A review of threshold time series models in finance

Cathy W. S. Chen · Feng-Chi Liu · Mike K. P. So

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Financial Risk and Volatility Modeling Stock Market Forecasting Methods Time Series Analysis and Forecasting

Abstract

Since the pioneering work by Tong (1978Tong ( , 1983)), threshold time series modelling and its applications have become increasingly important for research in economics and finance.A number of books and a vast number of research papers published in this area have been motivated by Tong's threshold models.The goal of this paper is to give a through review on the development of the family of threshold time series model in finance and to provide a streamlined approach to financial time series analysis.It covers threshold modeling, nonlinearity tests, statistical inference, diagnostic checking, and model selection, as well as applications of the threshold autoregressive model and its generalizations in finance.

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References

1986Generalized autoregressive conditional heteroskedasticity 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1992The Cross-Section of Expected Stock Returns 1991Conditional Heteroskedasticity in Asset Returns: A New Approach 1989A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle 1993On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks 2002Dynamic Conditional Correlation 1981The relationship between return and market value of common stocks

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