Forecasting volatility by means of threshold models

The aim of this paper is to compare the forecasting performance of competing threshold models, in order to capture the asymmetric effect in the volatility. We focus on examining the relative out‐of‐sample forecasting ability of the SETAR‐Threshold GARCH (SETAR‐TGARCH) and the SETAR‐Threshold Stochastic Volatility (SETAR‐THSV) models compared to the GARCH model and Stochastic Volatility (SV) model. However, the main problem in evaluating the predictive ability of volatility models is that the ‘true’ underlying volatility process is not observable and thus a proxy must be defined for the unobservable volatility. For the class of nonlinear state space models (SETAR‐THSV and SV), a modified version of the SIR algorithm has been used to estimate the unknown parameters. The forecasting performance of competing models has been compared for two return time series: IBEX 35 and S&P 500. We explore whether the increase in the complexity of the model implies that its forecasting ability improves. Copyright © 2007 John Wiley & Sons, Ltd.     

Critical considerations in the development of systems thinking and practice

This paper is concerned with the development of ‘Systems Thinking.’ In particular, it considers and critiques ‘traditional Systems Thinking’ within the framework of Critical Systems Thinking. Before embarking on such a venture it is necessary to derive a base context from which to develop argument and analysis. Therefore the outline of this paper is as follows: A contextual setting for Systems Thinking, Theoretical Considerations, Soft Systems Thinking and Methodology, and A Critical Systems Thinking (CST) approach. The account of the development of Systems Thinking is followed by a synopsis of a theoretical framework for Systems Thinking which will allow us to gain an understanding of contemporary views. The paper then goes on to review SSM and CST in order to provide a platform for a critique of traditional forms of Systems Thinking. The final section briefly discusses the applicability of CST to the ‘real-world’ context by outlining some current studies being undertaken by the author.