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Measuring the Distance between Sets of ARMA Models

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  • Umberto Triacca

    (Department of Computer Engineering, Computer Science and Mathematics, University of L’Aquila, Via Vetoio Coppito, L’Aquila I-67010, Italy)

Abstract

A distance between pairs of sets of autoregressive moving average (ARMA) processes is proposed. Its main properties are discussed. The paper also shows how the proposed distance finds application in time series analysis. In particular it can be used to evaluate the distance between portfolios of ARMA models or the distance between vector autoregressive (VAR) models.

Suggested Citation

  • Umberto Triacca, 2016. "Measuring the Distance between Sets of ARMA Models," Econometrics, MDPI, vol. 4(3), pages 1-11, July.
    • Handle: RePEc:gam:jecnmx:v:4:y:2016:i:3:p:32-:d:74072
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    References listed on IDEAS

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    1. Maharaj, E.A., 1994. "A Significance Test for Classifying ARMA Models," Monash Econometrics and Business Statistics Working Papers 18/94, Monash University, Department of Econometrics and Business Statistics.
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    6. Terence Mills, 2013. "Breaks and unit roots in global and hemispheric temperatures: an updated analysis," Climatic Change, Springer, vol. 118(3), pages 745-755, June.
    7. Corduas, Marcella & Piccolo, Domenico, 2008. "Time series clustering and classification by the autoregressive metric," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1860-1872, January.
    8. Di Iorio, Francesca & Triacca, Umberto, 2013. "Testing for Granger non-causality using the autoregressive metric," Economic Modelling, Elsevier, vol. 33(C), pages 120-125.
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    Cited by:

    1. Francesca Di Iorio & Umberto Triacca, 2022. "A comparison between VAR processes jointly modeling GDP and Unemployment rate in France and Germany," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(3), pages 617-635, September.
    2. Pacifico, Antonio, 2020. "Bayesian Fuzzy Clustering with Robust Weighted Distance for Multiple ARIMA and Multivariate Time-Series," MPRA Paper 104379, University Library of Munich, Germany.
    3. Mahmoudi, Mohammad Reza, 2021. "A computational technique to classify several fractional Brownian motion processes," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).

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