A seminar by Professor Tak Kuen Siu from Macquarie University
Title: Threshold Autoregressive Nearest-Neighbour Models for Claims Reserving
Abstract: Motivated by claims reserving in non-life insurance, a class of threshold autoregressive nearest-neighbour (TAR-NN) models is discussed. The TAR-NN model extends a major class of parametric nonlinear time series models, namely threshold autoregressive (TAR) models, by introducing a random field structure. It also generalizes nearest-neighbour (NN) models by introducing a regime-switching mechanism. Attention is given to a class of self-exciting threshold autoregressive nearest-neighbour (SETAR-NN) models and their applications to claims reserving. The (strict) stationarity and geometric ergodicity of the SETAR-NN model are discussed. The conditional least-square (CLS) method is used to estimate the SETAR-NN model and some of its nested models. Simulation studies on the parameter estimates are conducted. Applications of the SETAR-NN model and the nested models for projecting future claims liabilities are presented based on insurance claims data.
This talk is based on the following paper:
Tak Kuen Siu, Threshold Autoregressive Nearest-Neighbour Models for Claims Reserving, Econometrics and Statistics, 2022, ISSN 2452-3062.
https://www.sciencedirect.com/science/article/abs/pii/S2452306222000284
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