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FACULTAD FACULTAD DE INGENIERÍA INGENIERÍA DE SISTEMAS SISTEMAS
CÁTEDRA
:
ECONOMETRÍA
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INTRODUCCIÓN AUTOCORRELACION HETEROCEDASTICIDAD
Series de tiempo or e ra ransv nsversa ersa
Los investigadores en la proyección de series de tiempo financieras, tales como precios de acciones, tasas de inflación, tasas de cambio, han observado que su habilidad de predecir tales variables varía considerablemente de un periodo a otro.
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IDEAS CLAVE CLAVE VOLATILIDAD :
•
en un periodo determinado.
• Es de anotar que, aunque la serie sea estacionaria y
tenga, por tanto, varianza constante, puede presentar oscilaciones a corto plazo que es lo que recoge la varianza condicional para el estudio de la volatilidad.
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MODELOS AUTORREGRESIVOS uan o e mo e o e regres n nc uye no solamente los valores actuales sino además los valores rezagados (pasados) de las variables explicativas (las X), se denomina modelos de rezagos distribuidos. Si el modelo incluye uno o más valores rezagados (pasados) de las variables
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REPRESENT REPRESENTACIÓN ACIÓN DE DE UN MODEL MODELO AUTORREGRESIVO
Representa un modelo de rezago distribuido mientras que
Es un ejempl ploo de un modelo autorregresivo Estos
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EL PAPEL DEL “TIEMPO”, O EL “REZAGO” EN LA ECONOMÍA En Economía la dependencia de una variable Y (la (la varia riable depen pendien iente) respecto a otra u otra otrass vari variab able less X (las (las vari variab able less ex expl plic icat ativ ivas as)) raramente es instantánea. Muy frecuentemente, Y responde a X en un la de ti el al de mi
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DEFINICIÓN Los modelos ARCH
han sido diseñados
ara
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OBJETIVOS DEL MODELO ARCH Contrib ribuir con la dism isminución de las limitaciones estructurales de los modelos financieros al incorporar t
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MODELO ARCH • En el modelado de la econométrica tradicional,
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MODELO ARCH Un proceso ARCH(q) simple viene definido por dos expresiones:
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MODELO ARCH La ideal del ARCH es que la varianza de µ en el tiempo t (=σ2), depende del tamaño del término de error al cuadrado en el tiempo (t-1), es decir de µ 2t-1.
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