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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

Forecasting Random Walks Under Drift Instability

Pesaran, M. Hashem - 2011

Persistent link: https://www.econbiz.de/10012756639

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

Specification Testing for Nonlinear Cointegrating Regression

Wang, Qiying - 2011

We provide a limit theory for a general class of kernel smoothed U statistics that may be used for specification testing in time series regression with nonstationary data. The framework allows for linear and nonlinear models of cointegration and regressors that have autoregressive unit roots or...

Persistent link: https://www.econbiz.de/10013131589

How costly is it to ignore breaks when forecasting the direction of a time series?

Timmermann, Allan; Pesaran, M. Hashem - 2003

break are likely to perform better over unconditional approaches that use expanding or rolling estimation windows provided …

Persistent link: https://www.econbiz.de/10011506213

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

Optimal Forecasts in the Presence of Structural Breaks

Pesaran, M. Hashem - 2011

This paper considers the problem of forecasting under continuous and discrete structural breaks and proposes weighting observations to obtain optimal forecasts in the MSFE sense. We derive optimal weights for continuous and discrete break processes. Under continuous breaks, our approach recovers...

Persistent link: https://www.econbiz.de/10013117153