Predictive Ability Tests with Possibly Overlapping Models - Economics Seminar

Event Date: 23 November 2022

Speaker: Jack Fosten, Senior Lecturer & Deputy Director of the Data Analytics for Finance and Macro Research, Kings College London

Time: 4-5:15pm

Location: Please contact Rachel Hill (r.hill@strath.ac.uk) for Zoom details.

Abstract:  "This paper provides novel tests for comparing out-of-sample predictive ability of two or more competing models that are possibly overlapping. The tests do not require pre-testing, and importantly are valid under different out-of-sample estimation schemes, under dynamic mis-specification, and under general loss functions used for forecast evaluation. In pairwise model comparisons, the test is constructed by adding a random perturbation to both the numerator and denominator of a standard Diebold-Mariano test statistic, which prevents degeneracy in the presence of overlapping models, but becomes asymptotically negligible otherwise. A similar idea is used to develop a superior predictive ability test for the comparison of multiple models to a benchmark. We establish the first order validity of block bootstrap critical values which are simple to compute."

Published: 20 September 2022