ARFIMAX and ARFIMAX-TARCH realized volatility modeling

Stavros Degiannakis

doi:10.1080/02664760802271017

ARFIMAX and ARFIMAX-TARCH realized volatility modeling

Stavros Degiannakis

Research output: Contribution to journal › Article › peer-review

Abstract

ARFIMAX models are applied in estimating the intra-day realized volatility of the CAC40 and DAX30 indices. Volatility clustering and asymmetry characterize the logarithmic realized volatility of both the indices. The ARFIMAX model with time-varying conditional heteroskedasticity is the best performing specification and, at least in the case of DAX30, provides statistically superior next trading day’s realized volatility forecasts.

Original language	English
Pages (from-to)	1169-1180
Number of pages	12
Journal	Journal of Applied Statistics
Volume	35
Issue number	10
DOIs	https://doi.org/10.1080/02664760802271017
Publication status	Published - 2008

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10.1080/02664760802271017

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title = "ARFIMAX and ARFIMAX-TARCH realized volatility modeling",

abstract = "ARFIMAX models are applied in estimating the intra-day realized volatility of the CAC40 and DAX30 indices. Volatility clustering and asymmetry characterize the logarithmic realized volatility of both the indices. The ARFIMAX model with time-varying conditional heteroskedasticity is the best performing specification and, at least in the case of DAX30, provides statistically superior next trading day{\textquoteright}s realized volatility forecasts.",

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AB - ARFIMAX models are applied in estimating the intra-day realized volatility of the CAC40 and DAX30 indices. Volatility clustering and asymmetry characterize the logarithmic realized volatility of both the indices. The ARFIMAX model with time-varying conditional heteroskedasticity is the best performing specification and, at least in the case of DAX30, provides statistically superior next trading day’s realized volatility forecasts.

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ARFIMAX and ARFIMAX-TARCH realized volatility modeling

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