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Improving forecasting performance by window and model averaging

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  • Prasad S Bhattacharya

    ()

  • Dimitrios D Thomakos

    ()

Abstract

This study presents extensive results on the benefits of rolling window and model averaging. Building on the recent work on rolling window averaging by Pesaran et al (2010, 2009) and on exchange rate forecasting by Molodtsova and Papell (2009), we explore whether rolling window averaging can be considered beneficial on a priori grounds. We investigate whether rolling window averaging can improve the performance of model averaging, especially when ‘simpler’ models are used. The analysis provides strong support for rolling window averaging, outperforming the best window forecasts more than 50% of the time across all rolling windows. Furthermore, rolling window averaging smoothes out the forecast path, improves robustness, and minimizes the pitfalls associated with potential structural breaks.

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Bibliographic Info

Paper provided by Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance in its series Economics Series with number 2011_1.

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Date of creation: 21 Feb 2011
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Handle: RePEc:dkn:econwp:eco_2011_1

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Keywords: Exchange rate forecasting; inflation forecasting; output growth forecasting; rolling window; model averaging; short horizon; robustness.;

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Cited by:
  1. Dimitrios D. Thomakos & Fotis Papailias, 2013. "Covariance Averaging for Improved Estimation and Portfolio Allocation," Working Paper Series 66_13, The Rimini Centre for Economic Analysis.

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