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Combination of forecasts across estimation windows : an application to air travel demand
Jungmittag, Andre - In: Journal of forecasting 35 (2016) 4, pp. 373-380
Persistent link: https://www.econbiz.de/10011580774
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Variable selection and forecasting in high dimensional linear regressions with structural breaks
Chudik, Alexander; Pesaran, M. Hashem; Sharifvaghefi, Mahrad - 2020
This paper is concerned with problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows or exponential down-weighting. However, these studies...
Persistent link: https://www.econbiz.de/10012258549
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Modeling and forecasting S&P 500 volatility : long memory, structural breaks and nonlinearity
Martens, Martin; Dijk, Dick van; Pooter, Michiel de - 2004
The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...
Persistent link: https://www.econbiz.de/10011335205
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Forecasting Random Walks under Drift Instability
Pesaran, M. Hashem - 2011
This paper considers forecast averaging when the same model is used but estimation is carried out over different … estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or … more structural breaks. It is shown that compared to using forecasts based on a single estimation window, averaging over …
Persistent link: https://www.econbiz.de/10012714199
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Forecasting Random Walks Under Drift Instability
Pesaran, M. Hashem - 2011
This paper considers forecast averaging when the same model is used but estimation is carried out over different … estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or … more structural breaks. It is shown that compared to using forecasts based on a single estimation window, averaging over …
Persistent link: https://www.econbiz.de/10012756639
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Evaluating Real-Time Forecasts in Real-Time
Ravazzolo, Francesco - 2010
The accuracy of real-time forecasts of macroeconomic variables that are subject to revisions may crucially depend on the choice of data used to compare the forecasts against. We put forward a flexible time - varying parameter regression framework to obtain early estimates of the final value of...
Persistent link: https://www.econbiz.de/10012717174
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Small sample properties of forecasts from autoregressive models under structural breaks
Timmermann, Allan; Pesaran, M. Hashem - 2003
Autoregressive models are used routinely in forecasting and often lead to better performance than more complicated models. However, empirical evidence is also suggesting that the autoregressive representations of many macroeconomic and financial time series are likely to be subject to structural...
Persistent link: https://www.econbiz.de/10011508088
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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
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Forecasting long memory time series under a break in persistence
Heinen, Florian; Sibbertsen, Philipp; Kruse, Robinson - 2009
We consider the problem of forecasting time series with long memory when the memory parameter is subject to a structural break. By means of a large-scale Monte Carlo study we show that ignoring such a change in persistence leads to substantially reduced forecasting precision. The strength of...
Persistent link: https://www.econbiz.de/10003899580
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Forecasting inflation with gradual regime shifts and exogenous information
González, Andrés; Hubrich, Kirstin; Teräsvirta, Timo - 2011
We propose a new method for medium-term forecasting using exogenous information. We first show how a shifting-mean autoregressive model can be used to describe characteristic features in inflation series. This implies that we decompose the inflation process into a slowly moving nonstationary...
Persistent link: https://www.econbiz.de/10009238009