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Uncovering regimes in out of sample forecast errors from predictive regressions

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  • Pitarakis, Jean-Yves

Abstract

We introduce a set of test statistics for assessing the presence of regimes in out of sample forecast errors produced by recursively estimated linear predictive regressions that can accommodate multiple highly persistent predictors. Our tests statistics are designed to be robust to the chosen starting window size and are shown to be both consistent and locally powerful. Their limiting none distributionsare also free of nuisance parameters and hence robust to the degree of persistence of the predictors.Our methods are subsequently applied to the predictability of the value premium whose dynamics are shown to be characterised by state dependence.

Suggested Citation

  • Pitarakis, Jean-Yves, 2020. "Uncovering regimes in out of sample forecast errors from predictive regressions," UC3M Working papers. Economics 31555, Universidad Carlos III de Madrid. Departamento de Economía.
    • Handle: RePEc:cte:werepe:31555
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    More about this item

    Keywords

    Predictive Regressions;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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