¿Qué tan buenos son los patrones del igbc para predecir su comportamiento? Una aplicación con datos de alta frecuencia

Alonso, Julio César

doi:10.1016/S0123-5923(09)70078-6

Información del artículo

Resumen

Bibliografía

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Estadísticas

Resumen

El objetivo del artículo es evaluar la utilidad de patrones de comportamiento para predecir el comportamiento futuro del Índice General de la Bolsa de Colombia (IGBC). Para tal fin, se emplearon 18 diferentes especificaciones del modelo GARCH-M y datos de alta frecuencia. Los modelos considerados tienen en cuenta el efecto Leverage, el efecto Día de la Semana, el efecto Hora y el efecto Día-Hora. Se evalúan 115 pronósticos para los siguientes 10 minutos para cada uno de los 18 modelos, empleando estadísticas descriptivas y las pruebas de Granger y Newbold (1977) y Diebold y Mariano (1995). Se encuentra que la mejor especificación es la que no tiene en cuenta el efecto día-hora en la media ni en la varianza.

Palabras clave:

Intraday

Garch-M

efecto Día de la Semana

efecto Hora

efecto Día-Hora

Abstract

The purpose of this article is to evaluate the usefulness of performance trends for forecasting the future performance of the IGBC (Colombian exchange market index). To this end, 18 different specifications of the GARCH-M model and high frequency data were used. The models in review considered the leverage, day-of-the-week, hour-of-the-day, and day-hour effects. 115 different forecasts for the next 10 minutes were assessed for each of the 18 models, using descriptive statistics and the Granger's and Newbold (1977) and Diebold's and Mariano (1995) tests. The best model was found to be the one that does not consider the day-hour effect on the mean or the variance.

Keywords:

Intraday

Garch-M

day-of-the-week effect

hour-of-the-day effect

day-hour effect

Resumo

O objetivo do artigo é avaliar a utilidade de padrões de comportamento para prever o comportamento futuro do Índice Geral da Bolsa da Colômbia (IGBC). Para esse fim, se empregaram 18 diferentes especificações do modelo GARCH-M e dados de alta frequência. Os modelos considerados têm em conta o efeito “Leverage” (Avalancagem), o efeito “Dia da Semana”, o efeito “Hora” e o efeito “Dia-Hora. São avaliados 115 prognósticos para os 10 minutos seguintes para cada um dos 18 modelos, empregando estatísticas descritivas e as provas de Granger e Newbold (1977) e Diebold e Mariano (1995). Se verifica que a melhor especificação é aquela que não tem em conta o efeito dia-hora na média nem na variação.

Palavras-chave:

Intraday

Garch-M

efeito Dia da Semana

efeito Hora

efeito Dia-Hora

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