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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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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.
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LADRÓN DE GUEVARA CORTÉS, Rogelio, TORRA PORRAS, Salvador, MONTE MORENO, Enric. 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_. 2018. Vol. 22, núm. 4, pàgs. 1049-1064. [consulta: 25 de febrer de 2026]. ISSN: 1405-5546. [Disponible a: https://hdl.handle.net/2445/162077]