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Empirical Economic and Financial Research pp 9–43Cite as

Decomposition of Time Series Using the Generalised Berlin Method (VBV)

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Part of the book series: Advanced Studies in Theoretical and Applied Econometrics ((ASTA,volume 48))

Abstract

The Generalised Berlin Method (Verallgemeinertes Berliner Verfahren, or VBV) is a flexible procedure to extract multiple unobservable components from a discrete or continuous time series. The finite number of observations doesn’t have to be equidistant. For economic time series (mostly monthly or quarterly data) the interesting components are trend (economic cycle) and season. For financial data (daily, hourly, or even higher frequency data) two components are of interest: a long-time component (length of support, i.e. 201 observations) and a short-time component (length of support, i.e. 41–61 observations). The VBV has control parameters to result in components satisfying subjective preferences in the shape of these components. In a special case the solutions coincide with the known Berlin Method (Berliner Verfahren, or BV) in its base version.

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Authors and Affiliations

  1. Helmut Schmidt University, University of the Federal Armed Forces Hamburg, 22043, Hamburg, Germany

    Hartmut Hebbel & Detlef Steuer

Authors
  1. Hartmut Hebbel
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  2. Detlef Steuer
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Correspondence to Hartmut Hebbel .

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Editors and Affiliations

  1. Dept. of Mathematics and Statistics, University of Konstanz, Konstanz, Germany

    Jan Beran

  2. Faculty of Business Administration and Economics, University of Paderborn, Paderborn, Germany

    Yuanhua Feng

  3. Helmut Schmidt University, Hamburg, Germany

    Hartmut Hebbel

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Hebbel, H., Steuer, D. (2015). Decomposition of Time Series Using the Generalised Berlin Method (VBV). In: Beran, J., Feng, Y., Hebbel, H. (eds) Empirical Economic and Financial Research. Advanced Studies in Theoretical and Applied Econometrics, vol 48. Springer, Cham. https://doi.org/10.1007/978-3-319-03122-4_2

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