In this paper we put forward a new time series model, which describes nonlinearity and seasonality simultaneously. We …-transition nonlinearity and for time-varying seasonality. We find that the model fits the data well for 14 of the 18 series. We also consider … out-of-sample forecasting where we compare forecasts from the SEASTAR models with forecasts from nested models. It turns …

we examine the forecasting performance of various models for seasonality and nonlinearity using quarterly industrial …Seasonality often accounts for the major part of quarterly or monthly movements in detrended macro-economic time series …. In addition, business cycle nonlinearity is a prominent feature of many such series too. A forecaster can nowadays …

we examine the forecasting performance of various models for seasonality and nonlinearity using quarterly industrial …Seasonality often accounts for the major part of quarterly or monthly movements in detrended macro-economic time series …. In addition, business cycle nonlinearity is a prominent feature of many such series too. A forecaster can nowadays …

models turn out to produce statistically equally good results in terms of forecasting the business cycle turning points. …

transition autoregression (STAR). The performance of these models in terms of forecasting the business cycle turns is compared …. Both types of models produce statistically equivalent in-sample forecasting results, whilst the CEI with exponential STAR …

Sisällysluettelo: Kari Takala Studies in time series analysis of consumption, asset prices and forecasting 11 Kari … seven papers deals with three different areas of econometric applications: consumption, asset prices, and forecasting … consumption theories and formulates an error-correction forecasting model for consumption.A single cointegration relationship is …

variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared … topure asMA and no-change forecasts. This is done both in terms ofconditional mean forecasting as well as in terms of risk … forecasting. …