IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v30y2009i3p349-368.html
   My bibliography  Save this article

Generation Of Time Series Models With Given Spectral Properties

Author

Listed:
  • Georgi N. Boshnakov
  • Bisher M. Iqelan

Abstract

. We give a method for generation of periodically correlated and multivariate ARIMA models whose dynamic characteristics are partially or fully specified in terms of spectral poles and zeroes or their equivalents in the form of eigenvalues/eigenvectors of associated model matrices. Our method is based on the spectral decomposition of multi‐companion matrices and their factorization into products of companion matrices. Generated models are needed in simulation but may also be used in estimation, e.g. to set sensible initial values of parameters for nonlinear optimization. We are not aware of any other general method for multivariate linear systems of comparable generality and control over the spectral properties of the generated model.

Suggested Citation

  • Georgi N. Boshnakov & Bisher M. Iqelan, 2009. "Generation Of Time Series Models With Given Spectral Properties," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 349-368, May.
    • Handle: RePEc:bla:jtsera:v:30:y:2009:i:3:p:349-368
    DOI: 10.1111/j.1467-9892.2009.00617.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9892.2009.00617.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9892.2009.00617.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Franses, Philip Hans, 1996. "Periodicity and Stochastic Trends in Economic Time Series," OUP Catalogue, Oxford University Press, number 9780198774549.
    2. Franses, Philip Hans & Paap, Richard, 2004. "Periodic Time Series Models," OUP Catalogue, Oxford University Press, number 9780199242030.
    3. Paul Gilbert, 2000. "A note on the computation of time series model roots," Applied Economics Letters, Taylor & Francis Journals, vol. 7(7), pages 423-424.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Leo Krippner, 2023. "Estimating and Applying Autoregression Models via Their Eigensystem Representation," CAMA Working Papers 2023-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Radu Titus MARINESCU & Aurelian DIACONU & Alexandru BADIU & Alexandru BADIU, 2016. "Analyzing the correlation between GDP and import using a statistical-econometric model," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(10), pages 98-102, October.
    3. Bergmeir, Christoph & Costantini, Mauro & Benítez, José M., 2014. "On the usefulness of cross-validation for directional forecast evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 132-143.
    4. Constantin ANGHELACHE & Ioan Constantin DIMA & Mãdãlina-Gabriela ANGHEL, 2016. "Using the Autoregressive Model for the Economic Forecast during the Period 2014- 2018," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(1), pages 21-31, January.
    5. Madalina - Gabriela ANGHEL, 2012. "Statistical Indicators Used in the Analysis of Portfolios of Financial Instruments," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 60(4), pages 117-120, November.
    6. Constantin Anghelache & Madalina-Gabriela Anghel & Stefan Virgil Iacob, 2022. "Theoretical Aspects Regarding The Models Of The Financial - Monetary Analysis," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 52-58, February.
    7. Madalina-Gabriela ANGHEL & Luminita Madalina CALOTA, 2016. "Statistical-econometric model used in performance analysis of the company," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(10), pages 33-40, October.
    8. Ramona-Maria DIMITROV, 2023. "Forecasts On Some Financial Indicators: A Case Study For S.C.D.A Simnic," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(2), pages 185-211, November.
    9. Amaal Elsayed Mubarak & Ehab Mohamed Almetwally, 2024. "Modelling and Forecasting of Covid-19 Using Periodical ARIMA Models," Annals of Data Science, Springer, vol. 11(4), pages 1483-1502, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Niels Haldrup & Antonio Montañés & Andreu Sansó, 2004. "Testing for Additive Outliers in Seasonally Integrated Time Series," Economics Working Papers 2004-14, Department of Economics and Business Economics, Aarhus University.
    2. Aknouche, Abdelhakim, 2024. "Periodically homogeneous Markov chains: The discrete state space case," MPRA Paper 122287, University Library of Munich, Germany.
    3. Dennis Fok & Philip Hans Franses, 2013. "Testing earnings management," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(3), pages 281-292, August.
    4. T. Manouchehri & A. R. Nematollahi, 2019. "Periodic autoregressive models with closed skew-normal innovations," Computational Statistics, Springer, vol. 34(3), pages 1183-1213, September.
    5. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, September.
    6. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, June.
    7. Dillon Alleyne, 2006. "Can Seasonal Unit Root Testing Improve the Forecasting Accuracy of Tourist Arrivals?," Tourism Economics, , vol. 12(1), pages 45-64, March.
    8. Aknouche, Abdelhakim & Rabehi, Nadia, 2024. "Inspecting a seasonal ARIMA model with a random period," MPRA Paper 120758, University Library of Munich, Germany.
    9. Franses, Philip Hans & van Dijk, Dick, 2005. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," International Journal of Forecasting, Elsevier, vol. 21(1), pages 87-102.
    10. Fok, D. & Franses, Ph.H.B.F. & Paap, R., 2005. "Performance of Seasonal Adjustment Procedures: Simulation and Empirical Results," Econometric Institute Research Papers EI 2005-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Franses, Philip Hans, 2013. "Data revisions and periodic properties of macroeconomic data," Economics Letters, Elsevier, vol. 120(2), pages 139-141.
    12. Franses, P.H. & McAleer, M., 1995. "Testing Nested and Non-Nested Periodically Integrated Autoregressive Models," Papers 9510, Tilburg - Center for Economic Research.
    13. Yang, Lijian & Park, Byeong U. & Xue, Lan & Hardle, Wolfgang, 2006. "Estimation and Testing for Varying Coefficients in Additive Models With Marginal Integration," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1212-1227, September.
    14. Panagiotelis, Anastasios & Smith, Michael, 2010. "Bayesian skew selection for multivariate models," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1824-1839, July.
    15. Koop, Gary & Dijk, Herman K. Van, 2000. "Testing for integration using evolving trend and seasonals models: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 97(2), pages 261-291, August.
    16. Elizabeth Bucacos, 2008. "Real (effective) exchange rate in Uruguay: a periodic cointegration approach," Monetaria, CEMLA, vol. 0(2), pages 265-289, julio-sep.
    17. Jonathan Aylen & Kevin Albertson & Gina Cavan, 2014. "The impact of weather and climate on tourist demand: the case of Chester Zoo," Climatic Change, Springer, vol. 127(2), pages 183-197, November.
    18. Łukasz Lenart, 2017. "Examination of Seasonal Volatility in HICP for Baltic Region Countries: Non-Parametric Test versus Forecasting Experiment," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(1), pages 29-67, March.
    19. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
    20. Beenstock, Michael & Reingewertz, Yaniv & Paldor, Nathan, 2016. "Testing the historic tracking of climate models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1234-1246.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jtsera:v:30:y:2009:i:3:p:349-368. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.