Extraction of the underlying structure of systematic risk from non-Gaussian multivariate financial time series using independent component analysis: Evidence from the Mexican stock exchange
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hdl:2117/175732
Tipus de documentArticle
Data publicació2018-01-01
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Abstract
Regarding the problems related to multivariate non-Gaussianity of financial time series, i.e., unreliable results in extraction of underlying risk factors -via Principal Component Analysis or Factor Analysis-, we use Independent Component Analysis (ICA) to estimate the pervasive risk factors that explain the returns on stocks in the Mexican Stock Exchange. The extracted systematic risk factors are considered within a statistical definition of the Arbitrage Pricing Theory (APT), which is tested by means of a two-stage econometric methodology. Using the extracted factors, we find evidence of a suitable estimation via ICA and some results in favor of the APT.
CitacióLadrón de Guevara, R.; Torra Porras, S.; Monte, E. Extraction of the underlying structure of systematic risk from non-Gaussian multivariate financial time series using independent component analysis: Evidence from the Mexican stock exchange. "Computación y sistemas", 1 Gener 2018, vol. 22, núm. 4, p. 1049-1064.
ISSN2007-9737
Versió de l'editorhttp://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/3083/0
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