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Gaussian Mixture and Kernel Density-Based Hybrid Model for Volatility Behavior Extraction From Public Financial Data
[Zeitschriftenartikel]
Abstract This paper carried out a hybrid clustering model for foreign exchange market volatility clustering. The proposed model is built using a Gaussian Mixture Model and the inference is done using an Expectation Maximization algorithm. A mono-dimensional kernel density estimator is used in order to build ... mehr
This paper carried out a hybrid clustering model for foreign exchange market volatility clustering. The proposed model is built using a Gaussian Mixture Model and the inference is done using an Expectation Maximization algorithm. A mono-dimensional kernel density estimator is used in order to build a probability density based on all historical observations. That allows us to evaluate the behavior’s probability of each symbol of interest. The computation result shows that the approach is able to pinpoint risky and safe hours to trade a given currency pair.... weniger
Thesaurusschlagwörter
Finanzmarkt; Devisen; statistische Methode; Algorithmus; künstliche Intelligenz
Klassifikation
Volkswirtschaftstheorie
Erhebungstechniken und Analysetechniken der Sozialwissenschaften
Freie Schlagwörter
foreign exchange market; gaussian mixture model; kernel density estimation; algorithmic trading
Sprache Dokument
Englisch
Publikationsjahr
2019
Zeitschriftentitel
Data, 4 (2019) 1
Heftthema
Data Analysis for Financial Markets
DOI
https://doi.org/10.3390/data4010019
ISSN
2306-5729
Status
Veröffentlichungsversion; begutachtet (peer reviewed)