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Filtering and Prediction in Noncausal Processes

Author

Listed:
  • Christian Gouriéroux

    () (CREST and University of Toronto)

  • Joann Jasiak

    () (York University)

Abstract

This paper revisits the filtering and prediction in noncausal and mixed autoregressive processes and provides a simple alternative set of methods that are valid for processes with infinite variances. The prediction method provides complete predictive densities and prediction intervals at any finite horizon H, for univariate and multivariate processes. It is based on an unobserved component representation of noncausal processes. The filtering procedure for the unobserved components is provided along with a simple back-forecasting estimator for the parameters of noncausal and mixed models and a simulation algorithm for noncausal and mixed autoregressive processes. The approach is illustrated by simulations

Suggested Citation

  • Christian Gouriéroux & Joann Jasiak, 2014. "Filtering and Prediction in Noncausal Processes," Working Papers 2014-15, Center for Research in Economics and Statistics.
  • Handle: RePEc:crs:wpaper:2014-15
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    Cited by:

    1. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.

    More about this item

    Keywords

    Noncausal Process; Nonlinear Prediction; Filtering; Look-Ahead Estimator; Speculative Bubble; Technical Analysis;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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