Bootstrap based probability forecasting in multiplicative error models
نویسندگان
چکیده
As evidenced by an extensive empirical literature, multiplicative error models (MEM) show good performance in capturing the stylized facts of nonnegative time series; examples include, trading volume, financial durations, and volatility. This paper develops a bootstrap based method for producing multi-step-ahead probability forecasts valued time-series obeying parametric MEM. In order to test adequacy underlying model, class specification tests is also developed. Rigorous proofs are provided establishing validity proposed methods. The establishes semiparametric MEMs. Monte Carlo simulations suggest that our methods perform well finite samples. A real data example illustrates
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ژورنال
عنوان ژورنال: Journal of Econometrics
سال: 2021
ISSN: ['1872-6895', '0304-4076']
DOI: https://doi.org/10.1016/j.jeconom.2020.01.022