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In this paper developments in the analysis of univariate nonlinear time series are considered. First a number of commonly used nonlinear models are presented. The next section is devoted to methods of testing linearity, which is an important part of nonlinear model building. Techniques of...
Persistent link: https://www.econbiz.de/10002679532
This article is concerned with forecasting from nonlinear conditional mean models. First, a number of often applied nonlinear conditional mean models are introduced and their main properties discussed. The next section is devoted to techniques of building nonlinear models. Ways of computing...
Persistent link: https://www.econbiz.de/10002847459
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This paper contains a survey of univariate models of conditional heteroskedasticity. The classical ARCH model is mentioned, and various extensions of the standard GARCH model are highlighted. This includes the Exponential GARCH model. Stochastic volatility models remain outside this review. --...
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Applying nonparametric variable selection criteria in nonlinear regression models generally requires a substantial computational effort if the data set is large. In this paper we present a selection technique that is computationally much less demanding and performs well in comparison with...
Persistent link: https://www.econbiz.de/10010310027
The financial and economic crisis has drawn attention to the need for a better understanding of destabilising effects that arise in the financial sector and spill over to the real economy. In turn, weakening economic conditions are likely to feed back to the financial sector, thus giving rise to...
Persistent link: https://www.econbiz.de/10010500365
In this paper we examine the forecast accuracy of linear autoregressive, smooth transition autoregressive (STAR), and neural network (NN) time series models for 47 monthly macroeconomic variables of the G7 economies. Unlike previous studies that typically consider multiple but fixed model...
Persistent link: https://www.econbiz.de/10011807313
In this paper we derive conditions for the conditional covariance matrix to be positive definite in a general vector ARCH model. The conditions can be easily extended to the diagonal vector GARCH model. For the general vector GARCH model, analytical expressions for the conditions in terms of the...
Persistent link: https://www.econbiz.de/10010281189