A new structure for analyzing discrete scale invariant processes: covariance and spectra

DOI10.1007/s10955-013-0799-4zbMath1283.62192arXiv1003.1187OpenAlexW1974709536MaRDI QIDQ385562

N. Modarresi, Saeid Rezakhah

Publication date: 2 December 2013

Published in: Journal of Statistical Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1003.1187

zbMATH Keywords

multi-dimensional self-similar processesspectral density matrixwide sense Markov

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Inference from stochastic processes and spectral analysis (62M15) Markov processes (60J99)

Related Items

Discretization of continuous time discrete scale invariant processes: estimation and spectra, Innovative methods for modeling of scale invariant processes, Characterization of discrete scale invariant Markov sequences, Multi-scale invariant fields: estimation and prediction

Cites Work

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• Weak convergence of positive self-similar Markov processes and overshoots of Lévy processes
• Spectral analysis of multi-dimensional self-similar Markov processes
• Scale invariances and Lamperti transformations for stochastic processes