An evaluation of forecasting using leading indicators
Article Abstract:
The use of leading indicators of economic activity to forecast various economic time series is again becoming popular due to perceived forecasting failures by macro-economic systems and developments in leading-indicator theory. However, as in the case of the UK, several problems regarding the use of leading indicators in macroeconomic models should first be solved before they can be considered as essentials for economic forecasting.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1996
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The decomposition of forecast in seasonal ARIMA models
Article Abstract:
A procedure for decomposing the forecast function of a seasonal ARIMA model has been developed. It breaks down the forecast function in terms of the ARIMA model's permanent and transitory components. The procedure simplifies ARIMA interpretation and supports comparisons between ARIMA models and models in state space representation.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1995
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The extended switching regression model: allowing for multiple latent state variables
Article Abstract:
An extended switching regression model with several latent state variables is constructed. Volatility f orecasts of foreign exchange rates using the model dominate forecasts generated using other procedures.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2007
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- Abstracts: Inflation forecasting for aggregates of the EU-7 and EU-14 with Bayesian VAR models. Alternative regime switching models for forecasting inflation
- Abstracts: A fractal forecasting model for financial time series. The importance of interest rates for forecasting the exchange rate
- Abstracts: Forecasting of curves using a Kohonen classification. Highest-density forecast regions for nonlinear and non-formal time series models
- Abstracts: Estimating and forecasting the long-memory parameter in the presence of periodicity. Forecasting volatility
- Abstracts: A semiparametric method for predicting bankruptcy. Identifying the time-effect factors of multiple time series