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Model uncertainty and the forecast accuracy of ARMA models: A survey

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URI: https://hdl.handle.net/10016/20707
ISSN: 2387-0303
UXXI: DT/0000001369
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ws1508.pdf (701.53 KB)
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2015-05-01
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The objective of this paper is to analyze the effects of uncertainty on density forecasts of linear univariate ARMA models. We consider three specific sources of uncertainty: parameter estimation, error distribution and lag order. For moderate sample sizes, as those usually encountered in practice, the most important source of uncertainty is the error distribution. We consider alternative procedures proposed to deal with each of these sources of uncertainty and compare their finite properties by Monte Carlo experiments. In particular, we analyze asymptotic, Bayesian and bootstrap procedures, including some very recent procedures which have not been previously compared in the literature.
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Bayesian forecast, Bootstrap, Model misspecification, Parameter uncertainty, Bootstrap, Model misspecification, Parameter uncertainty
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DES - Working Papers. Statistics and Econometrics. WS