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arXiv · 1812.07295

A new time-varying model for forecasting long-memory series

Luisa Bisaglia·Matteo Grigoletto
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Abstract

In this work we propose a new class of long-memory models with time-varying fractional parameter. In particular, the dynamics of the long-memory coefficient, $d$, is specified through a stochastic recurrence equation driven by the score of the predictive likelihood, as suggested by Creal et al. (2013) and Harvey (2013). We demonstrate the validity of the proposed model by a Monte Carlo experiment and an application to two real time series.

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Luisa Bisaglia, Matteo Grigoletto. 2018-12-18. A new time-varying model for forecasting long-memory series. https://arxiv.org/abs/1812.07295

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