also discussed.