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Olga Vasyechko and Michel Grun Rehomme
''A new smoothing technique for univariate time series: the endpoint problem''
( 2014, Vol. 34 No.3 )
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
JEL: C1 - Econometric and Statistical Methods: General
E3 - Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data)
Manuscript Received : May 06 2013 Manuscript Accepted : Jul 08 2014

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