Semi-Parametric Bootstrap-Based Inference in Long-Memory Models

Data in the economic and financial spheres often exhibit dynamic patterns characterized by a long-lasting response to past shocks. The correct modelling of such long-range dependence is of paramount importance, both in the production of accurate forecasts over long-term horizons and in the isolation of long-run equilibrium relationships. We will produce new methodological and theoretical advances pertaining to statistical inference in time series models in which such 'long-memory' properties feature. Based on semi-parametric techniques, the aim is to produce inferences about long-memory phenomena that are accurate, no matter what the precise nature of the true, but unknown, data generating process.