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
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 ex...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/175732 |
| Acceso en línea: | https://hdl.handle.net/2117/175732 https://dx.doi.org/10.13053/CyS-22-4-3083 |
| Access Level: | acceso abierto |
| Palabra clave: | Mathematical statistics Computer science Extraction techniques Underlying risk factors Independent component analysis Arbitrage pricing theory Mexican stock exchange Estadística matemàtica Informàtica Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica Àrees temàtiques de la UPC::Informàtica |
| Sumario: | 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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