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This paper employs a local information, nearest neighbour forecasting methodology to test for evidence of nonlinearity … in-sample nonlinearity in the series. …
Persistent link: https://www.econbiz.de/10008579497
In this paper, nonlinear models are restricted to mean nonlinear parametric models. Several such models popular in time series econometrics are presented and some of their properties discussed. This includes two models based on universal approximators: the Kolmogorov-Gabor polynomial model and...
Persistent link: https://www.econbiz.de/10008556269
Persistent link: https://www.econbiz.de/10008526441
The paper advances the log-generalized gamma distribution as a suitable generator of conditional skewness. Based on the NYSE composite daily returns an asMA-asQGARCH model along with skewness dynamics is estimated. The results indicate a skewness that varies between sizeable negative skewness...
Persistent link: https://www.econbiz.de/10011398115
The asymmetric moving average model (asMA) is extended to allow forasymmetric quadratic conditional heteroskedasticity (asQGARCH). Theasymmetric parametrization of the conditional variance encompassesthe quadratic GARCH model of Sentana (1995). We introduce a framework fortesting asymmetries in...
Persistent link: https://www.econbiz.de/10011303289
In this paper, we compare the forecasting performance of seasonal and non linear autoregressive models in terms of point, interval, and density forecasts for the growth rates of the Tunisian industrial production, for the period 1976:1- 2006:2. Our results suggest that the point forecasts...
Persistent link: https://www.econbiz.de/10009394334
We compare the forecasting performance of linear autoregressive models, autoregressive models with structural breaks, self-exciting threshold autoregressive models, and Markov switching autoregressive models in terms of point, interval, and density forecasts for h-month growth rates of...
Persistent link: https://www.econbiz.de/10010731704
Nonlinear time series models have become fashionable tools to describe and forecast a variety of economic time series. A closer look at reported empirical studies, however, reveals that these models apparently fit well in-sample, but rarely show a substantial improvement in out-of-sample...
Persistent link: https://www.econbiz.de/10010731787
This chapter reviews the principal methods used by researchers when forecasting seasonal time series. In addition, the often overlooked implications of forecasting and feedback for seasonal adjustment are discussed. After an introduction in Section 1, Section 2 examines traditional univariate...
Persistent link: https://www.econbiz.de/10014023693
The asymmetric moving average model (asMA) is extended to allow for asymmetric quadratic conditional heteroskedasticity (asQGARCH). The asymmetric parametrization of the conditional variance encompasses the quadratic GARCH model of Sentana (1995). We introduce a framework for testing asymmetries...
Persistent link: https://www.econbiz.de/10005771222