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Chapter 15. Forecasting with Bayesian Vector Autoregression

Karlsson, Sune - 2013

This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by …

Persistent link: https://www.econbiz.de/10014025233

An alternative Bayesian approach to structural breaks in time series models

Hauwe, Sjoerd van den; Paap, Richard; Dijk, Dick van - 2011

We propose a new approach to deal with structural breaks in time series models. The key contribution is an alternative dynamic stochastic specification for the model parameters which describes potential breaks. After a break new parameter values are generated from a so-called baseline prior...

Persistent link: https://www.econbiz.de/10011383033

Bayesian prediction with a cointegrated vector autoregression

Villani, Mattias - 1999

vector autoregression is presented. The large degree of uncertainty in the choise of the cointegration vectors is … incorporated into the analysis through a prior distribution on the cointegration vectors which allows the forecaster to … different cointegration vectors are weighted together in an optimal way. The ideas of Litterman (1980) are adapted for the prior …

Persistent link: https://www.econbiz.de/10011584826

Forecasting natural gas prices using highly flexible time-varying parameter models

Gao, Shen; Hou, Chenghan; Bao Hoang Nguyen - In: Economic modelling 105 (2021), pp. 1-14

Persistent link: https://www.econbiz.de/10013367152

Bayesian nonparametric methods for macroeconomic forecasting

Marcellino, Massimiliano; Pfarrhofer, Michael - 2024

Persistent link: https://www.econbiz.de/10014520837

Predicting extreme daily regime shifts in financial time series exchange/Johannesburg stock exchange : all share index

Makatjane, Katleho; Moroke, Ntebogang Dinah - In: International Journal of Financial Studies : open … 9 (2021) 2, pp. 1-18

During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an encouraging alternative to traditional linear models....

Persistent link: https://www.econbiz.de/10012508859