A New EMD Approach using Local Median Smoothing
This research is a collaboration across multiple institutions within the MSCA Digital Finance network.
Lead Researcher
Humboldt-Universitat zu Berlin
MSCA Digital FinancePrincipal Investigator
Weierstrass Institute (WIAS), Berlin
Project Director
Humboldt-Universitat zu Berlin, IDA
IDA DirectorResearcher
National Yang Ming Chiao Tung University (NYCU), Taiwan
Doctoral Researcher
Bucharest University of Economic Studies (ASE)
MSCA Digital FinanceCo-Investigator
Bucharest University of Economic Studies (ASE)
Partner institutions in the MSCA Digital Finance research network.
Institute for Digital Assets
Humboldt-Universitat zu Berlin
Bucharest University of Economic Studies
Warsaw School of Economics
University of Edinburgh
National Yang Ming Chiao Tung University
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This work is part of the MSCA Digital Finance project, funded by the Marie Sklodowska-Curie Actions (MSCA) under the European Union's Horizon programme.
The project develops robust signal decomposition methods for analyzing non-stationary financial time series, with applications to:
Sha, Y., Spokoiny, V., Hardle, W. K., Jheng, D. S.-L., Ionescu, M.-E., & Pele, D. T. (2024). A New EMD Approach using Local Median Smoothing. Working Paper.