SERIE RESEARCH mEmORIMDIl MODEL-FREE ASYMPTOTICALLY BEST FORECASTING OF STATIONARY ~"ECONQMIG7TIME SERIES
نویسنده
چکیده
Given observations on a stationary economie vector time series process we show that the best % periods ahead forecast (best in the sense of having minimal forecast error variance) of one of the variables can be consistently estimated by nonparametric regression on an ARMA memory index. Our approach is based on a combination of the ARMA memory index modeling approach of Bierens (1986a) with a modification to time series of the nonparametric kernel regression approach of Devroye and Wagner (1980). This approach is truly model-free, as no explicit specification of the distribution of the data generating process is needed.
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