This article considers the daily yield of a financial asset for the purpose of modeling and comparing its stochastic volatility probability density. To do so, ARCH models and their extensions in discrete time are proposed as well as the empirical stochastic volatility mo-del developed by Paul Wilmot...

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Autores:
Tipo de recurso:
Fecha de publicación:
2008
Institución:
Universidad de Medellín
Repositorio:
Repositorio UDEM
Idioma:
spa
OAI Identifier:
oai:repository.udem.edu.co:11407/1419
Acceso en línea:
http://hdl.handle.net/11407/1419
Palabra clave:
ARCH
Heterocedasticity
Itô dissemination processes
Probability density function
Simulation
Volatility
Rights
restrictedAccess
License
http://purl.org/coar/access_right/c_16ec
Description
Summary:This article considers the daily yield of a financial asset for the purpose of modeling and comparing its stochastic volatility probability density. To do so, ARCH models and their extensions in discrete time are proposed as well as the empirical stochastic volatility mo-del developed by Paul Wilmott. For the discrete case, the models that enable estimating the conditional heterocedastic volatility in an instant t of time, t∈[1,T] are shown. For the continuous case, an Itô dissemination process is associated with the stochastic volatility of the financial series; that enables making said process discrete and simulating it, to obtain empirical volatility probability densities. Finally, the results are illustrated and compared to the methodologies discussed in the case of the financial series United Status S&P 500, the Mexican Stock Exchange Price and Quote Index (IPC is the Mexican acronym), and the Colombian Stock Exchange General Index (IGBC is the Colombian acronym).