Parsimonious Heterogeneous ARCH Models for High Frequency Modeling release_m5xyvuh5hfd2dad6qdhbbqvmzi

by Juan Carlos Ruilova, Pedro Alberto Morettin

Published in Journal of Risk and Financial Management by MDPI AG.

2020   Volume 13, p38

Abstract

In this work we study a variant of the GARCH model when we consider the arrival of heterogeneous information in high-frequency data. This model is known as HARCH(n). We modify the HARCH(n) model when taking into consideration some market components that we consider important to the modeling process. This model, called parsimonious HARCH(m,p), takes into account the heterogeneous information present in the financial market and the long memory of volatility. Some theoretical properties of this model are studied. We used maximum likelihood and Griddy-Gibbs sampling to estimate the parameters of the proposed model and apply it to model the Euro-Dollar exchange rate series.
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Date   2020-02-20
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