A new smoothing technique for univariate time series: the endpoint problem

Olga Vasyechko () and Michel Grun Rehomme ()
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Olga Vasyechko: ERMES, EA 4441, University Pantheon-Assas, UP2
Michel Grun Rehomme: ERMES, EA 4441, University Pantheon-Assas, UP2

Economics Bulletin, 2014, vol. 34, issue 3, 1419-1430

Abstract: Many filters have been developed to estimate trend-cycle component of time series. Among these tools, moving averages remain the most efficient. In particular, while the symmetric Henderson smoother is applied for trend-cycle estimation in software programs such as X11, for the most recent observations, it may be necessary to use asymmetric filters. In this regard, we propose a new smoothing method, based on the Epanechnikov kernel, to treat endpoints. We then compare this method with the Henderson filter on a data sample.

Keywords: Time Series Analysis; Smoothing Techniques; Asymmetric Moving Average; Kernels (search for similar items in EconPapers)
JEL-codes: C1 E3 (search for similar items in EconPapers)
Date: 2014-07-08
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