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Mixing conditions for multivariate infinitely divisible processes with an application to mixed moving averages and the supOU stochastic volatility model

Florian FuchsRobert Stelzer — 2013

ESAIM: Probability and Statistics

We consider strictly stationary infinitely divisible processes and first extend the mixing conditions given in Maruyama [15 (1970) 1–22] and Rosiński and Żak [61 (1996) 277–288] from the univariate to the -dimensional case. Thereafter, we show that multivariate Lévy-driven mixed moving average processes satisfy these conditions and hence a wide range of well-known processes such as superpositions of Ornstein − Uhlenbeck (supOU) processes or (fractionally integrated) continuous time autoregressive...

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