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

2018/12/18 by Bisaglia, Luisa, Grigoletto, Matteo
#Applications (stat.AP) #FOS: Computer and information sciences #FOS: Economics and business #Methodology (stat.ME) #Statistical Finance (q-fin.ST)

paper · doi:10.48550/arxiv.1812.07295

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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