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Non-linear time series modelling in financial economics

Chappell D.

Management

2000

Vol. 4, no. 1

85-100

In this paper we give a summary of some of the non-linear time series modeIs. We present and discuss the properties of the random walk model, ARCH (auto-regressive conditional heteroscedasticity) and GARCH (generalised ARCH) classes of models, threshold auto-regressive models, smooth transition autoregressive models, bilinear models and others. We give examples of modelling chosen economic and financial phenomena and we offer modelling strategy based on flow chart.

On the detection of chaotic dynamics in time series: an introduction

Chappell D.

Management

1999

Vol. 3, no. 1

69-82

This paper considers various methods for detecting chaotic behaviour in time series. The possibility of chaotic behaviour is very important from a forecasting point of view. Chaotic behaviour makes anything except very short-term forecasting impossible because of sensitive dependence on initial conditions. We also demonstrate that some common non-linear time series models can exhibit chaotic behaviour.