Since the pioneering work by Tong (1978, 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
This paper considers the Bayesian analysis of threshold regression models. It shows that this analys...
A growing body of threshold models has been developed over the past two decades to capture the nonli...
Abstract: In this paper we propose a new class of nonlinear time series models, the threshold variab...
In this paper we present some nonlinear autoregressive moving average (NARMA) models proposed in the...
The aim of this paper is to justify the use of threshold autoregressive models in financial time ser...
In modeling of financial time series is widely accepted ARCH model with conditional heteroscedastici...
Financial instruments are known to exhibit abrupt and dramatic changes in behaviour. This paper inve...
The subject of time series analysis has drawn significant attentions in recent years, since it is of...
In the financial market, the volatility of financial assets plays a key role in the problem of measu...
markdownabstract__Abstract__ Two of the fastest growing frontiers in econometrics and quantitativ...
Threshold autoregressive models in which the process is piecewise linear in the threshold space have...
This paper considers a time series model with a piecewise linear conditional mean and a piecewise li...
In this paper we propose a new class of nonlinear time series models, the threshold variable driven ...
Re-visiting the past can lead to new discoveries'-Confucius (551 B.C.-479 B.C.) This paper is a...
markdownabstract__Abstract__ Two of the fastest growing frontiers in econometrics and quantitativ...
This paper considers the Bayesian analysis of threshold regression models. It shows that this analys...
A growing body of threshold models has been developed over the past two decades to capture the nonli...
Abstract: In this paper we propose a new class of nonlinear time series models, the threshold variab...
In this paper we present some nonlinear autoregressive moving average (NARMA) models proposed in the...
The aim of this paper is to justify the use of threshold autoregressive models in financial time ser...
In modeling of financial time series is widely accepted ARCH model with conditional heteroscedastici...
Financial instruments are known to exhibit abrupt and dramatic changes in behaviour. This paper inve...
The subject of time series analysis has drawn significant attentions in recent years, since it is of...
In the financial market, the volatility of financial assets plays a key role in the problem of measu...
markdownabstract__Abstract__ Two of the fastest growing frontiers in econometrics and quantitativ...
Threshold autoregressive models in which the process is piecewise linear in the threshold space have...
This paper considers a time series model with a piecewise linear conditional mean and a piecewise li...
In this paper we propose a new class of nonlinear time series models, the threshold variable driven ...
Re-visiting the past can lead to new discoveries'-Confucius (551 B.C.-479 B.C.) This paper is a...
markdownabstract__Abstract__ Two of the fastest growing frontiers in econometrics and quantitativ...
This paper considers the Bayesian analysis of threshold regression models. It shows that this analys...
A growing body of threshold models has been developed over the past two decades to capture the nonli...
Abstract: In this paper we propose a new class of nonlinear time series models, the threshold variab...