Resumo

LADRON DE GUEVARA CORTES, Rogelio; TORRA PORRAS, Salvador  e  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. Comp. y Sist. [online]. 2018, vol.22, n.4, pp.1049-1064.  Epub 10-Fev-2021. ISSN 2007-9737.  https://doi.org/10.13053/cys-22-4-3083.

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.

Palavras-chave : Extraction techniques; underlying risk factors; independent component analysis; arbitrage pricing theory; Mexican stock exchange.

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