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Mean shifts, unit roots and forecasting seasonal time series

Paap, Richard; Franses, Philip Hans; Hoek, Henk - In: International Journal of Forecasting 13 (1997) 3, pp. 357-368

Persistent link: https://www.econbiz.de/10005428827

Consideration sets, intentions and the inclusion of "don't know" in a two-stage model for voter choice

Paap, Richard; van Nierop, Erjen; Heerde, Harald J. van; … - In: International Journal of Forecasting 21 (2005) 1, pp. 53-71

Persistent link: https://www.econbiz.de/10005428881

Forecasting unemployment using an autoregression with censored latent effects parameters

Franses, Philip Hans; Paap, Richard; Vroomen, Bjorn - In: International Journal of Forecasting 20 (2004) 2, pp. 255-271

Persistent link: https://www.econbiz.de/10005429567

The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production

Franses, Philip Hans; van Dijk, Dick - In: International Journal of Forecasting 21 (2005) 1, pp. 87-102

Persistent link: https://www.econbiz.de/10005429332

Forecasting aggregates using panels of nonlinear time series

Fok, Dennis; van Dijk, Dick; Franses, Philip Hans - In: International Journal of Forecasting 21 (2005) 4, pp. 785-794

Persistent link: https://www.econbiz.de/10005418146

John Geweke, Contemporary Bayesian Econometrics and Statistics, Wiley, New Jersey (2005) (Hardcover, 300 pages) ISBN: 0-471-67932-1.

Paap, Richard - In: International Journal of Forecasting 23 (2007) 3, pp. 529-531

Persistent link: https://www.econbiz.de/10005418258

Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements

Martens, Martin; van Dijk, Dick; de Pooter, Michiel - In: International Journal of Forecasting 25 (2009) 2, pp. 282-303

We evaluate the forecasting performance of time series models for realized volatility, which accommodate long memory, level shifts, leverage effects, day-of-the-week and holiday effects, as well as macroeconomic news announcements. Applying the models to daily realized volatility for the S&P 500...

Persistent link: https://www.econbiz.de/10005428820

Terasvirta, Timo; van Dijk, Dick; Medeiros, Marcelo C. - In: International Journal of Forecasting 21 (2005) 4, pp. 781-783

Persistent link: https://www.econbiz.de/10005428858

Paul D. McNelis, Neural networks in finance--gaining predictive edge in the market, Elsevier Academic Press (2005) ISBN 0-12-485967-4 hardcover, 243 pages.

Van Dijk, Dick - In: International Journal of Forecasting 22 (2006) 2, pp. 407-408

Persistent link: https://www.econbiz.de/10005429531

Forecasting returns and risk in financial markets using linear and nonlinear models

Clements, Michael P.; Milas, Costas; van Dijk, Dick - In: International Journal of Forecasting 25 (2009) 2, pp. 215-217

Persistent link: https://www.econbiz.de/10005418218