Application of empirical mode decomposition to analyze simulated financial time series
Result description
Paper is focused on application of empirical mode decomposition technique to analyze time series generated by financial simulators. EMD technique like Fourier or wavelet method decomposes a signal into a series of simpler functions. These functions are known as intrinsic mode functions. The most advantage of IMF is that they are filtered directly from the original time series. Implementation and algorithmic details of EMD technique is discussed in detail. Simulations of financial time series are performed by various generators, which are based either on computer-agents technique or numerical solvers of stochastic differential equations. Varying constitutive equations which describe different trading strategies of interacting agents produce different time series to analyze. Numerical results of performed analysis are presented.
Keywords
empirical mode decompositionintrinsic mode functionstime series analysissimulationforeign exchange rate models
The result's identifiers
Result code in IS VaVaI
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Application of empirical mode decomposition to analyze simulated financial time series
Original language description
Paper is focused on application of empirical mode decomposition technique to analyze time series generated by financial simulators. EMD technique like Fourier or wavelet method decomposes a signal into a series of simpler functions. These functions are known as intrinsic mode functions. The most advantage of IMF is that they are filtered directly from the original time series. Implementation and algorithmic details of EMD technique is discussed in detail. Simulations of financial time series are performed by various generators, which are based either on computer-agents technique or numerical solvers of stochastic differential equations. Varying constitutive equations which describe different trading strategies of interacting agents produce different time series to analyze. Numerical results of performed analysis are presented.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Mathematical Methods in Economics 2010
ISBN
978-80-7394-218-2
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
University of South Bohemia
Place of publication
České Budějovice
Event location
České Budějovice
Event date
Jan 1, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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Result type
D - Article in proceedings
CEP
BB - Applied statistics, operational research
Year of implementation
2010